Note: Descriptions are shown in the official language in which they were submitted.
TITLE
Al engine database that instantly curates music playlists based on user's
temporary experience
requirement
BACKGROUND
Music has been used to influence people behaviour, for example calm in
situations, help them
to study or work or influence them to confess.
Music characteristics can be cataloged in databases or directly in audio files
Music needs to be cataloged by type of help it can provide, like this audio
file is good for
relaxing, or this audio file is good for influencing people to be calm.
Traditionally the music cataloging and indexing, like for example, elevator
music, has been done
by a person, based on his personal knowledge and experience on human
behaviour.
Home automation allows users to select the type of music they want to play
when they arrive at
specific times to their homes. The music can be pulled from a playlist, or
recommendation tracks
curated by humans or automatically curated by algorithms based on their music
type, to name a
few.
SUMMARY
Is a method for an Artificial Intelligence engine to make music
recommendations based on the
users specific temporary environment and short term goals. More specific,
based on data
gathered from the user's smartphone and online social media and calendar
presence, the Al
engine can detect if a calendar event is about to happen or if the user is
riding a shared ride
such as Uber, or based on geolocation if the users are in their houses.
DETAILED DESCRIPTION
Specific embodiments of the technology will now be described in detail with
reference to the
accompanying figures. In the following detailed description of embodiments of
the technology,
numerous specific details are set forth in order to provide a more thorough
understanding of the
technology. However, it will be apparent to one of ordinary skill in the art
that the technology
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may be practiced without these specific details. In other instances, well-
known features have
not been described in detail to avoid unnecessarily complicating the
description.
In the following description of figures, any component described with regard
to a figure, in
various embodiments of the technology, may be equivalent to one or more like-
named
components described with regard to any other figure. For brevity,
descriptions of these
components will not be repeated with regard to each figure. Thus, each and
every embodiment
of the components of each figure is incorporated by reference and assumed to
be optionally
present within every other figure having one or more like-named components.
Additionally, in
accordance with various embodiments of the technology, any description of the
components of
a figure is to be interpreted as an optional embodiment, which may be
implemented in addition
to, in conjunction with, or in place of the embodiments described with regard
to a corresponding
like-named component in any other figure.
In general, embodiments of the invention relate to a method and a network of
devices that
include Workspace Fitness Devices, such as Smart Under-the-desk Bikes and
Smart Desk
Controllers embedded in Smart Sit-and-Stand Desks that connect or "talk" to
one another,
electronically identify individual users, track their activities, connect to a
remote server database
and modify its records. Secondary devices, such as smartphones, can connect to
this network
and remotely monitor and control the settings on the devices such as the
desk's height or the
required tension in the Smart Under-the-desk Bike. The performance data
captured by this
network of devices can be shared to fitness tracking software or devices. By
using our invention,
we plan to motivate employees that sit behind the desk for many hours a day to
improve their
health, performance and overall wellbeing.
Our invention refers to technology based on Smart Desk Controllers, Workspace
Fitness
Controllers embedded in equipment such as Smart Sit-and-Stand Desks and Smart
Under-the-desk Bikes, a brief background of the concept is explained below.
The tasks performed in a desk, be it an office, home, or school desk, have
changed over the
years. Office desks in the middle of the past century tended to be heavy as
they needed to
support heavy typewriters. Additionally, desks in a work office were in open
areas where users
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didn't want people to move their desks away. Some were even made of metal or
heavy
materials.
In its earlier years, the office desk evolved from supporting typewriters to
CRT monitors and a
computer keyboard. Soon, CRT monitors were also replaced by newer computers
with a mouse,
a keyboard, and a lightweight LCD monitor (or a pair of LCD monitors)
connected to a CPU or a
laptop. In essence, office desks have remained the same overtime. Today, most
desks are still
comprised of legs and a flat desktop surface resting at a height of
approximately 30", allowing
the user to sit comfortably in a chair while performing their tasks.
There are studies that claim people who work on a desk for more than 8
continuous hours must
stand up from time to time. It has also been claimed that certain people
experience better
thought processing and focus while standing as opposed to sitting.
A newer type of desk that was previously only suitable to architects and
graphic designers is
making its way to offices, these are the height-adjustable desks commonly
known as
"Sit-and-Stand Desks". Some have a manual crank to adjust the height, others
have an electric
motor - the latter using a controller. Basic controllers only turn the motor
up and down, whereas
some more advanced controllers can sense the height of the desk, have
programmable
memory, and have integrated timers to alert the user when it is time to stand
up and continue
their work. New Sit-and-Stand Desks usually have a pair of legs and must be
connected to the
electricity in order to provide power to the motors that adjust the desk's
height. Most tabletops
are made of solid material, thus, the furniture manufacturers need to connect
all cables, motors,
and connectors below the table top.
Electric motor-driven Sit-and-Stand Desks require a controller to control the
up and down
functions. Some controllers are even calibrated to provide visual feedback
through a display
with the approximate height of the desk at the current position and have
memory settings where
the user can program at which height he/she prefers to use that desk.
Employers and/or users of these types of desks are concerned about the
personal health issues
of seating for long periods of time.
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In the case of offices, a desk is typically used by a single user; however,
other workspaces may
be occupied by desks that don't have a single user, but rather multiple ones.
That is the case of
shared spaces in offices or school classrooms. Electric Sit-and-Stand Desks
need an AC input.
Desks usually hold a monitor and/or a CPU in the form of a desktop, laptop, or
tablet. Such
devices require energy to work or recharge the device.
Fitness stationary bikes are capable to capture the energy generated by
pedaling (such as
dynamo) have been around for many years.
IOT Fitness Devices (I0T-FD) such as standing bikes are available at several
big-end fitness
centers around the globe. These devices are able to transmit captured data
when a workout
takes place. There are different methods for the 10T-FD to capture the ID of
the person using
the device, such methods include RF identification, bar code reading, and
security authorization
(i.e. manual input of the login credentials of the user).
The inventions described in this patent application are related to workspace
fitness as a concept
to live healthier lives in the corporate office environment by introducing
different components
that have a common device - the office desk - that is used by office workers
all over the world.
The concept of this new office desk is a sit and stand desk that elevates
using electronic
motors. Such motors are controlled by a central smart desk controller of our
invention, which
wirelessly connects to smart devices and wearables as well as to other
connected peripherals of
our invention.
References to the smart desk controller are the same as the intelligent
controller or intelligent
desk controller.
The Workspace Fitness Devices (WFDs) described here are different from a smart
gym device
because in a gym, a user goes to the device, identifies himself, and the
device keeps track of
his performance via the user's device or the connectivity via the LAN to the
remote server.
In the case of the Workspace Fitness Devices, the device moves to the user's
workspace and
the user is identified at the smart desk controller. The smart desk controller
then identifies the
user's selected Workspace Fitness Device by identifying the device itself. It
is possible for the
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device not to communicate to the remote server by itself, only via-the smart
desk controller or
the user's smart device (smartphone, snnartwatch).
Since the desk where the smart desk controller is installed may not be the
same desk for the
same person every day, the smart desk controller needs to identify the user in
order to tie up
that individual's performance when using the WFDs.
Figures 1 to 3 describe the first part of our invention, a Smart Desk
Controller that embeds in a
desktop with an optional built-in AC/DC distribution hub. Most commonly used
in a
height-adjustable desk, the controller of our invention replaces the common
keyboard or
controller that operates the height adjustment motors in the height-adjustable
desk. The Smart
Desk Controller apparatus embeds or installs inside the desktop itself, the
Smart Desk
Controller is not exposed on the top of the desktop. In a different embodiment
of our invention,
the Smart Desk Controller may be exposed on the outside or the sides of the
desktop.
Figure 1 shows the Smart Desk Controller of our invention, it uses an
integrated distribution hub
that allows for remote control of the distribution of the energy of the
foreign devices that are
connected to the desk, such foreign devices can be described as monitors,
computers, lamps,
or cell phone chargers. By concentrating all of the AC and DC connections on
the underside of
a height-adjustable tabletop or desktop it minimizes and organizes the amount
of cables that
need to pass underneath the tabletop by providing an all-in-one intelligent
Sit-and-Stand Desk
controller, or Smart Desk Controller, that has the following features:
A way to identify the user, by using a QR code, an NEC tag, a radio proximity
sensor such as a
Bluetooth or similar connection. The Smart Desk Controller of our invention
that also has a
power management distribution, including input and output ports for AC and DC
strategically
placed to better fit in a tabletop and to provide easy access for the user to
such power. A
working switchable light to illuminate the desk drawer immediately below where
the intelligent
desk controller is located. A way to communicate with other devices through a
wired or wireless
network in order to connect to the internet and through RF to communicate with
other Smart
Desk Controllers, IOT devices or Workspace Fitness Devices such as an
intelligent desk chair,
a stand, or a smart under-the-desk bike, as well to other Workspace Fitness
Devices such as a
smart-stepper, a smart-yoga-ball or a smart-balance-board.
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=
The NFC or Near Field Communication is a radio communication protocol in
which, on one end,
a device has an NEC tag and a second device has an NFC reader. The NFC tag
could be
passive or active. Passive NFC tags can take the form of keyless cards that
are used to open
offices - which only require someone to tap. The energy to power the
electronics in the NFC tag
comes from the electromagnetic field generated by the NFC reader. An Active
NEC tag, is for
example, one generated by a device such as a cellphone, which can generate a
string of RF
signals to emulate an NFC tag with an ID number on command.
Bluetooth is another protocol used by two devices with RX/TX capabilities that
use a frequency,
low power radio signal to communicate two or more devices (pair) which
transmit data between
both devices.
Identification by QR code is a process under which, the Smart Desk Controller
has a physical
visible QR code printed on the Smart Desk Controller itself or placed in the
Smart Sit-and-Stand
Desk where the Smart Desk Controller is installed. By using a specific
software in a smart
gadget such as a tablet or cellphone, a user can open the app in the cell
phone, open the
camera, and take a photo of the QR code. The OR code may contain information
pertaining to a
website to open, a URL to follow or a serial number to be encoded, which, in
combination with a
database - such as the one that runs on the remote server for the workspace
Fitness database -
correlates the information regarding the user name, or owner of the cellphone
and the
registered user in the database against the serial number of the Smart Sit-and-
Stand Desk
related to the serial number encoded on the QR code.
Other means of identification include the use of a printed serial number or
code, under which,
the user can input that information into the cell phone app and request the
Smart Desk
Controller to identify him/her as the user of that particular Smart Sit-and-
Stand Desk.
The Smart Desk Controller of our invention also features proximity sensors
that detect the
presence of a person or objects such as a Workspace Fitness Device.
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In a different embodiment of our invention, the Smart Desk Controller has a
built in keypad on
the side of the tabletop with a CPU that controls all of the e-features. The
Smart Desk Controller
can read NEC tags or information coming from NEC tag generators such as
smartphones.
Figure 1 shows the front view of a Smart Desk Controller (100) that includes
one or more AC
outlets (110A, 110B), one or more USB connectors (105A, 105B), a keyboard to
control the
required height of the Smart Sit-and-Stand Desk, the keyboard consisting for
example of
buttons to position the desk down (111) or up (112), one or more memory
buttons (113, 114,
115, 116) where a user can record a position the user wants and manually
override the
requested heights set by using the smart gadget to set the height of the
standup desk. A QR
code (121) and an NEC and RFID reader (120) both used for identification of
the user of the
Smart Sit-and-Stand Desk. In a different embodiment of our invention, the
Smart Desk
Controller rescinds the use of a power distribution hub and acts as all the
other features of a
Smart Desk Controller.
One familiar with the art will appreciate that the keyboard or buttons could
be a detached
external keyboard. One also familiar with the art can appreciate that the
keyboard can be one
from the group of a capacitive keyboard.
A case scenario will be explained to demonstrate one of the uses of our
invention. This example
does not limit the proposed uses of our invention. A user comes in to a desk,
it can be his
assigned desk or an unassigned desk, the user taps his/her phone to the Smart
Desk
Controller, it identifies him/her by reading the NEC tag and communication
thru the network to
the remote server, confirming in the database the name and preference settings
for the Smart
Sit and Stand Desk. Such preferences may include (for example) the desired
times for different
desired positions. For example, at 10am, the user wants the Smart Sit-and-
Stand Desk to be in
the stand position for 1 hour and then, automatically come back down after the
specified
timeframe.
Figure 2 shows a back-view of the Smart Desk Controller, which includes one or
more AC
outlets (110C, 110D, 110E), one or more USB connectors (105C, 105D), a DC
power in
connector (not shown), an AC power in connector (202), a wireless LAN
connector (200) a
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universal connector (201) and an external antenna connector (210) where one
can install an
optional external antenna (not shown).
Figure 3 is a bottom view of the Smart Desk Controller
One familiar with the art will appreciate that the bottom part can be exposed
as part of the Smart
Desk Controller into the Desktop embedding process, which is supported by the
top of the
controller attached to the bottom of the desktop. The Smart Desk Controller
(100) bottom that
includes one or more AC outlets (110F, 110G), one or more USB ports (105 E) a
sensor or light
aperture (301) and a remote-controlled locking mechanism.
Figures 1 to 5 describe one form of our invention, the Smart Sit-and-Stand
Desk, which
comprises of a desktop that sits on at least two telescopic, or height
adjustable legs with a
motor that drives the legs up and down and a Smart Desk Controller with or
without a power
distribution hub. In a different embodiment of our invention, the Smart Sit-
and-Stand Desk has
integrated controls with IOT (Internet of Things) capabilities.
Figures 1 to 5 also describe another form of our invention while using an
ergonomic desktop,
which features a lightweight honeycomb tabletop that rests on top of the
electric driven legs.
The tabletop has an embedded or integrated Smart Desk Controller with buttons
on the side of
the tabletop. In a different embodiment of our invention, the buttons are part
to an external
keyboard that is facing out on a side of the desktop. In a different
embodiment of our invention,
the keyboard is a capacitive keyboard that can be concealed inside the
tabletop itself. In a
different embodiment of our invention, the embedded Smart Desk Controller is
installed in the
ergonomic tabletop in such a way that the built-in buttons or keyboard are in
a side of the Smart
Desk Controller that is facing out by the side or the top of the desktop.
The ergonomic desktop bottom has embedded open trails that can carry the
electrical and data
cables that run internally and exit through one of the legs or through their
designated entry and
exit areas. In a different embodiment of our invention, the Smart Desk
Controller that has built-in
AC outlets with digital wattage meters that run locally and can act as IOT
devices to connect to
a remote server or device, together, with a power management software app a
user can retrieve
power use information or control the delivery of power thru those outlets. In
a different
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embodiment of our invention, the controller also has a built in DC converter
with a USB
connector for powering smart devices.
The Smart Sit-and-Stand Desk of our invention can be used in the office,
cubicle, or the home
office.
The Smart Sit-and-Stand Desk of our invention has an ergonomic tabletop design
that optimizes
space for the 21st century tasks. When our Smart Sit-and-Stand desk is used in
the stand or sit
position, the optimal height for tabletop is co-related to the height of a
person's elbows. In the
same correlation, the height of the eyes of the user need to be horizontal to
the top of the
monitor display. Such correlation needs to be maintained regardless if the
Smart Sit-and-Stand
Desk is in the sit or stand position, although the heights vary, as when a
person is standing up,
the height distance between the tabletop and the monitor height is different.
In a different
embodiment of our invention, the monitor elevation system is a separate
mechanical system
that match the height of the monitor display once the desk is standing and
when the desk is in
the seat position adjusts the monitor height to the preset height.
In a different embodiment of our invention, the Smart Sit-and-Stand Desk
includes an optional
desk drawer with the following features: made from lightweight material, USB
connector or port
inside the desk drawer to provide power charging to a smart gadget device, a
USB extension
from the charging drawer in case the user wants to connect the phone to the
workstation. A
Tampering sensor that could trigger alarms in the Smart Desk Controller or
send information via
their IOT connectivity to other smart gadgets. Our Smart Sit and Stand Desk
also includes a
remotely-controlled electronic lock (can be unlocked by the phone app) and a
height sensor
attached to the bottom of the drawers to prevent accidents when lowering the
desk.
AC in and out of the leg's base to create a chain of connections when using
the desk in open
spaces such as school classrooms or large open work areas. In a different
embodiment of our
invention, the drawers can only open if the smart device is present, detected
by the Smart Desk
Controller, or if the user overrides them via a connection on a website. It
also has a built in
presence sensor that senses when someone is near or seated at the desk, or
while using the
desk if a user is using a Workspace Fitness Device such as an under-the-desk
bike (as an
example). In a different embodiment of our invention, the first top drawer is
a slim one for the
smart gadget.
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In a different embodiment of our invention, the height-adjusting crank and
axles of the Smart
Sit-and-Stand Desk are completely covered to avoid malfunction by tampering or
dust.
Figures 4 and 5 describe another component of our invention - the Workspace
Fitness Devices.
These devices are modifications of conventional fitness devices such as an
under-the-desk
bike, a yoga ball, or a stepper (to name a few), that have some electronics
that we identify as a
Workspace Fitness Device controller. In some parts of this document, we refer
to the
Workspace Fitness Device as such or as an 10T-FD device (Internet of Things
Fitness Device).
Our invention is a Is a network of interconnected Workspace Fitness Devices
(WED) that
connect to other WFDs or to the Smart Desk Controller (SDC).
The SDC controls the main connectivity of the activities to the remote server
and database
(cloud or a similar system). The SDC reads the user's ID and pairs it with the
interconnected
Workspace Fitness Devices connected to the Sit-and-Stand Desk where the SDC is
located or
to another device within the same network of interconnected Workspace Fitness
Devices.
The typical recommendation for a Sit-and-Stand Desk user is to use the stand
function for at
least one hour a day.
In one embodiment of our invention, one characteristic of our invention is
that the WED itself,
does not identify the user, but the WED is part of a paired network of devices
connected to a
user or individual. In essence, a user has a Sit-and-Stand Desk with an
intelligent controller
such as the Smart Desk Controller described above, and a series of peripheral
devices such as
an intelligent chair, an intelligent board for balance, a stationary under-the-
desk bike, and an
intelligent stepper, which we also identify as Workspace Fitness Devices.
A Smart Desk Controller that is installed in a dedicated space within the
tabletop. In a different
embodiment of our invention, the Smart Desk Controller is installed to the
bottom or top of a
tabletop.
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A Smart Desk Controller that also functions as a hub for energy (AC and DC
power)
A Smart Desk Controller that has IOT capabilities (LAN. Wi-Fi and NFC)
The Smart Desk Controller that has sensors to detect the presence of nearby
Workspace
Fitness Devices. Those sensors are one or a combination from the group of
proximity sensors,
electromagnetic sensors, RF communication between the Smart Desc Controller
and the
Workspace Fitness Device, or a triangulation of remote sensing by using the
user's smart
gadgets or smartwatches as bridges to determine by time and distance there's a
close
presence.
One familiar with the art will understand that a user cannot use more than one
workspace
fitness device at a time. For example, he/she can use the chair while the desk
is in the sitting
position, but if he/she positions the desk to the standing position, he/she
can use any of the
peripheral WFDs. Because the Smart Desk Controller has a built-in Workspace
Fitness Device
proximity sensor, by the mere fact that the WFD is close to the desk, that WFD
is identified as
being used by the user of that desk. There is no need for the user to identify
each individual
device as its own. This is practical even when there are offices sharing
multiple WFDs. For
example, an office can have 100 Smart Sit-and-Stand Desks but they may only
need 20 Smart
Under-the-desk Bikes, and/or 20 Smart Balance-Boards.
FIGURE 6 shows how the Workspace Fitness Device has a built-in controller that
is
battery-powered. In a different embodiment of our invention, the WFD can also
harvest power
from the WED itself by capturing user-generated energy while the user operates
the WFD (i.e. a
user pedals a Smart Under-the-desk Bike with a power harvesting mechanism).
The power
harvested is then used to power the WFD controller or Workspace Fitness
Controller.
A WFD can take a variety of shapes and sizes, from a Smart under-the-desk bike
- a type of
stationary bike specifically designed to be low profile and fit under a Sit-
and-Stand Desk - to a
much simpler stepper.
The Smart under-the-desk bike features an adjustable tension resistance to
select the level of
power needed to be applied by the user in order to turn the cranks/pedals.
Whereas the WFD
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stepper has an adjustable sensor to adjust the power the user needs to apply
in order to move
one foot down.
The aforementioned products are just a few examples and it should be noted
that the
embodiment of a WFD is not limited to those previously mentioned.
Each WFD has a controller, such controller can have a CPU or a system-on-card
type
device that can have one or more of the following methods of communication:
Bluetooth, NFC, RFID, Wi-Fi, or any other radio frequency-emitting device that
communicates either directly to the Smart Desk Controller or directly through
to a
remote server.
In a different embodiment of our invention, the WFD controller, or Workspace
Fitness
Controller, also has a GPS that can work under the wi-fi network, cell LAN
network, or
by satellite triangulation. One of the purposes for the GPS is to be able to
locate the
WFD inside a specific geographic area as described in the software app
description in
this document.
The controller can send signals to the remote server in order notify the
server's
database if the WFD is in use, who the user is, the time the device has been
in use, if
the device is reserved for a specific time of the day, and what the WFD's
health status
is, among other data described throughout this document.
The controller also connects to the Smart Desk Controller, which is able to
recognize
who is using that desk, and because of the proximity of the WFD to the smart
desk, the
Smart Desk Controller could determine that the same user of the Smart Sit-and-
Stand
Desk where the Smart Desk Controller is installed, is the same person who is
using the
WFD.
The WFD has sensors and transmitters such as proximity sensors and geolocation
ping
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transmitters that help locate the WFD in a specific geographic area.
A Smart desk controller (600) connects (698) to a remote server (690) which
has a database
(691) and runs its own software (692 not shown). The Smart Desk Controller
also connects
(601) to a Workspace Fitness Device (650) or WFD. The WFD can optionally
directly connect
(699) to the same remote Server (690).
The Smart Desk Controller (600) is installed in the tabletop of the desk (not
shown), it consists
of a cabinet with a Motherboard (610) which has a memory (611), a CPU (612),
and wi-fi / LAN
connectivity (613) to connect to other devices such as other Smart Desk
Controllers (600),
Workspace Fitness Devices (650), or connection (698) with cloud services such
as a remote
server (690) with a database (691), bluetooth, Radio Frequency, Near Field
Connection (NEC),
RFID and other radio connectivity options (614), and Sensors (615) such as
proximity sensors
(616) for detecting a nearby Workspace Fitness Device (650). One familiar with
the art will
notice that there could be other types of sensors not described here and there
could be other
components necessary for the functioning of the Smart Desk Controller such as
batteries,
harnesses, and other such components not mentioned in this description. The
smart Desk
controller (600) also has a power distribution system (618) with adaptors, the
distribution system
consists of AC plugs (622) and DC USB connectors (620) located in different
parts of the Smart
Desk Controller (600) to provide power to other devices such as cell phones,
computers, and
monitors, among others. It also has AC inputs (621) from the power coming from
the leg's
cables (not shown).
The workspace fitness device (650) is one from the group consisting of an
under-the-desk
bicycle, steppers, twisters, boards, yoga balls and other similar devices used
for fitness while
using the regular desk or table, a Sit-and-Stand Desk, or other similar desks.
The workspace fitness device (650) has a controller (660) that connects to the
equipment
adjustments (670) which can include the force, weight, or torque adjustments
(671) (to name a
few). Such adjustments affect the overall performance of the user and should
be considered for
the total fitness monitoring computed within the remote server (690). The
Workspace fitness
device's controller (660) consist of a Motherboard (661 with a memory (662),
CPU (663) and
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connectivity devices (666) such as the bluetooth (666), RFID and NFC (666),
sensors (667)
including proximity and other sensors as well as a LAN or Wi-Fi connection
(668). Such
connections are used to connect (601) with the Smart Desk Controller, or to
connect (699) with
the remote server (690). One familiar with the art, understands that this is a
redundant
connection between the Workspace Fitness Device (WFD), the Smart Desk
Controller, the
smart gadget, and the remote server. As such, the connectivity between each
one of those
devices can be accomplished by using the connected device as a bridge. For
example, the
VVFD can be connected to the Smart Desk Controller, but not to the internet
noro the remote
server or smart gadget.ut because the VVFD is connected to the Smart Desk
Controller, the
Smart Desk Controller acts as a bridge to patch the communication needed
between the WED
and the smart gadget. For example, based on the scenario just explained, a
user can control the
torque of the WED using his/her smart gadget even if the WED is not connected
to the internet
but is connected to the Smart Desk Controller.
The smart gadget is one from the group consisting of a cell phone, tablet,
smartwatch, pc,
laptop, or similar devices.
In a different embodiment of our invention, the Smart Desk Controller has an
HDMI-out port (not
shown in the figures) that connects to the secondary port of the user's
monitor that is present at
the Sit-and-Stand Desk.
When the user is logged into the SDC, the HDMI port shuts down any signal sent
through the
HDMI port, hence, giving priority to the desktop or laptop computer's HDMI
display information
to display to the user's monitor.
When the user is not logged in and is not using the monitor on top of the Sit-
and-Stand Desk,
the SDC can send information through the HDMI port to display information such
as reservation
information from the remote management system as explained in Pat13. That
information can
only be displayed for determined periods of time at specific hours, that way
saving energy from
the monitor display.
Alternatively, in a different embodiment of our invention, the keyboard at the
SDC can wake up
the display information sent to the monitor. In this case, if a user wants to
see information
CA 3020145 2018-10-09
related to the SDC, the SDC can display that information to the monitor as
requested. This is
useful if someone wants to know if the Sit-and-Stand Desk is reserved as
explained in Pat13,
but may want to check until what time the reservation is valid.
Figure 4 shows how a Smart Desk Controller (400) and a Workspace Fitness
Device
communicate. A user (not shown) uses the Smart Sit-and-Stand Desk (not shown)
where the
Smart Desk Controller (400) is installed. With the use of the proximity
sensor, the NFC reader or
bluetooth connectivity, the Smart Desk Controller (400) identifies the
presence of a Workspace
Fitness Device (402). The controller of the WFD (not shown) communicates with
the Smart
Desk Controller (400) and transmits all of the collected data from the user's
performance while
using the WFD.
In a different embodiment of our invention, a Smart Desk Controller (400) that
detects or
communicates in proximity to a smartwatch (401) or smart gadget such as a
tablet or
smartphone that the user is wearing or storing in his pocket (as an example).
The smartwatch
(401) is also in close proximity to a WFD (402). The SDC (400) might not
sense, see or
communicate directly with the WFD (402), but the smartwatch (401) can be the
link between the
SDC (400) and the WED (402) in case no direct connection between the SDC and
the WED is
possible. This is an option to determine if a WFD is located within the
workspace of the user.
One familiar with the art will understand that the determination of the use
can be completed by
having at least a couple of the devices connecting to a remote server or
connecting with each
other and determining the use of the SDC and the WFD based on time, distance,
or physical
proximity to the WFD.
FIG. 5 shows a flowchart in accordance with one or more embodiments of our
invention. While
the various steps in these flowcharts, part of this application, are presented
and described
sequentially, one of ordinary skill will appreciate that some, or all of the
steps presented may be
executed in no particular order, may be combined or omitted, and some, or all
of the steps may
be executed in parallel. Furthermore, the steps may be performed actively or
passively.
FIG. 5 shows a flowchart describing the communication between a Smart Sit and
Stand Desk
with an integrated Smart Desk Controller and a Workspace Fitness Device in
accordance with
one or more embodiments of the invention. Figure 5 shows a Smart Desk
Controller (500) that
CA 3020145 2018-10-09
includes a Motherboard (510) with a memory (511), CPU (51), LAN and Wi-Fl card
(513), a
radio communication mechanism with Bluetooth, Radio Frequency, NEC and/or RFID
(514) and
proximity and other sensors (515, 516, 517), and has an optional display (523)
that is optionally
connected to a power distributor or adaptor (518) with an AC to DC converter
(519) that
provides DC power to foreign devices via a USB connector (520) and has AC
input (51) and AC
output plugs (522). That Smart Desk Controller (500) connects (598) via a
network or the
internet to a remote server (590) that also connects to a database (591). Such
a database
contains the names or personal identifications of the users and keeps track of
their performance
data,preference settings, and other relevant information such as their
prefered devices, average
times of use per devices, etc. The information in the database can be password-
protected and
access to the data can be limited by the user or groups of users. The remote
server is also open
for connections (507) to smart gadgets (505), which can access the information
contained in the
database once account access is validated. The Smart Gadget can communicate
directly to the
Smart Desk Controller (500) using one of two methods of connection, either by
connecting via
the internet relay (507) using the server (590) as a bridge or a direct
communication (506) with
the Smart Desk Controller (500) using either bluetooth or other Radio
Frequency (RF) means.
The Smart Desk Controller (500) may communicate directly to the Workspace
Fitness Device
(550) using either a local connection (501) such as NFC, Bluetooth, or other
RE means of
communication, as well as by using the remote server as a relay or bridge, or
by simultaneously
accessing the information at the remote server database (591).
One familiar with the art will appreciate that the communication between the
Smart Desk
Controller and the WFD can be opened or started using one method, and once the
communication is open, switch to other methods. For example, using an NFC
reader to identify
the device, and once the device is identified, switch to Bluetooth
communication to carry all of
the data transfer needed. Alternatively, one may use the NFC as a means of
opening the
communication, but once identification is performed, use the joint connection
to the Remote
server to communicate between both devices.
One familiar with the art will also appreciate that in order for the WFD (550)
to access data from
the remote server database (591) a direct connection from the WFD and the
database via the
CA 302'0145 2018-10-09
Internet may not be required, as the Smart Desk Controller (500) can be used
as a bridge or
relay to connect the WFD (550) to the Remote server (590) and then to the
database (591).
Viceversa, the Smart Desk Controller can communicate with the Remote server
and the
database without the need of an internet connection if a connection with the
WED is established
and the connection between the WED and the database is active in any other
way.
Figure 6 is a continuation of figure 5 from the point of view of the Workspace
Fitness Device.
Throughout this application, we have been talking about how the Smart Desk
Controller
communicates with the Remote Server and Database and how external devices such
as smart
gadgets, for example: smartphones, laptops, or tablets, can also connect to
the remote server
and access the data stored in the database This part of our invention
corresponds to a software
app. Data captured by the Smart Desk Controller and shared directly to other
devices or a
remote server can be viewed and controlled in a software app. Features of this
app include: the
total amount of time the desk is in the standing position, time in the sitting
position, and time of
use (based on picks from the wattage use and sensors in the tabletop) and
positions (up,
down). In a different embodiment of our invention, the data collection or data
sharing can
optionally be disabled by the administrator. The software administrator can be
the user of the
device, the employee, the employer or the administrator of the office facility
(to name a few).
The data collected from the Smart Desk Controller or the remote server can be
shared with
fitness tracking devices such as fitbits or smartwatches. Secondary devices
can be paired with
the Smart Desk Controller. Such secondary devices include, but are not limited
to:
smartphones, tablets, smartwatches, fitness bands, computers or laptops (to
name a few).
Our invention also includes a software application and a remote cloud
environment service.
Such services, data, and features are available when the Smart Desk Controller
connects to a
secondary wired or wireless device, the secondary device can be one from the
group of a
laptop, PC, smartphone, tablet or a remotely connected server (Remote Server)
that can share
data via an internet connection. The software app features includes the
capability to remotely
control the height of the Smart Sit-and-Stand Desk from the smartphone app,
run statistics on
how long the person sits or stands, or track position changes made by the
user, all of which are
monitored by the Smart Desk Controller.
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In a different embodiment of our invention, the software runs sit and stand
challenges among
colleagues and other sit and stand device users,it monitors and displays the
amount of wattage
used by the devices connected to the desk, it can send alerts if intruders
open the desk
drawers,and it has display alerts when controlling the desk, such as "heads up
to see if there
aren't any objects blocking the desk when coming down".
In a different embodiment of our invention, the software application features
one-touch elevation
for when a user wants to set the height of the Smart Sit-and-Stand Desk to a
predetermined
height with the single touch of a button from a remote secondary device.
Other features include sit-stand tracking - to keep track of the time of the
day and a minute
count of the minutes spent at different positions, a sit-stand reminder that
is audible, visible and
automatic, and a "do not disturb" light that is displayed on the user's
smartphone, tablet, or
similar device with a monitor light, code, or words to allow other people in
the same office space
that the user of that desk doesn't want to be disturbed.
In a different embodiment of our invention, Workspace Fitness Devices and
accessories include
a Smart Mat that can sense or measure the presence of a user. The Smart Mat
may also
capture the energy produced by the user and connects to the Smart Desk
Controller by wired or
wireless connection to provide relevant statistics and data to users.
All peripherals send data to the app, thus, that data can be collected by
other platforms/apps
such as a fitbit for complete overall input from the user.
Figure 7 shows a side view of an under-the-desk bike (700) that is under a
desk (720). In this
example, the under-the-desk bike is a WED; however, one familiar with the art
will know that
there are other WED devices, and all of them share very similar
characteristics. Some examples
include (but are not limited to) a stand, a seat (703), a backrest (702), an
adjusting knob (704),
and in the case of a bike: a set of cranks (701), a base, or rollers (705A and
705B and a
controller (710) with or without a display. The controller that reads the data
from the cranks and
adjusts the torque of the cranks to be either lighter or harder, allowing the
user to exercise at
varying intensities.
CA 302*0145 2018-10-09
Figure 8A and 8B show a side perspective view of a stepper (800) that acts as
WFD. The
stepper consists of a controller (710) and a pair of pneumatic-driven steps
(801A, 801B).
Moreover, the controller is connected to the pneumatic adjustment to increase
or decrease the
pressure of the steps. Figure 8B shows a user (810) using the stepper (800)
WFD.
All of the data from the under-the-desk bike and stepper is sent to the remote
management
server either via a direct connection through a LAN or an indirect connection
via the Smart Desk
Controller at the user's desk. Another method for direct transmission to the
remote management
server is via the user's smart devices. Suitable devices include smartwatches,
tablets, or
smartphone devices that are able to connect to the WFD.
Power is generated/harvested through the turning/pedaling of the cranks (in
the case of an
under-the-desk bike) or through the up and down movement of pneumatic steps
(in the case of
a stepper). The captured energy is then transmitted to the power management
source which
can send it directly to the device's batteries or to power any of the WFD's
components, such as
the controller or motors.
Unlike devices that can be found at a gym, the Workspace Fitness Device is a
portable device
(WFD) that the user moves close to the workstation or area where the user will
use it. Unlike in
a gym, where the user goes to the machine - the machine goes to the user.
The WFD logs the user by having the user tap into the SDC, not the device.
Because the WFD
is within the geographic space or within reach of sensors of the SDC, the WFD
is identified as
being at that particular workspace. Unlike at a gym with IOT devices, where
the user taps into
the fitness device, in our invention, the user taps into the SDC, then, the
SDC connects to the
WFD. In a different embodiment of our invention, the user may tap directly to
the WFD and the
WFD may send information to the server via a direct connection between the WFD
and the
SDC, the WFD via LAN with the remote server, the WFD to the smart gadget of
the user which
then connects directly to the remote server, or the smart gadget to the SDC.
The Ul to locate the WFD could be in the smartwatch, the smart gadget, PC,
Laptop, or web
portal. The Ul has several functions: turn off an audible alarm or alarm
alert, or locate via GPS,
CA 3020145 2018-10-09
as some examples.
The WFD has the capability to have a GPS and an audible alarm as a means for
location
tracking. The smartwatch can request the smart desk controller to turn off an
audible alert at the
WFD when, for example, the user needs to locate the WFD that he/she has
reserved or he/she
wants to use when someone (or no one) is using it within a building floor or
an office space.
With the GPS, the user may track the WFD he wants to use with an audible
alert; thereby,
making it easier for the user to locate the device.
In a different embodiment of our invention, the WFD can lock itself to prevent
its use when a
user or a system-wide alert is sent to the WFD. Reasons to lock the device may
include (but are
not limited to) a timer or the fact that a different user from the one who is
using it in that moment
has it reserved for that period of time. By locking the device, it prevents
unauthorized use and
encourages people to reserve the WFD in the web-portal or management system
when
available.
When a user who has a WFD reserved is looking for it, the audible alert and
the locking of the
WFD functionality may be triggered.
The locking of the WFD can be - in the case of the under-the-desk bike - to
lock the cranks or
tighten them as high as possible so it is uncomfortable or impossible for the
user to pedal the
bike. For the stepper, the locking mechanism can also be to tighten the
adjustment so the
stepper is no longer operational. In the case of the Yoga Ball, there might
not be a locking
mechanism, but the controller could also vibrate in such a way that the yoga
ball might be
uncomfortable for the user to sit on.
The WFD device also has functionality to prevent unauthorized use of the
device in such a way
that when, for example, a child starts using the WFD in an unintended manner
(such as
pedaling excessively rapidly) the WFD device can detect the WFD is being used
in an
unintended manner and it can either lock itself, make it very hard, or turn on
the audible alarm to
prevent unauthorized use. A user can override this feature in case he/she
wants to use it for
higher performance. For example, the WFDs are meant to be used for workspace
fitness, not as
CA 3020145 2018-10-09
gym equipment. In this case, the WFDs are meant for low performance - i.e. low
pace fitness. In
a different embodiment of our invention a WFD could be a gym equipment
alternative.
When the WFD device has mechanical parts that cannot be adjusted automatically
from the
smart gadget controlling it or when the WFD device can sense the user's
preference while in
motion, that information is also stored and shared to the paired smart gadget
devices via means
of the remote management database system. That way, when a user is using a
WFD, the smart
gadget can display the user's preferences at that particular WFD. For example,
a user uses the
under-the-desk bike which has a manual seat height adjustment, thus, when the
user adjusts
the seat to sit at 12", the under-the-desk bike has a sensor that knows the
seat is set at a height
of 12". Furthermore, if the user decides to use the same model of under-the-
desk bike on a
different day and/or it is not exactly the same WFD he/she was using before,
the display on
his/her smart device will display the seat height setting; which, in this
case, will remind the user
that his/her preferred or last setting was at 12" for the seat height. In a
different embodiment of
our invention, when a sensor for the mechanical adjustment is not present, the
system may
request the user to input or take a photo of the height adjustment using
his/her smart device.
That way, the remote management database system can keep track of it.
The WFD also has a way to automatically set the desired settings adjustments
for that particular
user when he/she is using that WFD. For example, a user will start using a WFD
(i.e. an
under-the-desk bike) and it will be paired or sensed by the smart desk
controller or the login
information from the smart device and the WFD will identify the user. Then,
the WFD - in this
case, the under the desk bike - will be set to the required torque and
performance requirements
as set by the user.
In all cases, those commands can be overwritten by the user or an
administrator.
FIGURE 9 shows a flowchart of the operation of the Smart Desk Controller (SDC)
acting in the
presence of a Workspace Fitness Device (WFD). One familiar with the art will
appreciate that
any reference to the Smart Desk Controller should imply that the Smart Desk
Controller is
installed or embedded within the Smart Sit-and-Stand Desk. Step 900 describes
when a SDC
detects the presence of a WFD. In a normal office work day, a user may use the
Smart
Sit-and-Stand Desk in the sitting position for a certain amount of time and in
the standing
CA 3020145 2018-10-09
position for the remainder The positions and activities on the Smart Sit-and-
Stand Desk could
vary depending on the type of position or use the user wants. Part of the
experience of using
our solution is to use peripherals such as the Workspace Fitness Devices
(WFD), including the
Smart under-the-desk bike, which, in some cases could be stored in a different
area than the
workstation, as some office spaces may be space-limited, while others may
allow the user to
share the use of WFDs with office colleagues, given that the use of the WFD
(in most cases) is
for just a small percentage of the time a user spends sitting behind the desk.
Step 902 makes a
determination if a user has signed-in to the SDC or WFD. A user can sign-in to
a SDC or to a
WFD as well, the user does not need to be signed-in on both devices at the
same time, as
described in this flowchart. If the user is not signed-in on either device,
then there is nothing
else to do. If a user is signed-in on at least one of the devices, then he/she
may proceed to step
903 where the SDC and the WFD share the user's preset information. One
familiar with the art
will appreciate that either device could be the one the user is signed-in to.
This makes that
device "device #1", whereas the device where the user is not signed-in to is
known as "device
#2". Device #1 is responsible for transmitting the user's preset information
via the transfer
method that was previously described in this document. Step 904 describes that
the WFD then
applies the adjustments to the presets in that device. Such presets could be
the tension, the
height, or any other variable that can be electronically manipulated while
seated at the WFD
remotely.
Figures 9 through 11 show the relationship between Workspace Fitness Devices,
Smart Desk
Controllers, cloud services, and Software. More specifically, an iOS and
Android application that
allows the user to setup his/her desk based on the information provided
earlier in this document.
The software or mobile application captures the input of the person's height,
then, comparing it
to a table, calculates the positioning of the elements such as the seat or the
WFD, including the
seat, keyboard, and screen heights in relationship with the eyes of the user.
If the user operates the under the desk bike, height and weight are also
considered.
Our invention also includes two other forms of measurement that are taken into
consideration
when using our Workspace Fitness Devices (WFD) - including our under-the-desk
bike, stepper,
CA 3020145 2018-10-09
and balance board. Our database has the required height adjustments for the
use of those
devices and our algorithm performs calculations based on each user's specific
needs.
Also includes the elbow-height range and other data based on the ergonomy of
the person.
That is done with a table made up of different variables, or a custom input
that will match it with
the closest number in our reference table. In a different embodiment of our
invention, the input
is only done in a range instead of fixed values.
In a different embodiment of our invention, the app also calculates the
distance the monitor
should be from the face, the tilt of the monitor, or at what angle it should
be positioned.
The app also recommends the postures to adopt while standing at the Sit-and-
Stand Desk.
In a different embodiment of our invention, the app can also collect
information, such as the ID
of the user, his/her height, preferences (custom made or from patterns
registered at our remote
server's database),or the user's favorite WFD device to use (just to name a
few).
Case scenarios for Challenges description
Mirror co-workers or classroom: a master, set by profile, day, or activity, is
the one who controls
the ergonomyx devices. For example, a teacher may be the master for the
ergonomyx devices
in that classroom. When the teacher raises his/her desk up, all of the other
desks are also
raised unless the teacher is running his/her app in teacher's mode, thus,
controlling the devices.
Mirror co-workers by challenge: a challenge may be set by a leader or by
votes. Whatever
challenge idea receives the most votes is selected to be that week's corporate
challenge. The
challenge may be among co-workers on the same workplace or families within
their separate
work areas and school classes. Online tables for social media are also
available (need to have
a University researcher develop the social media app). Every day could be more
challenging,
and just like poker, a user can choose standards that are higher than the
other members in their
workspace and then wait to see if he/she gets re-challenged to choose even
higher standards.
CA 3020145 2018-10-09
Surprise challenge: occurs when many sign up but they don't know what is next -
the algorithm
randomly chooses for them. The Sit-and-Stand Desk can raise or lower with just
a small time
frame notice depending on the type of challenge.
Other options available from the main menu include:
Share a photo of your sit stand desk
Share your experience (blog type)
Fun facts about Sit-and-Stand Desks
Literature about the use of Sit-and-Stand Desks
The app that also manages for example:
As the app is connected to a centrally located database management remote
server and each
of the Smart Desk Controllers, Workspace Fitness Devices (WFD), smartphones,
and smart
wearables are connected to that database or connected to each other (and at
least one of them
is connected to the remote server), the database management system can be
updated
accordingly.
The app can manage equipment reservation within a predetermined area, be that
an office
space, building floor, an entire building, or a specific geographical area not
mentioned in this list.
The way the equipment reservation works is by understanding the needs of the
user. A regular
office worker, for example, may like to stand for one hour a day on the
"stand" position of the
desk and rest in the "sit" position for the remaining 7 hours of the work-day.
In this case, the
user may want to use the under-the-desk bike for 15 minutes (for example). By
setting up those
preferences, the user may program the smartphone or wearable device to remind
themselves
that it is time to "stand" after approximately 3 hours of work. Once the alert
goes off, the
under-the-desk bike should be used. If this is the case, in most offices it is
expected to have a
ratio of 3 Workspace Fitness Devices (WFD) per every 10 desks in the office.
Those 3 devices
could vary in the form of an under-the-desk bike, stepper, and a balancing
board. The software
algorithm manages the WFD inventory and availability. All office workers
within a certain area
can reserve the available devices to be used within a specific period of time.
The Smart Desk
Controller identifies the geographical location of the last time a particular
WFD has been used
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by someone in the office. By installing additional optional Smart Desk
Controllers in closet
areas, the database system could also locate not-in-use devices that are
stored in office closets,
unused office areas, or empty offices.
Challenges or contests among locally or remotely located coworkers, friends,
or family. As all of
the devices are connected to each other either via a direct or indirect
connection and they all
pass through the same remote server, users can create challenges or contests
when using any
smart-desk-controlled devices, including the Sit-and-Stand Desk and other WFD
devices such
as the under-the-desk bike, stepper, or balance board. Those challenges may
entail
recommendations regarding when the user should undergo a specific activity
based on a
predetermined set of conditions, including the desk's height, the under-the-
desk bike resistance
level, the stepper's resistance level, and the time of day.
Remotely control the settings of the Sit-and-Stand Desk or WFDs. The user can
use the app to
modify or program settings for later use, including the tension of the under-
the-desk bike or the
height of the Sit-and-Stand Desk. Program timers to change those features or
to cancel the
features.
Users can also monitor the use of individual (or multiple) WFD devices
allocated in close
proximity to them through the database. That way, supervisors can monitor the
use of the
devices and the popularity. In extreme cases, mothers can monitor if their
sons are doing the
required exercising or doctors can monitor if a patient is using the required
WFDs.
Our app also works as a gateway for WFDs to connect to the remote server as an
indirect
connection. As most WFDs only have bluetooth and a local Wi-Fi connection
without internet,
the cellphone on which the app is running can work as a gateway between the
WFDs and the
remote server to upload and download information such as settings, current
user settings,
usage data, device health, monitor, etc.
The use of a WFD in a waiting room and a way to promote its use. While waiting
for his/her
appointment, a person could use the WFD to keep active. Since this "guest" is
not a regular
user of the device, as described in this document, the "guest still does
his/her workout and
CA 3020145 2018-10-09
he/she might already be subscribed to a different fitness band / health
monitoring service
different from the one described above.
In this case, the user may tap, take a photo of the QR code, download our
"guest app" or simply
use the device and write a code displayed on the device.
Such code or session number is a reference to the data captured by that WFD
while that
particular user used the WFD. Once in his home, or at his smart gadget, the
user can log into
our web portal or the web portal from another company, and insert that code
into the computer
or smart gadget, the time collected at the WFD is then considered in the
overall fitness
performance of the user.
Since our platform is an open platform, other device-manufacturers can tap
into our system and
download health fitness data from any or our WFDs, users, or Smart Desk
Controllers.
FIGURE 10 is a flowchart that shows how the Smart Desk Controller adjusts the
settings of the
desk based on the user identification when that user has preset preferences
when using that
device - in this case, the Smart Sit-and-Stand Desk. A user preset is a
setting that the user sets.
This preset can be the desired height of the Smart Sit-and-Stand Desk, the
desired height of the
WFD, or any other adjustments such as the tension of the flywheel of the Smart
Under-the-desk
bike (amongst other examples).
Step 1000 describes how the user uses the workspace fitness device while
working at the smart
sit and stand desk. One familiar with the art will appreciate that a user may
use a workspace
fitness device from the group of a smart under-the-desk bike, a smart stepper,
or a smart yoga
ball. When using the device, it is most likely that the user will be located
in front of the desk that
has the Smart Desk Controller installed.
Step 1001 describes how the user makes adjustments to the settings at either
the Smart Desk
Controller (desk) or the Workspace Fitness Device itself.
Once the changes are made, the smart desk controller transmits any changes in
the user
presets to the remote server, where they are stored and accessible to the user
via a web portal
or through the app, as described in step 1002.
CA 3020145 2018-10-09
Step 1003 describes how the next time the user logs to a Smart Desk
Controller, those new
adjustments are recalled, regardless of whether or not it is the same Smart
Sit-and-Stand Desk
or Workspace Fitness Device.
Figure 11 is a flowchart that shows how the Smart Desk Controller can make a
determination of
the presence of a Workspace Fitness Device located nearby (Step 1100). In step
1101, a
determination is requested if a user is signed-in to the Smart Desk Controller
or to the
Workspace Fitness Device. If the user is not signed-in to either device, then
the process ends
(1110). Step 1102 describes, how, if the user has signed-in to at least one of
the
aforementioned devices, then a determination has to be made to check if a user
setup preset for
that type of Workspace Fitness Device has been made. For example, if this is
the first time a
user is using a Smart Sit-and-Stand Desk (workspace fitness device), then, a
user preset for
this user does not exist for this type of device. If the user preset does not
exist, then proceed to
step 1104. Alternatively, in the case that a user preset does exist, then
proceed to step 1103.
Step 1103, adjusts the Smart Sit-and-Stand Desk to match the user's preset,
then the process
ends (1111).
Continuing with step 1104, the smart sit and stand desk must use the default
settings based on
the height of the workspace fitness device in relation to the smart Sit-and-
Stand Desk,then, the
process ends (1111).
Figure 12 is a flowchart that describes the process from the guest or user's
perspective. Step
1200 describes that a guest uses a public WFD. Public WFD are devices that are
not linked to a
personal account but are open for many people to use that same device. WFD
identify
themselves when they are used in a workspace environment and when the devices
are paired
with Smart Desk Controllers. If in the case a guest will use the WFD without
the login credentials
and simply walks up and uses the WFD. The guest may expect to collect the
information or data
captured by the WFD for that workout. In Step 1210, at the end of the workout
the guest records
the session info. The method to record the session info is from one of the
following group: by
reading a OR code displayed on the screen of the WFD or a QR code printed on
the WFD, by
using our app in his/her phone and reading the QR code displayed or printed on
the WFD, by
recording or writing the serial number of the WFD. The WFD keeps track of the
time the workout
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happened and the serial number of the WFD that did the job. The WFD (as
described in other
pages of this document) is connected to a cloud server that keeps track of the
data collected by
the WFD. Step 1220, when at home, the guest logs into a web portal or app. A
web portal from
our company or from the guest's fitness-device provider that is linked to our
database where the
record of his workout is kept. Step 1230, guest enters recorded session info.
By correlating the
recorded session info with our database, the data from that recorded session
can be retrieved
by either a screen print or a data file that can be used to integrate into the
guest's fitness
tracking device or system. Step 1240, the workout info is retrieved and can
become part of that
guest's fitness tracking data. The web portal or app either integrate that
workout into the guest's
personal daily record or provide the equivalent to manually input into other
devices.
Figure 13 shows a chart describing the relationship between the workspace
fitness ecosystem,
the user, and the machine learning/artificial intelligence database/engine.
The user (1300) is the one signing-in or using the described devices. A user
is at a Smart
Sit-and-Stand Desk (1301), which, simultaneously connects to the Remote server
(1319). If a
Smart Under-the-Desk Bike (1302) is present it is connected to the Smart Sit-
and-Stand Desk
(1301) wirelessly. At the desk, a Desktop Computer, laptop, or tablet (1305)
that has a software
installed, that software produces a session as described in figure 17. Any
device connected to
the remote server is enabled to create a session, which, for example, is a
window of time with a
start and finish timestamp that includes the data values collected from
different devices.
Sessions can be initiated using technologies such as NFC, Bluetooth or through
a browser
using a web-app. The Desktop Computer, laptop, or tablet (1305) also connects
to a remote
server via the internet. The Desktop Computer (1305) sends data regarding the
usage of the
keyboard, mouse, and display. One familiar with the art will appreciate that
usage data of other
types of peripherals can be sent.
Continuing on Figure 13 in a different embodiment of our invention, usage data
may not include
the content, as it is not as much interest to the Artificial Intelligence
Engine (Al engine) as the
use of the keyboard and mouse movements. One familiar with the art will
appreciate that, when
a tablet with a touchscreen is present, there might not be a need to have a
keyboard or mouse,
as the touchscreen serves as an input device for the tablet, and thus, the
data collected
includes the touchscreen activity on the tablet.
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Continuing on Figure 13, the Desktop Computer (1305) that is operated by the
user (1300) that
has a smartphone (1303) or any other smart gadget such as a tablet with our
software
application running. One familiar with the art will appreciate that Desktop
computer may be
synonymous of a laptop, notebook or other types of computing devices. One
familiar with the art
will also appreciate that the smartphone can also have a direct connection and
communication
with the Smart sit-and-stand Desk or Smart under-the-desk Bike at the same
time, or that the
Smart Under-the-desk bike can connect directly to the cloud services as
described in the
paragraphs above. One familiar with the art will also appreciate that, as the
smartphone is a
personal device with the user's credentials installed on it and since the
smartphone stays ON
most of the time, it recognizes that it's being operated by the owner of the
device.
Continuing with Figure 13, the user (1300) might use headphones (1306) that
are connected by
a wired or wireless connection to the smartphone (1303). One familiar with the
art will also
appreciate that the description of the headphones are just an example to
identify that the
smartphone is providing sound output. The meaning of the presence of a pair of
headphones
can be interchanged to anything that acts as a sound output device, including
a PA system
connected wired or wirelessly to the phone, or the smartphone's built-in
speakers or speaker
box, which is connected by a wired or wireless connection to the smartphone.
The user (1300) may also wear a fitness tracking device (1304) such as a
fitness band or
smartwatch that collects fitness data such as movement and heart beats or
Beats Per Minute
(BPM) information. The fitness tracker (1304) may also be connected to the
internet and the
remote server (1319). The fitness tracker may have a built-in optical heart
rate monitor which is
a personal monitoring device that allows one to measure one's heart rate in
real time or record
the heart rate for later study. An optical heart rate monitor is largely used
by performers of
various types of physical exercise.
One familiar with the art will appreciate that any of the smart devices such
as the Smart
Sit-and-Stand Desk (1301), the Smart Under-the-Desk Bike (1302), the
smartphone (1303), the
fitness tracking device (1304), and the Desktop Computer, laptop, or tablet
(1305) may connect
directly to the remote server,via a connection to the Internet, or indirectly
to the connection
acquired by a local connection between one of these devices and a device that
is connected to
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the Internet or to the remote server. For example, the Smart Under-the-Desk
Bike (1302), which
may not have a connection to the internet, but, since it is connected to the
Smart Sit-and-Stand
Desk (1301), it can use the Smart Sit-and-Stand Desk (1301) as a bridge (1320)
to connect to
the remote server (1319).
The remote server is connected to the Machine learning/Artificial Intelligence
Database (1333).
The user might be using other devices (1310) that could also connect to the
ecosystem and
feed data to the Machine learning/Artificial Intelligence Database (1333).
Other devices may
include devices that are smart or not. Smart devices are devices that connect
to the remote
server (1319) and from there, are able to send data to the workspace Fitness
ecosystem.
Non-smart devices are devices that may not connect to the remote server and
their use must be
manually reported (via the smartphone app or other mediums) to the remote
server so the
Artificial Intelligence Engine (Al engine) takes this input into
consideration. One familiar with the
art will appreciate that in this list, the other smart devices can be one from
the group of a Smart
Chair, a Smart Stepper, a Smart Treadmill, or a connected mat, to name a few.
Non smart
devices can be for example, but not limited to devices from the group of
reflexology foot paths
or acupressure boards, which are an alternative medicine tool that gives a
user the benefits of
acupressure. Most of these mats are made from plastic, cotton, or other
materials with plastic
acupuncture points that stimulate specific areas of the body to bring pain
relief or help with other
issues. The density of these acupressure points is very high, so many people
refer to them as
"bed of nails" mats.
Our invention is a machine learning / Artificial Intelligence engine that is
used in combination
with Workspace Fitness Devices such as the Smart Sit-and-Stand Desk and/or the
Smart
Under-the-Desk Bike. Our invention analyses the collected data from a
workspace fitness
environment and determines the best type of sensory input that can influence
the activity
performance of that particular user when operating a workspace Fitness Device.
Desk user's position and activity patterns while at the office can give some
indication regarding
the user's ergonomic deficiencies or needs. For example, Doctors recommend
that patients with
back pain use a sit and stand desk. But doctors don't know what the best time
of day or amount
of time for that patient to use it is. The best time for that patient to use
the sit and stand desk in
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a standing position might be right after lunch time in order to increase the
blood pressure and
reduce obesity. Other users may have the same needs, but their recommended
times of the day
and amount of time to work standing may vary. To make this more complex, a
user could stand
barefeet - or with shoes - in a carpet, hard-floor, or in an anti-fatigue mat.
The single fact that we
have a user that has been working all his life while seated and suddenly we
ask him to work
standing for X amount of time everyday has an influence in his health and work
productivity.
Some researchers have studied such influences on the personal health and work
productivity of
the users and their conclusion is that using sit and stand desks is generally
better for users'
personal health and overall productivity within the workplace. The need to
find the optimal
amount of time and the best times to work while sitting, standing, and moving
is of great
importance. Large corporations even employ ergonomic experts who evaluate, in
a person by
person basis, their employees' particular ergonomic needs. Those consultants,
most of the time
recommend what type of furniture to buy - most commonly, ergonomic chairs and
sit and stand
desks - and, as if they were a personal fitness coach at a gym, they'd give
employees a
schedule of activities to do while working - In this case, when to sit, stand,
or move. Most of the
time, this information comes in non-personalized charts that are handed to the
employees.
A Workspace Fitness experience doesn't necessarily only include a sit and
stand desk,there are
plenty of other fitness devices that can be used while working behind a sit
and stand desk,
including the under the desk bike, steppers, ellipticals, treadmills, or yoga
balls to name a few.
Once we put those components into play, we have other sensorial factors such
as ambiance
which may include: noise, music, or scents.
The need to automate the process to evaluate a person's needs and optimal
activity schedule
while working is constant and growing.
Sensorial input includes Music, Kinetic, Audible, and scent-therapy. In the
case of music, it
selects the type of music or specific song based on the music's properties,
including factors
such as (including but not limited to) rhythm and tempo.
Figure 14 shows a diagram with the data collected from the devices. One
familiar with the art
will appreciate that the information reflected here is the description of some
of the items that are
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the most interest for the Machine learning/Artificial Intelligence Database
(1333). The
workspace fitness device session data (1400) includes (but is not limited to):
the User ID, the
Revolutions per Minute (RPMs) and the intensity set at the Workspace Fitness
Device. For
example, if the Workspace Fitness Device is a Smart Under-the-Desk Bike, then,
the user may
have an intensity level from 0 to 10, the intensity level on a Smart sit-and-
stand desk is the
resistance level or tension on the flywheel that makes the pedaling softer or
harder for the user.
The fitness tracking device session data (1410) is the one that is collected
from the fitness
tracking device (1304 fig 13), which includes: Movement data and beats per
minute (BPM) or
Heart rate reading, which, is the speed of the heartbeat measured by the
number of
contractions (beats) of the heart per minute (BPM). The heart rate can vary
according to the
body's physical needs, including the need to absorb oxygen and excrete carbon
dioxide. It is
usually equal or close to the pulse measured at any peripheral point.
Activities that can provoke
change include physical exercise, sleep, anxiety, stress, illness, and
ingestion of drugs.
The smartphone session data (1420) is the one that is collected from the
software application
running in the smartphone (1303 fig 13). It includes: Music being played,
Sound level, External
sound, and decibel levels. The music is identified by trackname and metadata.
It may include
the name of the artist, recording studio name, composer, and other data. The
metadata in the
track may include rhythm, tempo and timbre, among other information. The sound
level is the
output level from the smartphone to the sound output. The external sound and
decibel level
measurement comes from the microphone at the smartphone that captures the
ambience sound
and interprets what type of sound is in the ambiance, including (but not
limited to) voices,
machines in the background, engines, and others, just to name a few. In a
different embodiment
of our invention, video picked up from the microphone can also be used to
identify the light
ambience of the room where the user is operating the workspace fitness device
and the
environment around the workspace.
The Desktop Computer, tablet, or laptop session data (1430) is the one
collected from the
software installed in the Desktop Computer, tablet, or laptop (1305 fig. 13),
which includes:
kinetic data coming from typing on the keyboard and moving the mouse, and the
display data
which may include the name of the app that is selected as the app that is
running primarily
where the input from the keyboard and mouse is happening.
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Figure 15 shows a flowchart describing how the music is classified and
correlated to stimuli
options.
Step 1501 - Music is classified and tagged based on tempo estimation and beat
tracking, and in
some cases - based on spectral features and timbre similarity with other
tagged music.
Step 1502 - Music classification is matched with the user's needs based on the
type of influence
or stimulus required to produce the expected results. We use the tagged music
with automatic
tempo estimation and beat tracking to recommend music that is specifically
tailored to the
performance needs and listening references of an individual using Workspace
Fitness Devices.
This provides a unique user experience, especially for the young-adult age
group which is
deeply connected to music. The software selects and recommends, from a
provided music
selection, based on information captured by the measurements acquired by the
sensors that are
part of the Workspace Fitness Devices, including the level of physical
activity that is acquired by
the sensors, as well as the customized fitness goals of each user.
The connection between music as a way to regulate physical activity has long
been known. For
example, music and rhythmic stimuli have been used for the rehabilitation of
gait disorders. Gait
abnormality is a deviation from normal walking (gait). Watching a patient walk
is the most
important part of the neurological examination. Normal gait requires that many
systems -
including strength, sensation, and coordination - function in an integrated
fashion.
The proposed patent application is based on using pre-classified music tracks
that had
embedded content analysis, and more specifically, tempo estimation and beat
tracking
functionalities. Automatic beat tracking algorithms connected to measured
activity have been
proposed to inform playlist generation for runners (Nuria Oliver and Lucas
Kreger-Stickles.
Papa: Physiology and purpose-aware automatic playlist generation. In ISMIR,
volume 2006,
page 7th, 2006) . In this work, the authors found that it was easier to use
music to reduce the
running pace than it was to increase it. The use of music in running was
further investigated by
other researchers (Joyce HDM Westerink, Arjan Claassen, Tijn Schuurmans,
Wijnand
IJsselsteijn, Yvonne de Kort, Suzanne Vossen, Yuzhong Lin, and Guido van
HeIvoort. Runners
experience of implicit coaching through music. In Sensing Emotions, pages 121-
134. Springer,
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2010). Real-time auditory feedback has been shown to improve running cadences
(Jutta
Fortmann, Martin Pielot, Marco Mittelsdorf, Martin B "uscher, Stefan Trienen,
and Susanne Boll.
Paceguard: improving running cadence by real-time auditory feedback. In
Proceedings of the
14th international conference on Human-computer interaction with mobile
devices and services
companion, pages 5-10. ACM, 2012). More recently, the use of heart beat
measurements has
been explored as a way to inform listening to music (Shahriar Nirjon, Robert F
Dickerson, Qiang
Li, Philip Asare, John A Stankovic, Dezhi Hong, Ben Zhang, Xiaofan Jiang,
Guobin Shen, and
Feng Zhao. Musicalheart: A hearty way of listening to music. In Proceedings of
the 10th ACM
Conference on Embedded Network Sensor Systems, pages 43-56. ACM, 2012). We
plan to
apply adjacent concepts for office workers. The differences are big as runners
perform high
cardio physical activities vs. an office worker who can only perform low
cardio activities while at
the office by using the Smart Under-the-Desk Bike, for example.
Step 1503 - Music is made available to the user in the form of an audio file.
Music can be
presented in the form of an audio file in the user's device, an online music
service such as
Pandora or on-demand audio, stored in the cloud, or available through any
other electronic
means. One familiar with the art will appreciate that the audio files include
metadata containers
such as the ID3, which is used in conjunction with the MP3 audio file format
that stores
information such as the title, artist, album, track number, and other
information about the file; in
this case, the metadata we use to classify the tempo, rhythm and other
identifiers about the
audio file. One familiar with the art will also appreciate that the audio file
may be the property of
the user or the user acquires access or rights to the music in any other
means. The music can
be tagged, for example, but is not limited to metadata stored in the audio
file itself, making the
music track part of a playlist, storing the music file under a separate
folder, or any other similar
means of classification and indexing.
Step 1504- End
In a different embodiment of our invention, one familiar with the art will
appreciate that the
sensorial experience can vary from auditive, to kinetic, to aromatic. In such
cases, the process
is the same, classify and tag the sensorial experience content. In the case of
aromatic, the
fragrances that are known to influence the behaviour of a person in an
expected way. For
example, if the scent of pine helps the user concentrate, and the sensorial
experience required
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by the user is to concentrate to think, then, the system sends commands to a
smart home
fragrance box or fragrance diffuser (i.e. a device that connects to WiFi and
can be controlled
from our application that has 2 or more different capsules or containers and
use the app to
control the level and intensity of each scent). The scents can be mixed &
matched between a
variety of options. The fragrance diffuser uses fans with adjustable speeds to
diffuse scents
throughout a room. Current Smart fragrance diffusers are available in the
market from brands
like Moodo, Agan Aroma, or several aroma diffuser machines coming from south
east Asia. One
familiar with the art will appreciate that in combination, or instead of
scents or fragrances, the
diffused product could be hormones that also help stimulate the user.
Continuing with the sensorial experiences, in the case of the kinetic
sensorial experience, it
includes(but is not limited to) the movements, vibrations and punctures that
might influence the
user's "feeling" sense. These include the use of a Smart Office Chair with
integrated motors
(insert Pat02) that provide massages or physical stimuli to the user on-demand
with signals to
power on, off, and intensity coming from the Al engine. The kinetic stimuli
may also include the
use of sensorial stimulants, such as anti-fatigue mats with or without motors,
pedals with
different types of surfaces or reflexology foot paths, and acupressure boards.
Or a smart mat.
Figure 16 shows a flowchart describing one embodiment of our invention
Step 1601 - Determination that the user wants the Al engine to help him get a
better sensorial
experience
Step 1602 - Determination that the sensorial experience type is an auditive
experience
Step 1603 - The Al engine software receives the session data with the data
captured from the
workspace fitness devices, smart under the desk bike, smart sit-and-stand
desk, fitness tracking
device, Desktop Computer, and Smartphone.
Step 1604 - the Al engine software tracks the performance of the user and,
Step 1605 - The software sends a command to the smartphone to play a specific
music at a
certain decibel level.
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Step 1606 - The music plays - through the snnartphone's headphones - a music
track tagged to
match the requested session experience
Step 1607 - After a set amount of time, reviews if the music recommendation
produced the
expected results. One familiar with the art will appreciate that by injecting
a sensorial experience
with music to a user using an Under-the-Desk bike while working may not change
the speed of
the pedaling in the next 10 seconds after the music is inflicted, this may
vary from individual to
individual where this data is also captured by the Al engine to consider and
be used as a
baseline of expected time to view results. For example, an individual may be
pedaling at 20
RPMs and, based on their performance goals set before the session, the user
might need to
pedal at 40 RPMs, thus, the system injects a new music track that matches the
expected
results.
Step 1608 - if the expected result is reached. Then End; if it is not met,
then back to Step 6.
Figure 17 shows a table with the session data collected from the devices. In
this case, showing
the data collected from the Desktop Computer/laptop/tablet, the smartphone,
the fitness band,
the Smart Sit-and-Stand Desk and the workspace fitness device (Smart Under-the-
Desk Bike).
The information is collected in real time but may only be represented as
averages over a
specific period of time. In this example, the table is separated by 5 minute
increments starting
when the user turned on the Desktop Computer at 9:10am, followed at the same
time by a
tapping or log-in process performed with the smartphone by tapping it to the
Smart
Sit-and-Stand Desk to initiate a session at the Smart Sit-and-Stand Desk at
the same time, it
was also detected that a Smart Under-the-Desk Bike was present and connected
to the
ecosystem. The user was wearing a fitness band, it transmitted a 50-60 heart
rate and there
was no song playing at the user's smartphone.
Continuing with the example, at 9:15am the height of the smart sit and stand
desk was identified
at 112 cm. Music (Vivaldi seasons, spring) started to play. Other information
such as music
metadata or audio levels were not captured in this example. One familiar with
the art will
CA 3020145 2018-10-09
appreciate that other values coming from input sources such as sensors,
input/output ports, and
others can be also collected for analysis in the machine learning / Al
database. Along the
collected session data from 9:10 am to 9:50 am there are many factors that are
considered as
input to the machine learning / Al database, one of the most important ones is
the music
selection at the smartphone, the BPM, and the RPM readings.
One familiar with the art will appreciate that the BPM are read in real time,
but in some
embodiments of our invention, an average in a predetermined amount of time
must be used in
order to have better data to process.
At the smartphone, the music data can include the music ID and the metadata
tag. As explained
before, the metadata tag may include the rhythm, tempo, and other relevant
information. If that
data is present, the smartphone can send that data as part of the session.
In a different embodiment of our invention, when the metadata with the rhythm
and tempo is not
present, the smartphone sends the data with the music ID. At the remote
server, the music ID
can be compared with a database of pre-classified music that has the data with
the rhythm and
tempo required.
In a different embodiment of our invention, when the workspace fitness device
that is identified
is a Smart Desk Controller (not necessarily a full Smart Sit-and-Stand Desk),
the data captured
is the same as the data needed from a Smart Sit-and-Stand Desk. Such data is
the desktop
height, time, and user ID (to name a few).
Figure 18 shows a pair of surveys, the first one taken just 30 minutes after
the session example
from figure 17. The second one taken 4 hours after the same session. There
could be more
surveys collecting the same or different data. The data collected by these
surveys is just an
exemplification of the data that is collected and then fed to the Machine
Learning / Al database
engine.
These surveys are sent to the user to their smartphone via a message sent
through our
software app running in their smartphones. One familiar with the art will
appreciate that the
messages and the surveys could be sent in other means, including channels such
as (but not
CA 3020145 2018-10-09
limited to): SMS messages, email messages, phone interviews, observational
studies, or a
survey sent to the user via our app installed at their Desktop Computer,
laptop, or tablet. In a
different embodiment of our invention, the answers to the survey can be
collected by having the
user access a web portal or a software application at their discretion where
they can find the
questions or surveys related to their sessions.
One familiar with the art will appreciate that the surveys collected from the
users are inputs of
data collected to be analysed using statistical techniques in order to find
the best combination of
tasks needed to be performed at the workspace fitness devices with the
expected results, which
is at this time, possible through the surveys. Other methods to capture such
data are through
3rd parties such as doctors or monitors who evaluate the user.
In a different embodiment of our invention, the surveys are replaced by
devices that measure
the happiness, fatigue, and energy levels of a user by evaluating chemical and
physical data
from medical equipment.
The survey includes a timestamp and a session ID (from figure 17 example)
describing the time
the session started and finished. One familiar with the art will appreciate
that a session could be
any predetermined amount of time with a start and end time. For the purposes
of this
exemplification, we show a data collection (from figure 17 from 9:10-9:50 am
on October 10,
2018. The survey includes a timestamp of when it was sent and a second
timestamp with the
time the user answered the survey.
Next are the questions asked to the user. In this case, the questions showed
here are just
examples, actual surveys could vary depending on the type and number of
questions. A value is
giving to each answer, such values are the ones considered by the Machine
Learning / Al
database engine.
Figure 19 is a table showing examples based on figures 17 and 18 for values
collected from the
workspace fitness ecosystem. The first set of readings are from the use of a
Smart
Under-the-Desk Bike while using a Smart Sit-and-Stand Desk in a high position.
For each
relationship, a value is given as a value code. VC1 is the relationship
between the tempo of the
music and the RPMs of the pedals/crankshaft of the Smart Under-the-Desk bike.
The VC2 value
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code is the relationship between the tempo of the music and the BPMs of the
user's heart rate.
VC3 is the relationship of the intensity of kinetic activity at the keyboard
and/or mouse and the
RPMs generated at the pedal/crankshaft of the smart under-the-desk bike. VC4
is the Desktop
Computer display and RPM relationship, where the Desktop Computer display data
may include
the name and type of the application that is open and active (where the mouse
and the
keyboard are inputting the data) this information is used to identify what
type of application the
user was using to identify a relationship between certain activities at a time
of the day. For
example, reading emails in the morning will include heavy use of a keyboard
and mouse, thus,
slowing the pedaling at the bike and reducing the output of RPMs detected.
One familiar with the art will appreciate that it is not necessary to capture
the content of the
keystrokes when typing, but to understand the keys per minute typed on the
keyboard. The
same goes for the mouse. For our machine learning / Al database engine, it is
not important to
understand where the mouse is pointed at or clicked, but to understand how
many times a
mouse pointer moved and for how long, in order to understand the relationship
between the use
of a mouse and other activities like standing or using the Smart Under-the-
Desk Bike.
The next set of values described in Figure 19 are the ones collected while the
user used the
Smart Sit-and-Stand Desk in a standing position when no Smart Under-the-Desk
Bike nor other
workspace fitness device was present. VC5 is the relationship between the
tempo and the BPM,
VC6 is the relationship between the tempo of the music and the kinetic
activity value coming
from the use of the keyboard and mouse. VC7 is the tempo and display value
relationship.
The last set of values in this example are the ones coming from the smart sit-
and-stand desk in
a sit position where VC8 is the relationship between the tempo and the BPM.
VC9 is the
relationship between the tempo of the music and the kinetic activity value
coming from the use
of the keyboard and mouse. VC10 is the tempo and display value relationship.
One familiar with the art will appreciate that the values in this example can
also be modified by
the software depending on the type of experience required by the user and on
improvements
based on the statistical techniques used to learn with the collected data.
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Figure 20 shows the collected data values and the relationship or influence
between the Value
Codes collected from the devices (2001) and the value of the data collected
from the surveys
(2002) also known as User Survey Values. By applying machine learning
statistical techniques
the goal is to have the User Survey Values to be as close as possible to the
optimal setting.
This Optimal Setting can be set by the software, the user, their employers,
medical doctors, or
any other person who may have access to modify such settings with the interest
of improving
the experience of the user while using the workspace fitness devices.
One familiar with the art will appreciate that with the data collected and
processed, the machine
learning / Al database engine will make suggestions or force the user to make
changes. The
machine learning / Al database engine will also collect data from such changes
and optimize the
recommendations, run the changes again until the software makes a
determination that the user
no longer wants to have his/her performance analysed while using a workspace
fitness device
and only wants the Workspace Fitness Device ecosystem to enforce, or recommend
the optimal
identified workspace sessions.
Our invention uses a statistical technique that gives a computer system the
ability to "learn" with
data without being explicitly programmed. By modifying the combination of
settings at the
workspace fitness device and the sensorial input in a specific session,
different value codes are
received. Moreover, in direct relation to those value codes, user survey
values are also received
for that session. If the survey values received are closer to the Optimal
Setting, then this
combination of settings is cataloged as "high" in the machine learning /
Artificial Intelligence
database engine (Al engine). For the next session, a new set of combination
settings is set by
the Artificial Intelligence engine, thus, the workspace fitness devices, the
smartphone, and all
other connected devices use that new set of combination settings to try in the
next session the
user initiates. The results are again compared and new combinations are
computed until the
settings of the workspace fitness device and the sensorial input in a specific
session provide
results closer to the Optimal Settings.
Embodiments of the invention may be implemented on a computing system. Any
combination
of mobile, desktop, server, router, switch, embedded device, or other types of
hardware may be
used. For example, as shown in FIG. 21A, the computing system (2100) may
include one or
more computer processors (2101), non-persistent storage (2102) (for example,
volatile memory,
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such as random access memory (RAM), cache memory), persistent storage (2103)
(for
example, a hard disk, an optical drive such as a compact disk (CD) drive or
digital versatile disk
(DVD) drive, a flash memory, etc.), a communication interface (2104) (for
example, Bluetooth
interface, infrared interface, network interface, optical interface, etc.),
and numerous other
elements and functionalities.
The computer processor(s) (2101) may be an integrated circuit for processing
instructions. For
example, the computer processor(s) may be one or more cores or micro-cores of
a processor.
The computing system (2100) may also include one or more input devices (2110),
such as a
touchscreen, keyboard, mouse, microphone, touchpad, electronic pen, or any
other type of input
device.
The communication interface (2104) may include an integrated circuit for
connecting the
computing system (2100) to a network (not shown) (for example, a local area
network (LAN), a
wide area network (WAN) such as the Internet, mobile network, or any other
type of network)
and/or to another device, such as another computing device.
Further, the computing system (2100) may include one or more output devices
(2106), such as
a screen (for example, an LCD display, a plasma display, touch screen, cathode
ray tube (CRT)
monitor, projector, or other display device), a printer, external storage, or
any other output
device. One or more of the output devices may be the same or different from
the input
device(s). The input and output device(s) may be locally or remotely connected
to the computer
processor(s) (2101), non-persistent storage (2102) , and persistent storage
(2103). Many
different types of computing systems exist, and the aforementioned input and
output device(s)
may take other forms.
Software instructions in the form of computer readable program code to perform
embodiments
of the invention may be stored, in whole or in part, temporarily or
permanently, on a
non-transitory computer readable medium such as a CD, DVD, storage device, a
diskette, a
tape, flash memory, physical memory, or any other computer readable storage
medium.
Specifically, the software instructions may correspond to computer readable
program code that,
when executed by a processor(s), is configured to perform one or more
embodiments of the
invention.
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The computing system (2100) in FIG. 21A may be connected to or be a part of a
network. For
example, as shown in FIG. 21B, the network (2110) may include multiple nodes
(for example,
node X (2111), node Y (2112)). Each node may correspond to a computing system,
such as
the computing system shown in FIG. 21A, or a group of nodes combined may
correspond to the
computing system shown in FIG. 21A. By way of an example, embodiments of the
invention
may be implemented on a node of a distributed system that is connected to
other nodes. By
way of another example, embodiments of the invention may be implemented on a
distributed
computing system having multiple nodes, where each portion of the invention
may be located
on a different node within the distributed computing system. Further, one or
more elements of
the aforementioned computing system (2100) may be located at a remote location
and
connected to the other elements over a network.
Figures 22 to 24 describe an embodiment of our invention, for example, a user
rides an Uber;
the Al engine has access to the users apps, makes a determination that the
user is requesting a
Uber ride at 4:30 pm (first determination of an action), from point A to Point
B. Then, it makes a
second determination, in this case a goal, which can be a calendar entry
showing a meeting at
5:00pm. Then makes a 3rd determination, this time based on statistical data
that the Uber ride
will take 30 minutes from point A to Point B. One familiar with the art will
appreciate that this
statistical data may come from the Uber app or from other apps and not exactly
from data in the
Al engines database. Based in those determinations, the Al engine makes a
suggestion of the
type of music the user wants or needs to hear to remain calm while at traffic
in the Uber ride.
data from an application running in the first device, in the case of this
example, the Uber app,
has data of the starting point and the finish point, the finish point
geolocalization data can be a
reference for the second determination to determine that the user is going to
the University for
example.
Based on the same example, multiple forward determinations can be made that
will influence
the Al engine recommendation for music to play for the user. For example a
fourth
determination can be that the Calendar entry for the 5:00 pm meeting is a life
coaching session
that the user will host, that means that the user needs to get "pumped-up" in
order to influence
his pupils. In this case, the Al engine recommends, first, music to remain
calm for the first 20
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minutes of the ride, and for the last 10 minutes of the ride a music selection
more appropriate
for the life coaching motivational session.
data based on user's patterns, for example, the user is a professor at a
University and every
Wednesday at 5:00pm has a life coaching session that lasts for 2 hours.
One familiar with the art will appreciate that the home automation system is a
device such as
Amazon Eco, Google Home, or similar connected sound system such as a portable
or fix sound
system that connects to a smart gadget, or a sound system that is connected to
the internet or
connects to the internet via a local connection to another device such as a
smartphone. A
connected sound system may also be one that is installed in a vehicle such as
a media center
or one from a PA system such as the ones used in schools or office spaces. One
familiar with
the art will appreciate that a smart gadget connects via wifi, aux audio
cable, bluetooth, radio
frequency or via the internet to a connected sound system, thus, reproducing
the sound in the
smart gadget itself or thru the speakers at the connected sound system. In a
different
embodiment of this invention, the playlist itself is downloaded by the
connected sound system
and played thru the speakers in the connected sound system.
Smart gadget is a device that has the capability to play audio files and
connect to the internet
Playlist is set of music track to play based on music curation. The playlist
has a start and an end
time, in some cases, the end time of the playlist is based in external factors
such as other
determinations, override by a different event or by the user manually
canceling the playlist
playback.
Figure 22 is a flowchart that shows how the invention works
Step 2201 shows how the user's smartphone makes a first determination of an
action. Actions
can also be something like riding a bike, where, there is a start and finish
point. The start point
can be data gathered from the geo location in the user's smartphone. Calendar
entries can be a
trigger for an action or the identification of an action, for example the
finish point can also be
determined by a calendar entry. Actions can also be something like requesting
a ride share, a
taxi or getting into a public transport. For example, a user starts riding a
bike at 4:30, (first
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determination), this determination can be made by determining the geo-location
of the user's
smartphone, the path used and the speed, in this case, the first determination
is that the user is
using a bike to ride to his destination. This first determination can also be
validated by patterns
on the Al engine database, something like: the user rides a bike to the
university every thursday
at 4:30pm.
Step 2202 shows how a second determination is made. Continuing with the same
example as
step 1, a second determination is made, this time a calendar entry that shows
that the user
teaches, for example, a life coaching session at the University at 5:00pm. The
second
determination entry could also be data gathered from other software
applications such as social
media entries and any other software that is connected to the software of our
invention that can
help to determine the user's destination. Other ways to determine the
destinations are for
example, if the user has requested a ride share, the end point of that ride
share. If the user is in
public transport, and based on the user's patterns of conduct, the user rides
that same public
transport everyday to go to the University to teach a class, then, that
becomes the second
determination.
Step 2203 shows how the software estimates the user's actual experience
required. For
example, based on the information from the first and second determination, the
software
calculates that the user needs to produce enough pedal RPMs to trust the bike
at least at 10
km/h in order to make it in time to the University before 5:00pm. The software
estimates the
user's actual optimal experience requirement to be: "motivation to pedal at a
regular pace".
Other optimal actual experiences are saved in the user preferences or
determined by the Al
engine itself. These experiences include for example, be calm in traffic, be
motivated to work,
relax while in public transport, and others.
Step 2204, In correlation to this information, the Al Engine database curates
a playlist based on
this actual experience, the playlist creates it using audio files or music
that have metadata info
such as tempo and rhythm to name a few that will motivate the user to pedal at
that pace.
Step 2205, the device plays the curated playlist
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Step 2206, end. Step 2407 in figure 24 shows a different embodiment of our
invention,
continuing with this example, in case the user pedals slower even after the
input of the
motivational music, then, the software detects an input, based on the
geolocation or speed the
user is moving. The input triggers the software to change the curated
playlist, in order to do so,
the process needs to go back to Step 1 and re-do the process again trying to
offer the user an
optimal actual experience to be motivated to pedal faster to make it in time
for the 5:00pm class.
Figure 23 shows a flowchart on how one curated playlist is combined with a
second one based
on a third determination
Step 2301 - curated playlist playing. Continuing with the example from Figure
X+1, the curated
playlist plays on the device.
Step 2302 - a third determination is made based on statistical data. This data
is gathered from
different sources such as traffic information, calendar information, previous
collected date, from
which, the software determines if the goal will be met as planned or not. For
example a goal can
be made it on time for a calendar entry. For example, at 5:00pm the person,
who is using a ride
share service such as Uber, is experiencing high traffic, so, determinations
one and two provide
data on the point of start and ends and suggest to play a calm or relaxing
music. But, the third
determination determines that the user needs to be motivated for a life coach
session, for which
he needs to hear music with high cadence rhythm and emotive sounds. So, for
example, for the
first playlist it is recommended to play calm music, maybe for the first 20
minutes of the 30
minute ride, and then, the second playlist, with more motivational type of
music for the last 10
minutes, that way, the user will arrive "motivated" to teach his life coach
session.
Continuing with Step 2302, the software makes the determination, based on
statistical data, that
the user needs a different type of influence from before.
Step 2303 - the software curates a new playlist with music ad hoc to the
actual necessities of
the user
Step 2304 - the new playlist is reproduced at the device. Then, end (Step
2305).
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In a different embodiment of our invention, there could be fourth and further
determinations that
follow this path.
Figure 24 shows a flowchart that reflects when a change is detected. The
change can be on any
of the factors that triggered the first and second determination to create the
first playlist from
Figure 22
Step 2401 shows how the user's smartphone makes a first determination of an
action. Actions
can also be something like riding a bike, where, there is a start and finish
point. The start point
can be data gathered from the geo location in the user's smartphone. Calendar
entries can be a
trigger for an action or the identification of an action, for example the
finish point can also be
determined by a calendar entry. Actions can also be something like requesting
a ride share, a
taxi or getting into a public transport. For example, a user starts riding a
bike at 4:30, (first
determination), this determination can be made by determining the geo-location
of the user's
smartphone, the path used and the speed, in this case, the first determination
is that the user is
using a bike to ride to his destination. This first determination can also be
validated by patterns
on the Al engine database, something like: the user rides a bike to the
university every thursday
at 4:30pm.
Step 2402 shows how a second determination is made. Continuing with the same
example as
step 1, a second determination is made, this time a calendar entry that shows
that the user
teaches, for example, a life coaching session at the University at 5:00pm. The
second
determination entry could also be data gathered from other software
applications such as social
media entries and any other software that is connected to the software of our
invention that can
help to determine the user's destination. Other ways to determine the
destinations are for
example, if the user has requested a ride share, the end point of that ride
share. If the user is in
public transport, and based on the user's patterns of conduct, the user rides
that same public
transport everyday to go to the University to teach a class, then, that
becomes the second
determination.
Step 2403 shows how the software estimates the user's actual experience
required. For
example,
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based on the information from the first and second determination, the software
calculates that
the user needs to produce enough pedal RPMs to trust the bike at least at 10
km/h in order to
make it in time to the University before 5:00pm. The software estimates the
user's actual optimal
experience requirement to be: "motivation to pedal at a regular pace". Other
optimal actual
experiences are saved in the user preferences or determined by the Al engine
itself. These
experiences include for example, be calm in traffic, be motivated to work,
relax while in public
transport, and others.
Step 2404, In correlation to this information, the Al Engine database curates
a playlist based on
this actual experience, the playlist creates it using audio files or music
that have metadata info
such as tempo and rhythm to name a few that will motivate the user to pedal at
that pace.
Step 2405, the new curated playlist is played at the device.
Step 2406, determines if there is a change detected, the change may come from
the sensors at
the playback device, or at the smartphone of the user. The change can also be
in the form of a
user's input, or a calendar input or similar. If a change is detected, then
Step 407, if there is no
change detected, then end (step 2408).
Step 2407 shows that in case the user pedals slower even after the input of
the motivational
music, then, the software detects an input, based on the geolocation or speed
the user is
moving. The input triggers the software to change the curated playlist, in
order to do so, the
process needs to go back to Step 2401 and re-do the process again trying to
offer the user an
optimal actual experience to be motivated to pedal faster to make it in time
for the 5:00pm class.
One familiar with the art will appreciate that the music curation can be done
locally in the device
such as a smartphone or a smart gadget, or remotely in a remote server.
While the invention has been described with respect to a limited number of
embodiments, those
skilled in the art, having benefit of this disclosure, will appreciate that
other embodiments can be
devised which do not depart from the scope of the invention as disclosed
herein. Accordingly,
the scope of the invention should be limited only by the attached claims.
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