Patent Publication Number: US-2021186360-A1

Title: Smart scale systems with body imaging and associated devices and methods

Description:
CROSS-REFERENCE TO RELATED APPLICATION(S) 
     The application claims priority to and the benefit of U.S. Provisional Patent Application No. 62/952,972, filed Dec. 23, 2019, which is incorporated herein by reference in its entirety. 
    
    
     TECHNICAL FIELD 
     The present disclosure relates generally to smart scale systems, and more particularly to smart scale systems with techniques for capturing and presenting both body composition measurements and images. 
     BACKGROUND 
     Scales are configured to determine body composition information relating to a user. For example, responsive to a living body stepping on a scale, the scale can determine a weight of the living body. In many cases, scales can include sensors that measure various body composition metrics using various techniques. On such technique can include bioelectrical impedance analysis (BIA). Scales utilizing BIA techniques can measure various detailed body composition measurements using electrical current traveling through the living body. 
     While scales can capture body composition metrics of the user, simply capturing these metrics may provide incomplete or insufficient information of a body transformation journey. Example body transformation journeys may include a time period during which the user loses weight (e.g., a weight-loss journey) or a time period during which the user develops their musculature (e.g., a body building journey, a rehabilitation journey). During a body transformation journey, a user may have a substantial change to the body composition over a period of time. This change to the body composition of the user may be inadequately depicted simply by captured body composition metrics. 
     One mechanism for addressing this issue is to implement a scale that can communicate with a user device to record body composition information measured by the scale. For example, an application on a mobile phone of a user can store weight and body mass information relating to the user. However, simply tracking weight information of a user often may not adequately capture the substantial changes to the body composition of the user during a body transformation journey. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The present embodiments are illustrated by way of example and are not intended to be limited by the figures of the accompanying drawings. 
         FIG. 1  is a representative environment within which some embodiments may be implemented. 
         FIG. 2  is a block diagram of a computing device that may be used to implement the techniques introduced here. 
         FIG. 3  is an example block diagram of a signaling process illustrating biometric information and image information acquisition in an environment as disclosed herein. 
         FIG. 4  is a block diagram of a scale configured in accordance with embodiments of the present technology. 
         FIG. 5  is a flow diagram of a method performed by a network-accessible scale to acquire biometric information in accordance with embodiments of the present technology. 
         FIG. 6  is an illustration of an environment that includes multiple imaging devices in accordance with embodiments of the present technology. 
         FIG. 7  is a flow diagram of a method to process biometric information and image information in accordance with embodiments of the present technology. 
         FIGS. 8A-8B  are example user interfaces illustrating an interactive dashboard that includes both biometric information and image information. 
         FIGS. 9A-9B  are example user interfaces illustrating a video that includes a time-lapse of both biometric information and image information. 
         FIGS. 10A-10C  are example block diagrams illustrating a process to activate a device in an environment as described herein. 
         FIG. 11  is a system diagram illustrating an example of a computing environment in which the present embodiments may be implemented. 
     
    
    
     Like reference numerals refer to corresponding parts throughout the figures and specification. 
     DETAILED DESCRIPTION 
     Smart scale systems with body imaging and associated devices and methods are disclosed herein. In some embodiments, for example, a smart scale system can include a scale configured to communicate biometric information of a user to a user device, an imaging device that captures an image of the user&#39;s body as the scale measures the biometric data, and an application that displays a dashboard including the captured biometric data and images of the user across a timeline having multiple time points. Specific details of several embodiments of the technology are described below with reference to  FIGS. 1-11 . Although many of the embodiments are described below with respect to devices, systems, and methods for capturing weight loss and body building journeys, other applications and other embodiments in addition to those described herein are within the scope of the technology. For example, the present technology may be used to track body development over periods of time for other reasons, such as rehabilitation and other medical needs. Additionally, several other embodiments of the technology can have different configurations, components, or procedures than those described herein, and that features of the embodiments shown can be combined with one another. A person of ordinary skill in the art, therefore, will accordingly understand that the technology can have other embodiments with additional elements, or the technology can have other embodiments without several of the features shown and described below with reference to  FIGS. 1-11 . 
     Many scales can be configured to send body composition metrics to a user device (e.g., mobile phone), and the user device can record this data over time. However, simply tracking raw data over a period of time may be an insufficient illustration of a user&#39;s body composition over time. For example, to supplement tracked body composition information to illustrate one&#39;s weight loss journey, a user may attempt to capture and identify images of their body captured during the weight loss journey. This may include accessing various websites or computing devices to search for and identify images during the weight loss journey. When images are identified, the user may compile the images to generate a time-lapse series of images representing the weight loss journey. Such a process may be an insufficient use of computational resources, as various devices may be repeatedly accessed to retrieve images of the user over a network. Further, sending various requests for images among devices in a network and transmitting images across the network may result in an inefficient user of network resources. 
     Introduced here, accordingly, are systems, devices, and methods for acquiring biometric information of a user along with media information (e.g., images, videos) of the user over a period of time that can be utilized in generating a video or dashboard illustrating changes to a body composition of a user over a period of time. The biometric information and media information associated with a user may be associated with a timestamp indicative of a time that the information was captured. A series of captured biometric information and media information for a user may be chronologically ordered according to the timestamps, which may allow for generation a video or interactive dashboard showing a time-lapsed display of the biometric information and media information of the user during a during a period of time, such as during a specific period of time (e.g., one or more years, one or more months, one or more days), over the course of a weight loss regime, during a muscle building program, during physical therapy, and/or other body transformation journey. 
     The present embodiments may acquire both biometric information of a user and media information and generate a multi-media presentation of this information with an increased efficiency in utilization of network and computer resources. For instance, rather than having to retrieve images and body composition metrics from a variety of devices over a network, a device (e.g., a network-accessible server system, user device) can acquire and store a series of biometric information and images of a user. A multimedia presentation of chronologically ordered information can be generated with greater efficiency by accessing received information from the device and chronologically ordering the information. 
     A network-accessible scale (also referred to as a “scale”) may capture a set of biometric information (e.g., weight information, body mass information, BIA-based measurements) associated with the user based on receipt of a triggering event (e.g., receipt of a request message, detecting a user has stepped on the scale). The scale can send the acquired biometric information to a user device (e.g., a mobile phone associated with the user). 
     The user device can request an imaging device (or simply “camera”) to capture image(s) of the user and send the captured image(s) to the user device. The user device can associate the received biometric information and image(s) with a timestamp indicative of a time/date that the information was captured. In some embodiments, the imaging device can be communicatively coupled to the user device and/or the scale, and can capture image(s) automatically when the scale takes the biometric measurements (either simultaneously or in succession). 
     A network-accessible server system can receive the biometric information, image(s), and timestamp information from the user device and process the information. The network-accessible server system may maintain multiple sets of biometric information and images of the user captured at various times. Upon a request, the network-accessible server system can generate an interactive dashboard and/or a video that includes the biometric information and images of the user ordered chronologically based on the timestamps. 
     The generated interactive dashboard and/or video may be illustrative of a user body transformation journey that illustrates a time-lapse depiction of body composition metrics and images of the user. The interactive dashboard and/or video may provide a detailed illustration of changes to the body composition of the user during the course of a body transformation journey. This provides information about not only the biometrics, but also the change of shape and physical appearance of the body over time, such as which portions of the body undergo changes (e.g., decreases in size, increases in size, muscle definition, muscle deterioration) and when. The generated interactive dashboard or video can be viewed, modified, and/or uploaded to various applications/websites that can be shared/accessed by others to share a body transformation journey of the user. As an example, during a weight loss journey, an interactive dashboard may allow for one to view a series of images and metrics illustrating the loss of weight by the user and changes to body composition metrics of the user during the weight loss journey. 
     In various embodiments, the systems and methods described herein can analyze the image data (e.g., images, videos) to provide additional information to the user. For example, the image data can be analyzed using software programs, including machine learning, that determine one or more parameters related to the image of the user, such as measurements of certain body parts (e.g., waist, hips, thighs, calves, arms), muscle definition, body shape, and/or changes in these parameters over time. 
     In the following description, numerous specific details are set forth such as examples of specific components, circuits, and processes to provide a thorough understanding of the present disclosure. Also, in the following description and for purposes of explanation, specific nomenclature is set forth to provide a thorough understanding of the present embodiments. However, it will be apparent to one skilled in the art that these specific details may not be required to practice the present embodiments. In other instances, well-known circuits and devices are shown in block diagram form to avoid obscuring the present disclosure. 
     The term “coupled” as used herein means connected directly to or connected through one or more intervening components or circuits. Any of the signals provided over various buses described herein may be time-multiplexed with other signals and provided over one or more common buses. Additionally, the interconnection between circuit elements or software blocks may be shown as buses or as single signal lines. Each of the buses may alternatively be a single signal line, and each of the single signal lines may alternatively be buses, and a single line or bus might represent any one or more of a myriad of physical or logical mechanisms for communication (e.g., a network) between components. The present embodiments are not to be construed as limited to specific examples described herein but rather to include within their scope all embodiments defined by the appended claims. 
     System Overview 
       FIG. 1  is a representative environment  100  within which some embodiments may be implemented. An example environment  100  may include any of a network-accessible scale  102 , a user device  104 , an imaging device  106 , a wireless network node  108 , and a network-accessible server system  110 . 
     The network-accessible scale  102  (or simply “scale  102 ”) may include a device that can capture biometric information of a living body. Biometric information can include any measurable characteristic of a body composition of a living body. Examples of biometric information that can be measured may include a weight, body mass index (BMI), or Bioelectrical Impedance Analysis (BIA) based information (e.g., body fat, muscle, body water, lean body mass, bone mass, protein, visceral fat, basal metabolic rate (BMR), metabolic age) relating to a living body. 
     The network-accessible scale  102  may include a plurality of sensors that can be used to determine various biometric information of a user. For example, a sensor can detect the weight of a user stepping on the scale  102 . In some embodiments, the network-accessible scale  102  may determine a change in pressure indicative of a user stepping on the scale  102 . 
     The environment  100  may include a user device  104 . The user device  104  can include an electronic device (e.g., mobile phone, computer) that can interact with various devices in the environment via one or more communications interfaces. For example, the user device  104  can communicate with the scale  102  via a wireless communication interface (Bluetooth®, Bluetooth® Low Energy (BLE), Near-Field Communication (NFC), Wi-Fi, etc.). 
     In some embodiments, the user device  104  may be communicatively coupled to a wearable electronic device (or a “smart watch”). The wearable electronic device can provide an input to the user device  104  (e.g., a voice command, selection of a button) that indicates a request to perform a task (e.g., capture weight information by the scale  102  and capture image by imaging device  106 ). 
     As an example, the wearable electronic device can send a digitized audio stream representing a voice command providing a request to capture weight information by scale  102  and capture an image by imaging device  106 . In this example, the user device  104  can identify the requested task and the devices to perform the requested task by inspecting the digitized audio stream. Accordingly, user device  104  can send a request message to scale  102  and imaging device  106  to capture weight information/image of the user. 
     The user device  104  may include a mobile application. The mobile application can interact with various devices (e.g., scale  102 , camera  106 ) in the environment  100  as described with greater detail below. The user device/motion application can be associated with a user profile associated with a user. As noted below, the user profile may be utilized in determining whether the scale  102  and/or imaging device  106  will send information to the user device  104 . 
     The environment  100  may include an imaging device  106 . The imaging device  106  (or simply “camera”) may include an electronic device configured to capture image(s) of an environment or a user. As noted below, the camera  106  can capture images of the user based on receipt of an input, such as a message from the user device requesting the camera  106  to capture the image. 
     The environment  100  may include a wireless network node  108 . The wireless network node  108  can include a wireless router configured to communicate with devices in a network using a suitable wireless protocol (e.g., Wi-Fi). 
     The wireless network node  108  can be a network device (e.g., a router, gateway), which in computer networking sense, is a node that is assumed to know how to forward packets on to other networks. In a home or small office environment, the wireless network node  108 , such as a digital subscriber line (DSL) router or cable router that connects the local area network (LAN) to the Internet acts as the default gateway for all network devices. For example, the wireless network node  108  and a network (e.g., the internet) may be connected via a twisted pair cabling network, a coax cable network, a telephone network, or any suitable type of connection network. In some embodiments, wireless network node  108  may be connected to a network wirelessly (e.g., which may include employing a data traffic network based on wireless telephony services such as 3G, 3.5G, 4G LTE and the like). 
     Any devices in the environment  100  can communicate either directly or indirectly, via one or more wireless network communication technologies, such as WLAN (e.g., Wi-Fi), Bluetooth, etc. The IEEE 802.11 standards are a set of WLAN technology specifications commonly seen for implementing wireless local area network (WLAN) computer communication. Examples of different wireless communication protocols in the IEEE 802.11 family of standards can include IEEE 802.11a, IEEE 802.11b, IEEE 802.11n, IEEE 802.11ac, and so forth. For example, a client device (e.g.,  102 ,  104 ,  106 ) establishes connection with the wireless network node  108 , the wireless network node  108  can communicate the traffic to the outside world (e.g., wide area network (WAN) and/or “the Internet”). 
     Although not shown for simplicity, the wireless network node  108  may include one or more processors, which may be general-purpose processors or may be application-specific integrated circuitry that provides arithmetic and control functions to implement the techniques disclosed herein on the wireless network node  108 . The processor(s) may include a cache memory (not shown for simplicity) as well as other memories (e.g., a main memory, and/or non-volatile memory such as a hard-disk drive or solid-state drive. In some examples, cache memory is implemented using SRAM, main memory is implemented using DRAM, and non-volatile memory is implemented using Flash memory or one or more magnetic disk drives. According to some embodiments, the memories may include one or more memory chips or modules, and the processor(s) on the wireless network node  108  may execute a plurality of instructions or program codes that are stored in its memory. 
     The environment  100  may include a network-accessible server system  110 . The network-accessible server system  110  can include one or more interconnected servers configured to access, store, and process information. In an embodiment, the network-accessible server system  110  can interact with the wireless network node  108  and/or the user device  104 . 
     The client devices (e.g.,  102 ,  104 ,  106 ) can connect to and communicate with the wireless network node  108  wirelessly including, for example, using the IEEE 802.11 family of standards (e.g., Wireless LAN), and can include any suitable intervening wireless network devices including, for example, base stations, routers, gateways, hubs, or the like. Depending on the embodiments, the network technology connecting between the client devices and the wireless network node  108  can include other suitable wireless standards such as the well-known Bluetooth communication protocols or near field communication (NFC) protocols. In some embodiments, the network technology between the devices and the wireless network node  108  can include a customized version of WLAN, Bluetooth, or customized versions of other suitable wireless technologies. Client devices can be any suitable computing or mobile devices including, for example, smartphones, tablet computers, laptops, personal digital assistants (PDAs), or the like. Client devices typically include a display and may include suitable input devices (not shown for simplicity) such as a keyboard, a mouse, or a touchpad. In some embodiments, the display may be a touch-sensitive screen that includes input functionalities. Additional examples of the devices can include network-connected cameras (or “IP cameras”), home sensors, and other home appliances (e.g., a “smart refrigerator” that can connect to the Internet). 
     It is noted that one of ordinary skill in the art will understand that the components of  FIG. 1  are just one implementation of the network environment within which present embodiments may be implemented, and the various alternative embodiments are within the scope of the present embodiments. For example, the environment  100  may further include multiple imaging devices  106 , intervening devices (e.g., switches, routers, hubs), etc. 
     Environment  100  as shown in  FIG. 1  is representative for illustrative purposes only. The techniques disclosed here can be applicable to alternative implementations that may have different configurations. One or more elements or devices introduced in  FIG. 1  may be eliminated, combined, or separated. For example, any of the network-accessible scale  102 , user device  104 , and network-accessible server system  110  can perform any of the tasks relating to the embodiments as described herein. 
     In one example, the network-accessible scale  102  can perform any of the steps as described with reference to  FIG. 7 . 
     With the environment introduced above in mind, various techniques for capturing both biometric information and imaging information are described in more detail below, with continued reference to the elements in  FIG. 1 . 
     Device Architecture 
       FIG. 2  is a high-level block diagram showing an example of a computing device  200  that can be used to implement one or more devices (e.g., scale  102 , user device  104 , camera  106 , wireless network node  108 , network-accessible server system  110 ) introduced here. 
     In the illustrated embodiment, the computing system  200  includes one or more processors  210 , memory  211 , a communication device  212 , and one or more input/output (I/O) devices  213 , all coupled to each other through an interconnect  214 . The interconnect  214  may be or may include one or more conductive traces, buses, point-to-point connections, controllers, adapters and/or other conventional connection devices. The processor(s)  210  may be or may include, for example, one or more general-purpose programmable microprocessors, microcontrollers, application specific integrated circuits (ASICs), programmable gate arrays, or the like, or a combination of such devices. The processor(s)  210  control the overall operation of the computing device  200 . Memory  211  may be or may include one or more physical storage devices, which may be in the form of random access memory (RAM), read-only memory (ROM) (which may be erasable and programmable), flash memory, miniature hard disk drive, or other suitable type of storage device, or a combination of such devices. Memory  211  may store data and instructions that configure the processor(s)  210  to execute operations in accordance with the techniques described above. The communication device  212  may be or may include, for example, an Ethernet adapter, cable modem, Wi-Fi adapter, cellular transceiver, Bluetooth transceiver, or the like. Depending on the specific nature and purpose of the processing device  200 , the I/O devices  213  can include devices such as a display (which may be a touch screen display), audio speaker, keyboard, mouse or other pointing device, microphone, camera, etc. 
     Biometric Information and Image Information Acquisition 
       FIG. 3  is an example block diagram of a signaling process  300  illustrating biometric information and image information acquisition in an environment as disclosed herein. As shown in  FIG. 3 , the signaling process  300  can include information acquisition and transmission between a network-accessible scale, a user device  304 , an imaging device  306 , and a network-accessible server system  308 . 
     Any of the network-accessible scale  302 , user device  304 , and/or imaging device  306  may detect a triggering event (block  310 ). A triggering event may include an occurrence that initiates the capture of biometric information and/or image information of a user. Example triggering events include the scale  302  determining that a user has stepped on the scale  302 , the user device  304  coming within a wireless communication range of the scale  302 , the user device  304  sending a message to the scale  302  and/or imaging device  306 , the user device  304  receiving an indication on a mobile application from a user, the imaging device  306  detecting (e.g., using motion sensing, facial recognition) that a user is near the scale  302  or has stepped on the scale  302 , etc. 
     The scale  302  can capture biometric information (block  312 ). This may include obtaining sensor data received from a plurality of sensors and processing the sensor data to derive biometric information, which may be referred to as “body composition metrics.” The scale  302  can determine various types of body composition metrics, such as weight (in pounds), body fat (as a percentage), lean body mass (in kilograms), BIA-based measurements, etc. 
     The scale  302  can send the captured biometric information to the user device  304  (block  314 ). The biometric information can be sent via a communication interface. The communication interface may include a short-range wireless communication interface, such as Bluetooth®, Bluetooth® low energy (BLE), NFC, etc. 
     The user device  304  can send a request to capture image information to the imaging device  306  (block  316 ). This request can instruct an imaging device  306  to capture image information of a user. The request may be sent responsive to receiving the biometric information, as described in block  314 . 
     In some embodiments, request can be transmitted via a wireless communication interface different than that of the communication interface. For example, the communication interface between the user device  304  and scale  302  can be a Bluetooth® interface and the wireless communication interface between the user device  304  and imaging device  306  can include a Wi-Fi interface. The communication interface between the user device  304  and imaging device  306  can include a wireless communication range (e.g., the maximum distance that communicating devices can successfully transmit data) greater than a wireless communication range between the user device  304  and scale  302 . 
     The imaging device  306  can be configured to capture image information (block  318 ). Imaging device  306  (e.g., cameras) can capture image(s) of the user responsive to either detecting a triggering event (block  310 ) or receiving a request to capture image information (block  318 ). As discussed in greater detail below, multiple cameras  306  can capture images of the user from various perspectives, which may be utilized in generating a 3-dimensional image of the user. 
     The imaging device  306  may send captured image information to the user device  304  (block  320 ). In some embodiments, the imaging device  306  may send the image to the network-accessible server system  308  via a wireless network node (e.g., wireless network node  108 ). 
     The user device  304  may associate the received biometric information and the received image information with a timestamp (block  322 ). The timestamp can include a digital record of a time of an occurrence of an event. Example events that can identified in the timestamp can include any of the time that the triggering event was detected, the time that the biometric information and/or the image information was received at the user device, the time that the biometric information and/or the image information was sent to the network-accessible server system, etc. As detailed below, timestamps may be utilized in ordering a series of biometric information and images acquired at various times. 
     The user device  304  may send the biometric information and the image information to the network-accessible server system  308  (block  324 ). In response to receiving the biometric information and the image information, the network-accessible server system  308  may perform a further action (e.g., store the information, process the information), as described in greater detail below. 
       FIG. 4  is an example block diagram of a scale  400 . As noted above, the scale  400  can include a network-accessible device configured to determine various body composition metrics relating to a user. 
     The scale  400  may include a plurality of sensors  402 . The plurality of sensors  402  located within the scale  400  may be configured to capture information that can be used to determine various body composition measurements of a user. 
     An example sensor  402  may include a weight sensor that can measure the weight of a user stepping on the scale  400 . Another example sensor  402  can include a bioelectrical impedance analysis (BIA) sensor that utilizes electric current (e.g., using electrodes) flowing through the body of the user to calculate impedance of the body. BIA sensors can detect various compositions of body water, body mass, body fat, etc. of the user. Examples of biometric information that can be measured may include a weight, body mass index (BMI), or Bioelectrical Impedance Analysis (BIA) based information (e.g., body fat, muscle, body water, lean body mass, bone mass, protein, visceral fat, basal metabolic rate (BMR), metabolic age) relating to a living body. 
     In some embodiments, the sensors  402  can include one or more imaging devices (e.g., cameras) integrated in the scale  400  to capture images of the user. The imaging devices integrated in the scale  400  may perform any of the functionality of the imaging devices (e.g., imaging device  106 ) as described herein. 
     The scale  400  may include an output  404  that can display various information to the user. For example, the output  404  can display a date, time, and the weight of the user. In some embodiments, the output  404  can provide indications of various events, such as detection of a user device or that the scale determined a user profile based on generated body composition measurements measured by the scale  400 . The output  404  can output any suitable information to improve user experience in interacting with the scale  400 . 
       FIG. 5  is an example flow diagram of a method  500  performed by a network-accessible scale to acquire biometric information. The method may include the scale detecting an input (block  502 ). The input may be indicative of a triggering event, such as the scale detecting that a living body has stepped onto the network-accessible scale, the scale receiving an indication from a user device to capture biometric information, or the scale receiving an indication from a mobile application on a user device indicating that the device is within a communication range of the scale, for example. 
     The method may include capturing biometric information of a user (block  504 ). The scale may capture biometric information of a user and determine body composition metrics using sensors included in the scale as described herein. 
     The method may include associating the biometric information with a timestamp (block  506 ). The timestamp may be indicative of a time that the biometric information was captured or a time that the input was detected, for example. 
     The method may include determining whether the captured biometric information corresponds to a user profile (decision block  508 ). This may include comparing the biometric information with information relating to known user profiles stored in the network-accessible scale to determine whether information relating to any profile is within a threshold similarity to the set of biometric information. The threshold similarity may be a predetermined value or percentage that represents the maximum difference that the biometric information can be from information relating to user profiles to correspond to a user profile. 
     As an example, a first user profile may have an average weight of 225 pounds and 18% body fat. Additionally, a second user profile may have an average weight of 125 pounds and 12% body fat. If the scale determines that the weight of the user on the scale is 128 pounds with a 12.5% body fat percentage, the scale may determine that the first user profile is outside the threshold similarity (e.g., within 3% of the captured biometric information), while the second user profile is within the threshold similarity to the captured biometric information. Accordingly, in this example, the captured biometric information may be associated with the second user profile. 
     In some embodiments, the scale can include one or more user profiles associated with users. In these embodiments, the scale can inspect captured body composition information to derive whether a person stepping on the scale corresponds to any of the stored user profiles. The scale can determine that captured body composition information is associated with a new user based on determining that no user profile is within a threshold similarity of the captured body composition information. In other embodiments, a user device (e.g., mobile phone) or a network-accessible server system may include the user profiles and determine whether captured body composition information corresponds to any user profile. 
     If it is determined that captured biometric information does not correspond to any user profile, the method may include storing the biometric information as associated with a new user profile (block  510 ). The stored biometric information associated with the new user profile may be sent to any of the user device or a network-accessible server system for further processing. 
     If it is determined that captured biometric information corresponds to a user profile, the method may include determining whether the user device associated with the corresponding user profile within a communication range (decision block  512 ). This may include receiving an indication from the user device that the user device is within a wireless communication range of the network-accessible scale. 
     If the user device associated with the corresponding user profile not within a communication range of the scale, the method may include storing the biometric information as associated with the corresponding user profile (block  514 ). The scale may repeatedly attempt to determine whether the whether the user device associated with the corresponding user profile within a communication range. 
     If it is determined that user device associated with the corresponding user profile is within a communication range of the scale, the method may include sending the biometric information to the user device associated with the corresponding user profile (block  516 ). 
       FIG. 6  is an example illustration of an environment  600  that includes multiple imaging devices  606   a - c . As shown in  FIG. 6 , the environment can include a number of imaging devices (e.g., three cameras  606   a - c ) that can capture images from various perspectives. 
     Capturing multiple images of a user from multiple perspectives can be used in generating a multi-dimensional image of the user, such as a 3-dimensional image of the user. The images may be stitched together to capture a perspective view or 3-dimensional image of the user that can show multiple angles or perspectives of the user. The cameras  606   a - c  may be interconnected devices (e.g., internet of things (IoT) devices) in a network that can forward the captured images to any of the user device  604  or a wireless network node  608 . 
     Biometric Information and Image Information Processing 
     A computing device (e.g., network-accessible server system) may be configured to perform various processing tasks relating to acquired biometric information and image information.  FIG. 7  is an example flow diagram of a method  700  to process biometric information and image information. 
     The method may include obtaining biometric information and image information (block  702 ). The biometric information and/or image information may be obtained responsive to an input indicative of a triggering event. The triggering event may include any of a network-accessible scale detecting a living body stepping on the network-accessible scale and a mobile device associated with a user being located within a wireless communication range of a network-accessible scale. 
     In some embodiments, the biometric information is received from a mobile phone via a first communication interface, the mobile phone may receive the biometric information from the network-accessible scale via a second communication interface, the first communication interface including a greater wireless communication range than the second communication interface. The imaging information may be received from a network node via a third communication interface, the network node configured to receive the imaging information from the imaging device via a fourth communication interface. 
     The method may include storing the received biometric information and image information (block  704 ). The information may be stored in a first portion of memory associated with a user. The information may be store with a timestamp indicative of a time that the biometric information and the imaging information was captured. 
     In some embodiments, the received biometric information and/or the received imaging information may be compared with information relating to known user profiles to determine whether information relating to any known user profile is within a threshold similarity to the received biometric information and/or the received imaging information. It may be determined that information relating to the first user profile is within the threshold similarity to the received biometric information and/or the received imaging information. Based on this determination, the biometric information and/or the received imaging information may be stored in a portion of memory associated with the first user profile. 
     In some embodiments, upon determining that no information relating to any known user profile is within the threshold similarity to the received biometric information and/or the received imaging information, the biometric information, the imaging information, and the timestamp may be stored in a second portion of memory associated with a new user profile. 
     The method may include obtaining biometric information and image information associated with a user (block  706 ). This may be performed based on receiving an indication to retrieve information associated with a user that includes timestamps during a time duration. For example, a request may provide an indication to retrieve biometric data and image data for a first user from the last three months. 
     The method may include generating an interactive dashboard (block  708 ). An interactive dashboard may allow for a user to interact with and view various images and biometric information on the dashboard. An example interactive dashboard is described with respect to  FIG. 8 . 
     Generating an interactive dashboard may include separating the biometric information by type (block  708 ). This may include determining a type of biometric information (e.g., weight, body mass) and separating the data based on type. For example, all biometric information associated with the weight of the user may be identified and separated from other biometric information. Separating the biometric information by type may be utilized in ordering the information and determining trends in the changes in the types of biometric information. 
     Generating an interactive dashboard may include chronologically ordering the separated biometric information based on timestamps (block  710 ). This may include inspecting all timestamps and ordering the information based on times indicated by the timestamps. For example, a first set of biometric information includes a timestamp indicating 4:00 pm on January 1. In this example, a second set of biometric information includes a timestamp indicating 7:00 am on January 8. The timestamps can be inspected to order the first set of biometric information ahead of the second set of biometric information. 
     Generating an interactive dashboard may include chronologically ordering the image information based on the timestamps (block  712 ). This may include inspecting all timestamps and ordering the information based on times indicated by the timestamps similar to that with respect to ordering the separated biometric information. 
     The method may include generating an interactive dashboard that includes the ordered biometric information and image information (block  714 ). This may include displaying a graphical representation of the one or more chronologically ordered biometric information types, such as by a trendline as shown in  FIG. 8 . The dashboard may also include the series of images ordered chronologically. The dashboard is discussed in greater detail with respect to  FIG. 8 . 
     The method may include generating a video that includes a time-lapse of biometric information and image information according to the timestamps (block  716 ). Generating the video may include chronologically ordering the imaging information according to the timestamps and generating a graphical representation of biometric information types included in the biometric information ordered chronologically according to the timestamps. The video may include the ordered imaging information adjacent to the graphical representation of biometric information types. 
     Any of the interactive dashboard and the video may include data representing a plurality of measured pieces of biometric information of the user, along with captured images of the user, across a timeline having multiple time points based on a plurality of stored timestamps. 
     A generated video may be sent to an external device as specified in the request for the video that includes both biometric information and imaging information captured during the second time period. 
     Interactive Dashboard and Video Generation 
       FIGS. 8A-8B  are example user interfaces illustrating an interactive dashboard  800  that includes both biometric information and image information. The dashboard  800   a - b  may be outputted onto a device, such as a mobile device or computer, for example. In some embodiments, the interactive dashboard  800   a - b  may be displayed via an application executing on a device. 
     As shown in  FIG. 8A , the dashboard  800   a  can include various information, such as a set of initial information  802 , a set of body composition information  804 , trendline(s)  806 , and image information  812 . 
     The set of initial information  802  displayed on the dashboard may include various information relating to the user, such as the weight of BMI of the user, for example. In some embodiments, general information, such as a current time or an indication that a scale is connected, may be included in the set of initial information  802 . 
     The set of body composition information  804  may include various measurements relating to a body composition of a user at a given time. Example body composition measurements may include body fat, muscle, body water, lean body mass, bone mass, protein, visceral fat, BMR, metabolic age, etc. 
     As shown in  FIG. 8A , the body composition measurements can be associated with a first time period (e.g., January 1). A user may interact with the dashboard to view images and biometric information at various times (e.g., April 1). In some embodiments, the user may select to view the images and biometric information chronologically (e.g., from January 1 to April 1). 
     The trendline(s)  806  may provide a graphical representation of a type of biometric information as a function of time. For example, a weight of a user can be shown as a trendline using points (e.g., points  810   a - d ) indicative of the changes in the user&#39;s weight over a period of time. A trendline  808  can be added between points  810   a - d  to illustrate the changes to the weight over time. In some embodiments, selecting a body composition measurement (e.g., set of body composition information  804 ) may cause the dashboard to display a trendline  808  of the selected body composition measurement. 
       FIG. 8B  illustrates an example interactive dashboard at a second time. For example, while  FIG. 8A  illustrates information relating to a first date (e.g., January 1),  FIG. 8B  may illustrate information relating to a second date (e.g., April 1). The differences between the dates can reflect changes to a user body composition and images during the time between the dates. 
     In the example as shown in  FIG. 8B , the dashboard can include a separate set of body composition information  804  and an image of the user captured on April 1  812 . The differences in the body composition information and the images of the user in the dashboard can provide a multi-media visualization of a user&#39;s body transformation journey. 
       FIGS. 9A-9B  are example user interfaces illustrating a video that includes a time-lapse of both biometric information and image information. As noted above, the biometric information and the images of a user can be chronologically ordered and presented as a time-lapsed representation of a user&#39;s body transformation journey. In the embodiments as shown in  FIGS. 9A-9B , a video  900  depicting both images of the user and a graphical representation of the biometric information may be played on a user device (e.g., mobile phone, tablet, laptop). In some embodiments, the video may be downloaded and viewed by accessing an internet-accessible server that is hosting the video. 
     As shown in  FIG. 9A , the video at a first time (e.g., January 1) may include a banner  902 , a first portion of video  904  depicting an image of the user and a second portion of video  906  depicting a graphical representation of biometric information (e.g., a trendline of a user&#39;s weight during a timespan). In some embodiments, the first portion of video  904  may include a 3-dimensional image of the user, where as the video plays, the 3-dimensional image of the user may allow for multiple perspectives of the user. 
     The second portion of video  906  may include one or more trendlines (e.g., trendline  908 ) of a type of biometric information (e.g., weight of the user, BMI of the user) during a time span (e.g., from January 1 to April 1). In some embodiments, the second portion of video  906  can include a plurality of body composition metrics relating to a first time (e.g., January 1). 
       FIG. 9B  is an illustration of an example video at a second time (e.g., April 1). The video may display a series of images of the user and the biometric information for the user in a chronological order. In an example, the video may begin with a first frame relating to a first time (e.g., January 1) as shown in  FIG. 9A  and end with a final frame relating to a second time (e.g., April 1) as shown in  FIG. 9B . 
     In many cases, a device (e.g., a scale  102 , camera  106 ) may be added to the environment. For example, in order to capture a 3-dimensional image of a user, multiple cameras may be added to the environment.  FIGS. 10A-10C  are example block diagrams of interfaces that implement a process to activate a device in an environment as described herein. 
     Device Activation 
     A network device can be activated and associated with a user profile. As shown in  FIG. 10A , an interface  1000   a  may allow for a new device to be added into the environment. A device may be added into the environment to assist in performing the steps as described herein. For example, a camera may be added to the environment to capture an image of the user. Adding a device to the environment may associate the device to one or more users such that data acquired from that device can be associated with a user. In the example as shown in  FIG. 10A , the interface  1000   a  may provide a display  1002  requesting a selection of a device (e.g., scale  1004   a , camera  1004   b ) to add. 
     Upon selection of a device (e.g., scale  1004   a ), the interface  1000   b  may indicate an indication to connect a device  1006  (e.g., scale  1004   a ) to a user device. This request can allow for the user device to connect to the scale via a suitable communication interface (e.g., Bluetooth®). In some embodiments, the user device may initiate a setup procedure with the scale to associate the scale with a user or mobile application. 
     Upon successful connection to a device (e.g., scale), the interface  1000   c  can provide a confirmation message indicating that the device is successfully connected. This process may be repeated for any new devices that are to be connected in the environment. 
     Example Computing Environment 
       FIG. 11  is a system diagram illustrating an example of a computing environment  1100  in which the present embodiments may be implemented. In some implementations, environment  1100  includes one or more client computing devices  1105 A-D. Client computing devices  1105  operate in a networked environment using logical connections  1110  through network  1130  to one or more remote computers, such as a server computing device. 
     In some implementations, server  1110  is an edge server which receives client requests and coordinates fulfillment of those requests through other servers, such as servers  1120 A-C. In some implementations, server computing devices  1110  and  1120  comprise computing systems, such as computer system  100 . Though each server computing device  1110  and  1120  is displayed logically as a single server, server computing devices can each be a distributed computing environment encompassing multiple computing devices located at the same or at geographically disparate physical locations. In some implementations, each server  1120  corresponds to a group of servers. 
     Client computing devices  1105  and server computing devices  1110  and  1120  can each act as a server or client to other server/client devices. In some implementations, servers ( 1110 ,  1120 A-C) connect to a corresponding database ( 1115 ,  1125 A-C). As discussed above, each server  1120  can correspond to a group of servers, and each of these servers can share a database or can have its own database. Databases  1115  and  1125  warehouse (e.g., store) information such as user data (e.g., user identifiers, user profiles, etc.), web page data, machine learning models, performance parameters, and so on. Though databases  1115  and  1125  are displayed logically as single units, databases  1115  and  1125  can each be a distributed computing environment encompassing multiple computing devices, can be located within their corresponding server, or can be located at the same or at geographically disparate physical locations. 
     Network  1130  can be a local area network (LAN) or a wide area network (WAN), but can also be other wired or wireless networks. In some implementations, network  1130  is the Internet or some other public or private network. Client computing devices  1105  are connected to network  1130  through a network interface, such as by wired or wireless communication. While the connections between server  1110  and servers  1120  are shown as separate connections, these connections can be any kind of local, wide area, wired, or wireless network, including network  1130  or a separate public or private network. 
     CONCLUSION 
     Unless contrary to physical possibility, it is envisioned that (i) the methods/steps described above may be performed in any sequence and/or in any combination, and that (ii) the components of respective embodiments may be combined in any manner. 
     The techniques introduced above can be implemented by programmable circuitry programmed/configured by software and/or firmware, or entirely by special-purpose circuitry, or by a combination of such forms. Such special-purpose circuitry (if any) can be in the form of, for example, one or more application-specific integrated circuits (ASICs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), etc. 
     Software or firmware to implement the techniques introduced here may be stored on a machine-readable storage medium and may be executed by one or more general-purpose or special-purpose programmable microprocessors. A “machine-readable medium”, as the term is used herein, includes any mechanism that can store information in a form accessible by a machine (a machine may be, for example, a computer, network device, cellular phone, personal digital assistant (PDA), manufacturing tool, any device with one or more processors, etc.). For example, a machine-accessible medium can include recordable/non-recordable media (e.g., read-only memory (ROM), random access memory (RAM), magnetic disk storage media, optical storage media, flash memory devices, etc.). 
     Any of the steps as described in any methods or flow processes herein can be performed in any order to the extent the steps in the methods or flow processes remain logical. 
     Note that any and all of the embodiments described above can be combined with each other, except to the extent that it may be stated otherwise above or to the extent that any such embodiments might be mutually exclusive in function and/or structure. 
     Although the present invention has been described with reference to specific exemplary embodiments, it will be recognized that the invention is not limited to the embodiments described but can be practiced with modification and alteration within the spirit and scope of the appended claims. Accordingly, the specification and drawings are to be regarded in an illustrative sense rather than a restrictive sense.