Smart environment for condition monitoring of one or more subjects in a delimited area

Abstract

Technologies are disclosed for a condition monitoring system configured to monitor one or more characteristics of one or more subjects in a delimited area. First sensor devices are disposed in one or more substantially stationary locations proximate to the delimited area. The one or more first sensor devices capture a first data corresponding to the one or more subjects. Second sensor devices are disposed in one or more substantially non-stationary locations proximate to the delimited area. The second sensor devices capture a second data corresponding to the one or more subjects. A control device receives and processes signals corresponding to the first data and / or the second data to determine first characteristics, second characteristics, and / or first secondary characteristics of the one or more subjects. The first characteristics, the second characteristics, and / or the first secondary characteristics are output for display and / or further processing.

Description

SMART ENVIRONMENT FOR CONDITION MONITORING OF ONE OR MORE SUBJECTS IN A DELIMITED AREACROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Patent Application No.63 / 586,800, filed September 29, 2023, the entire disclosure of which is incorporated by reference herein, for all purposes.BACKGROUND

[0002] Subjects, such as animals, may suffer from a number of health issues such as anxiety, dermatitis, and / or allergy, among others, for example. Gathering physical parameters from animals for diagnosis and treatment of such conditions may be difficult, and in some aspects, may be relatively expensive for pet owners and / or other animal owners / handlers.

[0003] Animals, such as pets, may demonstrate behaviors and other symptoms related to their respective health conditions. Pets may demonstrate certain behaviors related to their respective health conditions while in a contained / isolated environment(s), such as a home environment. In some instances, pets may demonstrate certain other behaviors and / or different behaviors while in a group environment with other animals / pets.BRIEF SUMMARY

[0004] Technologies are disclosed for a condition monitoring system that may be configured to monitor one or more characteristics of one or more subjects in a delimited area, one or more devices implemented within the system, and / or one or more methods / techniques corresponding to the system. One or more first sensor devices may be disposed in one or more substantially stationary (e.g., mounted on typically non-movable objects, wired connections, etc.) locations proximate (e.g., inside, or within thirty feet, etc.) to the delimited area. The one or more first sensor devices may be configured to capture a first data corresponding to the one or more subjects.

[0005] One or more second sensor devices may be disposed in one or more substantially non- stationary (e.g., mounted or attached to typically movable / moving objects / subjects, wireless connections, etc.) locations proximate to the delimited area. The one or more second sensor devices may be configured to capture a second data corresponding to the one or more subjects.

[0006] A control device may comprise a memory, a display, and / or a transceiver. The transceiver may be configured to communicate with the first sensor devices and / or the second sensor devices via a wireless communication network, and / or a wired communication network.

[0007] The control device may comprise a processor. The processor may be configured to receive one or more first signals from the one or more first sensor devices. The one or more first signals may correspond to the first data. The processor may be configured to receive one or more second signals from the one or more second sensor devices. The one or more second signals may correspond to the second data.

[0008] The processor may be configured to process the one or more first signals to determine one or more first characteristics of the one or more subjects. The processor may be configured to process the one or more second signals to determine one or more second characteristics of the one or more subjects.

[0009] The processor may be configured to process the first data, and / or the second data, via one or more algorithms to determine one or more first secondary characteristics of the one or more subjects.

[0010] The processor may be configured to output to the display the one or more first characteristics, the one or more second characteristics, and / or the one more first secondary characteristics.

[0011] In one or more scenarios, one or more nutrition distribution stations may be disposed in one or more locations proximate to the delimited area. The one or more nutrition stations may be configured to capture a third data corresponding to the one or more subjects.

[0012] One or more sleeping surfaces may be disposed in one or more locations proximate to the delimited area. The one or more sleeping surfaces may be configured to capture a fourth data corresponding to the one or more subjects.

[0013] The processor may be configured to receive one or more third signals from the one or more nutrition distribution stations. The one or more third signals may correspond to the third data. The processor may be configured to receive one or more fourth signals from the one or more sleeping surfaces. The one or more fourth signals may correspond to the fourth data.

[0014] The processor may be configured to process the one or more third signals to determine one or more third characteristics of the one or more subjects. The processor may be configured to process the one or more fourth signals to determine one or more fourth characteristics of the oneor more subjects. The processor may be configured to process the first data, the second data, the third data, and / or the fourth data via the one or more algorithms to determine one or more second secondary characteristics of the one or more subjects.

[0015] The processor may be configured to output to the display the one or more third characteristics, the one or more fourth characteristics, and / or the one or more second secondary characteristics.

[0016] In one or more scenarios, the one or more first sensor devices may comprise one or more cameras, one or more weight sensors, one or more first proximity sensors, one or more microphones, and / or one or more first temperature sensors.

[0017] In one or more scenarios, the one or more second sensor devices may comprise one or more wearable devices. The one or more wearable devices may comprise an accelerometer, a heart rate monitor, a radio frequency identification (RFID) tracking device, breathing rate monitor, a caloric consumption sensor, a second temperature sensor, a gyroscope, a magnetometer, a thermometer, one or more light sensors, devices with Wi-Fi, Bluetooth, LAN, cellular, satellite, sub-GHz radio, low power wide area network (LPWAN) communications, low support low power mesh network communication protocols such as Zigbee, and / or a second proximity sensor.

[0018] In one or more scenarios, the one or more nutrition distribution stations may comprise one or more feeding dispensers, and / or one or more fluid (e.g., water, milk, rehydration fluid, etc.) dispensers. The system may further comprise one or more waste collection containers that may be disposed in one or more locations proximate to the delimited area. The one or more waste collection containers may be configured to capture a fifth data corresponding to the one or more subjects.

[0019] The processor may be configured to receive one or more fifth signals from the one or more waste collection containers. The one or more fifth signals may correspond to the fifth data. The processor may be configured to process the one or more fifth signals to determine one or more fifth characteristics of the one or more subjects. The processor may be configured to process the first data, the second data, the third data, the fourth data, and / or the fifth data via the one or more algorithms to determine one or more third secondary characteristics of the one or more subjects.

[0020] The processor may be configured to output to the display the one or more fifth characteristics, and / or the one or more third secondary characteristics.

[0021] In one or more scenarios, the one or more algorithms may comprise a subject segmentation algorithm, an individual subject identified algorithm, a subject behavioral algorithm, and / or a subject posture estimation algorithm.

[0022] In one or more scenarios, at least some of the one or more wearable devices may be in physical attachment to one or more of the subjects. The one or more subjects may comprise at least some animals. At least some of the animals may be one or more cats, and / or one or more dogs.

[0023] In one or more scenarios, at least one of the first data, the second data, the third data, the fourth data, and / or the fifth data may comprise individual subject data, interactive subject data, aggregate subject data, subject defecation data, eating date, drinking data, and / or subject urination data.

[0024] In one or more scenarios, the delimited area may comprise a delimited congregate subject area, and / or a delimited individual subject area. The delimited area may be configured to contain the one or more subjects substantially within the delimited area. The delimited area may comprise an enclosed area, and / or an unenclosed area.

[0025] In one or more scenarios, the processor may be further configured such that at least one of: the one or more first characteristics, the one or more second characteristics, the one or more third characteristics, the one or more fourth characteristics, and / or the one or more fifth characteristics may comprise a temperature of one or more subjects, a heart rate of one or more subjects, a weight of one or more subjects, a location in the delimited area of one or more subjects, fluid (e.g., water, milk, rehydration fluid, etc.) consumption of one or more subjects, a food consumption of one or more subjects, a resting time of one or more subjects, a sleeping time of one or more subjects, and / or a waste measurement of one or more subjects (e.g., solid waste, liquid waste, vomit discharge, hairball discharge, etc.).

[0026] In one or more scenarios, the control device may be a first control device. The first control device may comprise one or more second control devices in communication via a condition monitoring communication network. The condition monitoring communication network may comprise the wireless communication network, and / or the wired communication network.

[0027] In one or more scenarios, the processor may be further configured such that at least one of: the one or more first secondary characteristics, the one or more second secondary characteristics,and / or the one or more third secondary characteristics may comprise a behavior of one or more subjects, an identification of one or more subjects, and / or a posture of one or more subjects.BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The elements and other features, advantages and disclosures contained herein, and the manner of attaining them, will become apparent and the present disclosure will be better understood by reference to the following description of various examples of the present disclosure taken in conjunction with the accompanying drawings, wherein:

[0029] FIG. 1 is a block diagram illustrating an example condition monitoring communication network operable to control one or more parts of a condition monitoring system via one or more devices, such as a condition monitoring control device (CMCD) device, among other devices.

[0030] FIG. 2 is an example illustration of a delimited area in which subject canines may congregate, be separated for feeding, and / or be penned for a sleeping / rest period.

[0031] FIG. 3A and FIG. 3B is an example flow diagram of at least one technique for capturing data corresponding to one or more subjects in a condition monitoring system.

[0032] FIG. 4 is a block diagram of a hardware configuration of an example device that may control one or more parts of a condition monitoring system / communication network, such as the CMCD device of FIG. 1.

[0033] FIG. 5 is an example illustration of a delimited area in which subject canines may congregate and / or be penned for a sleeping / rest period.

[0034] FIG. 6 is an example illustration of a delimited area in which subject felines may congregate, take in nutrition, and / or be penned for a sleeping / rest period.

[0035] FIG. 7 illustrates an example an accelerometer signal as disposed in a wearable device on a subject of the delimited area.

[0036] FIG. 8 is an example illustration of one or more algorithms processing an accelerometer signal to determine one or more subject motions / behaviors.

[0037] FIG. 9 depicts an example illustration of a subject food change analytical technique that may utilize different aspects of the various sensor data from the delimited area.

[0038] FIG. 10 depicts an example of a characteristic of an accelerometer signal as disposed in a wearable device on a subject of the delimited area.

[0039] FIG. 11 is an example of a wearable sensor attached to feline subjects in a delimited area.

[0040] FIG. 12 depicts an example illustration of canine subjects being moved from an interior congregate space to an isolated space in a delimited area.

[0041] FIG. 13 depicts an example illustration of canine subjects in an interior congregate space and isolated spaces in a delimited area.

[0042] FIG. 14 is an example illustration of a canine subject feeding in an isolated space of a delimited area.

[0043] FIG. 15 depicts an example illustration of canine subjects in one or more exterior congregate spaces in a delimited area.

[0044] FIG. 16 is an example illustration of a canine subject resting in an isolated space of a delimited area.

[0045] FIG. 17 is an example illustration of a surveillance dashboard providing visualizations of one or more sensors and analytical techniques that utilize the various sensor data from the delimited area.

[0046] FIG. 18 is an example illustration of a surveillance dashboard providing visualizations of one or more sensors and analytical techniques that utilize the various sensor data from the delimited area.

[0047] FIG. 19 is an example illustration of a surveillance dashboard providing visualizations of one or more sensors and analytical techniques that utilize the various sensor data from the delimited area.

[0048] FIG. 20 is an example illustration of a surveillance dashboard providing visualizations of one or more camera sensors from exterior congregate spaces, interior congregate spaces, and interior isolated spaces in a delimited area.DETAILED DESCRIPTION

[0049] For the purposes of promoting an understanding of the principles of the present disclosure, reference will now be made to the examples illustrated in the drawings, and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of this disclosure is thereby intended.

[0050] FIG. 1 is a block diagram illustrating an example Condition Monitoring Communication System Network (CMCSN) 100 operable to monitor and / or control one or more pails of a Condition Monitoring System (CMS). One or more of digital and / or analog control signals,electronic content, various input signals, and or various output signals, among other condition monitoring system information may be communicated from / across / among the Condition Monitoring Communication System Network 100. One or more of discrete control and / or continuous control schemes, techniques, and / or algorithms may be processed / performed by / across / from the Condition Monitoring Communication System Network 100.

[0051] Electronic content may include media content, electronic documents, device-to-device communications, streaming media content, digital image still frames, digital streaming video, Internet / cloud-based electronic applications / services / databases, electronic communications / services (e.g.. video / audio conferencing), Internet-based electronic services, virtual reality content and / or services, augmented reality content and / or services, media captioning content and / or services, electronic commerce, video components / elements of electronic content, and / or audio components / elements of electronic content, among other types of electronic content. Electronic content may comprise labeled behaviors that results from applying one or more machine learning (ML) models to accelerometer data, gyroscope data, still image and / or video data, manual annotations of the data, metadata, firmware versions, animal identity, and / or camera number, etc.

[0052] In one or more scenarios, CMCSN devices HOa-d transmit / receive signals and / or communications and / or may receive data service(s) from a wide area network (WAN) 120 via a connection to a Condition Monitoring Communication Network (CMCN) 130. The one or more nodes of Condition Monitoring Communication Network 130 and / or the WAN 120 may communicate with one or more cloud-based nodes (not shown) via the Internet 124. A subject animal may interact (e.g., directly) with a video display device such as 140a or 140b or 140c or 140d, such as touching this device with its nose, paw, body, and / or just looking at it. This could turn on / off video, change the channel, start or stop audio players and / or microphone recording devices, dispense a treat, reveal a toy, result in positive feedback such as petting and / or praise, etc.

[0053] The CMCN devices can include, for example, a modem 110a, a process control device / logic controller 110b, a wireless router including an embedded modem 110c, or a media gateway 1 lOd, among many others (e.g., digital subscriber line (DSL) modem, voice over internet protocol (VOIP) terminal adapter, video game console, digital versatile disc (DVD) player, communications device, hotspot device, etc.). The Communication Monitoring Communication Network 130, for example, can be a hybrid fiber-coaxial (HFC) network, a local area network(LAN), a wireless local area network (WLAN), a cellular network, and / or a personal area network (PAN), as well as others. As used herein, a Condition Monitoring Control Device (CMCD) may be any of the devices 110a-l lOd and / or 140a- 140i, an Internet Gateway, a router device, a set-top box (STB), a process control device / logic controller, a smart media device (SMD), a cloud computing device, any type of CMCD, and / or any other suitable device (e.g., wired and / or wireless) that may be configured to perform one or more of the techniques and / or functionality disclosed herein, for example.

[0054] The CMCD devices can facilitate communications between the WAN 120 and devices 140a- 140i. A cable modem or embedded MTA (eMTA) 110 a can facilitate communications between the WAN 120 and a computer 140a. A process control device / logic controller 110b can facilitate communications between the WAN 120 and a television / monitor / display 140b (e.g., a media presentation device, a graphical user interface, a process control interface, etc.) and / or a digital video recorder (DVR). A wireless router 110c can facilitate communications between a computer 140c and the WAN 120.

[0055] The media gateway l lOd can facilitate communications between a mobile device 140d (e.g., a tablet computing device, a smartphone, a personal digital assistant (PDA) device, a laptop computing device, etc.; one or more devices being PC -based, iOS-based, Linux-based, Unix-like, and / or Android-based, etc.) and the WAN 120. One or more speaker devices (e.g., sound radiation devices / systems) 140e may be in communication with the Condition Monitoring Communication Network 130, process control device / logic controller 110b, and / or television / monitor / display 140b, etc. Camera devices 140g, 140h, and / or 140i may be in communication with the computer 140a, the television / display / monitor 140b, the computer 140c, and / or the Condition Monitoring Communication Network 130, for example, among other devices and networks.

[0056] The one or more speaker devices 140e (e.g., surround sound speakers, home theater speakers, other external wired / wireless speakers, loudspeakers, full-range drivers, subwoofers, woofers, mid-range drivers, tweeters, coaxial drivers, etc.) may broadcast at least an audio component of electronic content / media content, among other audio signals, processes, and / or applications. The one or more speaker devices 140e may possess the capability to radiate sound in pre-configured acoustical / physical patterns (e.g., a cone pattern, a directional pattern, etc.). For example, process control device / logic controller condition monitoring audible alarms may be communicated via one or more of the speaker devices 140e.

[0057] One or more microphone devices 140f may be external / standalone microphone devices. The one or more microphone devices 140f may be in communication with the Communication Monitoring Communication Network 130, process control device / logic controller 110b, television / display / monitor 140b, computer 140a, computer 140c, mobile device 140a, etc. Any of the devices HOa-l lOd and / or devices 140a- 140i may include internal microphone devices. The one or more speaker devices 140e (e.g., “speakers”) and / or the one or more microphone devices 140f (e.g., “microphones”, that may be “high quality” devices such as far field microphones, noise-cancelling microphones, shotgun microphones, dynamic microphones, ribbon microphones, and / or various size diaphragm microphones, Bluetooth™-based remote / control devices, RF4CE- based remote / control devices, etc.) may have wired and / or wireless connections (e.g., Bluetooth, Wi-Fi, private protocol communication network, etc.) to any of the other devices 140a- 140i, the Condition Monitoring Communication Network 130, the WAN 120, and / or the Internet 124.

[0058] The camera devices 140g- 140i may provide digital video input / output capability for one or more of the devices HOa-l lOd and / or devices 140a- 140d. The camera devices 140g- 140i may communicate with any of the devices HOa-l lOd and / or devices 140a-140f, perhaps for example via a wired and / or wireless connection. One or more of the camera devices 140g- 140i may capture digital images, digital video streams, and / or may scan images of various kinds, such as Universal Product Code (UPC) codes and / or Quick Response (QR) codes, for example, among other images. One or more of the camera devices 140g- 140i may provide for video input / output for video monitoring (e.g., may serve as webcams or the like), for example, among other video functions.

[0059] Any of the camera devices 140g-140i may include microphone devices and / or speaker devices. The input / output of any of the camera devices 140g- 140i may include audio signals / packets / components, perhaps for example separate / separable from, or in some (e.g., separable) combination with, the video signals / packets / components of any of the camera devices 140g- 140i.

[0060] One or more of the camera devices 140g- 140i may detect the presence of one or more subjects and / or things that may be proximate to the camera devices 140g-140i and / or that may be in the same general space (e.g., the same room, same space, same room, same delimited area, etc.) as the camera devices 140g- 140i. One or more of the camera devices 140g- 140i may gauge a general activity level (e.g., high activity, medium activity, and / or low activity) of one or more subjects that may be detected by the camera devices 140g- 140i. One or more of the camera devices140g- 140i may detect one or more general characteristics (e.g., height, body shape, skin color, pulse, heart rate, breathing count, object size, object volume, object bulk, etc.) of the one or more subjects detected by the camera devices 140g- 140i. One or more of the camera devices 140g- 140i may be configured to recognize one or more specific subjects, for example. One or more of the camera devices 140g- 140i may be configured to detect a subject’s attention / gaze toward another subject (e.g., detecting a subject and / or object that may correspond to a subject’s attention / gaze toward another subject or object).

[0061] One or more of the camera devices 140g- 140i may be use wireless communication with any of the devices 110a-l lOd and / or 140a- 140d, such as for example Bluetooth™ and / or Wi-Fi™, among other wireless communication protocols. One or more of the camera devices 140g- 140i may be external to any of the devices HOa-l lOd and / or devices 140a- 140d. One or more of the camera devices 140g-140i may be internal to any of the devices HOa-l lOd and / or devices 140a- 140d.

[0062] One or more of the camera devices 140g- 140i may be a (e.g., industrial and / or commercial and / or residential) vision camera device. The vision camera may be a gigabit Ethernet compatible device (e.g., 10 GB Ethernet, or the like). The vision camera may function in black & white and / or color. The vision camera may have a capacity of at least 8.8 megapixel, or the like. The vision camera may have a resolution of 4096 x 2160 pixel, or the like. For example, the vision camera may be a (e.g., manufactured by Baumer such as a VLXT-90C.I LX series, or like / equivalent or other device as mentioned herein) may capture product images in various forms such as digital still image frames and / or video streams, etc., perhaps for example from zero to ninety-five (95) frames per second (fps). The vision camera may have one or more parameters configurable remotely and / or locally.

[0063] CMCD devices such as process control device / logic controller devices, media gateway devices, among others, may support visual and / or voice interface with users, viewers, and / or Condition Monitoring Communication Network 130 operators. This interface may support smart enhancement to the user / viewer / operator experience, for example in the condition monitoring network environment, or in any network environment. One or more traditional and / or current viewer experiences can be enriched to utilize visual and / or voice interface, perhaps for example to derive smart actions and / or results.

[0064] In one or more scenarios, any of the devices 110a-l lOd, 140a-l40i, among other devices, may be used to implement any of the capabilities, techniques, methods, and / or devices described herein.

[0065] The WAN network 120 and / or the Condition Monitoring Communication Network 130 may be implemented as any type of wired and / or wireless network, including a local area network (LAN), a wide area network (WAN), a global network (the Internet), etc. Accordingly, the WAN network 120 and / or the Condition Monitoring Communication Network 130 may include one or more communicatively coupled network computing devices (not shown) for facilitating the flow and / or processing of network communication traffic via a series of wired and / or wireless interconnections. Such network computing devices may include, but are not limited, to one or more access points, routers, switches, servers, computing devices, and / or storage devices, etc.

[0066] Described herein is a subject housing area / delimited area, where the subjects may be animals, such as canines and / or felines. The delimited area may be embedded with technology to stream most pails, perhaps every part, of the subject’s day and / or night. One or more cameras may be aimed / focused at one or more various spaces in the area, at isolated sleeping pens, and / or at subject feeders, waste deposition areas such as litterboxes, and / or at other areas of interest such as outdoor spaces, toys, etc. The delimited area may include microphones, proximity sensors, smart subject beds, and other sensors and / or smart technology. One or more wearable devices may be attached to the one or more subjects, where the wearable devices may comprise one or more sensors.

[0067] A connected ecosystem, like the delimited area may be a canine / dog smart room and / or a feline / cat smart room that may comprise a variety of sensor modalities. The delimited area / smait room may be with technology that may enable learning as much as possible about subject / pet health. Wearables (e.g., collar bom), proximity sensors, as well as cameras (e.g., such as those mounted on smart room walls / ceilings), microphones, and / or other smart devices / sensors may provide data for understanding subject’s emotional states, social interactions, and / or behavior patterns. The sensors in and / or around the smart rooms may capture data corresponding to most / every part of the subject’s day, such as eating, drinking, playing, running, napping, and / or sleeping, among other subject activities. This data may be used to determine one or more characteristics corresponding to the one or more subjects. This data may support enablement / development of one or more algorithms and / or may quantify subject behavior patterns.The data collected in the room may provide a live / real time monitoring system / recording system for the use of the subject’s caretakers. Any of the cameras described herein may be placed in a substantially stationary location and / or in a substantially mobile context (e.g., on a mobile device, etc.). Any of the cameras described herein, however placed, may be controlled (e.g., locally and / or remotely) to pan, zoom, tilt, focus, etc. Any of the cameras described herein, however placed, may be black & white, color, infrared, etc. cameras.

[0068] Subjects in the delimited area / smart rooms may be group housed and / or free to move as they please, indoors and / or outdoors. The subjects may exhibit behaviors freely, and / or may engage in social interaction with other subjects and / or non-subjects (e.g., humans and / or other animals) in a way that is not possible in isolated subject housing. The smart room may track subject behaviors to learn about subject movements and / or social interactions, and / or may link that information / data with connected devices disposed in, developed for, prototyped in, and / or tested in the smart room, as well as subject health databases. Such data may enable device and / or algorithm development, tracking early indicators of disease and / or changes in subject health (e.g., detection of subclinical and clinical indicators), and / or tracking behavior over time. The smart room may collect room, sleeping pen camera data, feeder camera data, audio data, weight data, and location data through RFID tracking, among other sensor data. Pens may be used for sleeping, resting, eating, drinking, collection of samples, medical procedures, forced isolation, etc.

[0069] Collar worn wearable devices can capture valuable information about subject / pet behavior through motions of the subject’ s / pet’s head and / or neck. Being able to measure other behaviors such as location in a room, proximity to other subjects / animals, proximity to feeders and / or sleeping surfaces / beds, information about eating, drinking, urinating, defecating, pet weight, etc., may benefit from a connected ecosystem embedded with many kinds of smart technology / sensors to stream / record data over a daily / weekly / y early period. Information for individual subjects / pets, groups of subjects / pets, may be tracked / studied / observed over time to identify changes. Such data may be linked to other subject / pet health information.

[0070] One or more algorithms may be useful to interpret sensor data coming from the smart room / delimited area. For example, one or more algorithms may be deployed to make inferences / interpretations regarding subject / animal behavior. For example dog / cat / subject segmentation algorithms may allow for isolation of images of subjects / dogs / cats from within an arbitrary setting. Individual identification algorithms may allow for continuous monitoring of aspecified individual / subject within a group house context. Behavior recognition algorithms may allow for identification of periods of data containing subject behaviors of interest. Posture estimation algorithms may provide posture information that may compliment behavior recognition, etc.

[0071] For example, if a bed sensor detects an increase or decrease in weight for a dog vs. the dog's typical weight, a video camera could be used to determine if the dog is only partly on the bed, if there are multiple dogs on the bed, if the dog brought a toy on the bed, and / or if the dog is by itself on the bed (e.g., in which case the dog might have gained or lost weight). This could allow the owner to better interpret the weight data and, if useful, manage the dog's food intake and exercise to support optimal weight.

[0072] For example, if a sensor detects a dog is walking differently than usual, a bed sensor could be used to see if the dog has gained weight, this could allow the owner to manage the dog's food intake and / or exercise to support optimal weight, and / or seek veterinary advice as needed.

[0073] For example, if a sensor detects little or no movement, then a temperature sensor could be used to determine if the dog is running a fever / is ill. This could allow the owner to recognize an early sign of illness and / or seek appropriate care for the pet.

[0074] For example, if a bed sensor shows the dog is sleeping poorly, the bed sensor (e.g., a weight and / or proximity sensor, a camera, etc.) could be used to determine if the dog spends a lot of time resting and / or sleeping the following day. This information (e.g., poor sleep, followed by sleeping / resting) could allow the owner to better manage activities and / or plans for the day.

[0075] For example, if a bed senor or other sensor detects that the dog is agitated / not sleeping well at night, one or more microphones could be used to determine if the dog were howling / whining (e.g., indicating anxiety) and / or if there is an environmental sound (e.g., like thunder or traffic noise) that was responsible for the dog not sleeping well. There may be various solutions to these issues. For example, if the dog was anxious, a behavior plan and / or medication may be useful. For example, if there was environmental noise like traffic, then moving the dog’s bed and / or sound insulation may be useful.

[0076] Delimited areas / smart rooms may include Smart Cat Condos for a feline colony and / or a full Smart Pet Room for a (e.g., small dogs) canine colony. An example Smart Cat Condo may comprise a single room of 15 cat condos, such as that illustrated in FIG 6. One or more, or each, condo may comprise nutrition scales (e.g., water / fluids and / or food scales), a litterbox scale, oneor more cameras that may be aimed / focused at the scales, at the food and / or water / fluids bowls, waste collection stations, etc. The cats may wear wearable devices. An example canine Smart Pct Room may comprise multiple sections / spaces, housing as many as sixteen dogs, among other numbers of dogs, for example. The Smart Rooms may collect data periodically and / or constantly throughout the day / night using room and pen cameras, feeder scales, feeder cameras, wearable devices, and / or other sensors enabling measuring most / every aspect of the subject’ s / pet’s day. Through the data generated by the smart room, metrics related to the subject’ s / pet’ s location and / or social behavior may be determined. Video data may be collected corresponding events like eating and / or spontaneous events like “booty scooting”, among other subject events. Such metrics derived from this information and / or video can be displayed in a dashboard format, for example in FIG. 16, FIG. 17, FIG. 19, and / or FIG. 20.

[0077] Without the capabilities, techniques, methods, systems, and / or devices described herein, the skilled artisan would not appreciate how to determine various characteristics corresponding to a plurality of subjects in a delimited area. The present disclosure provides the skilled artisan with the capability, systems, devices, methods, and / or techniques to deploy various sensors in the interior / exterior congregate spaces and / or exterior / interior isolated spaces in a delimited area. The present disclosure also provides the skilled artisan with the capability, systems, devices, methods, and / or techniques to collect signals from the various sensors and to determine one or more characteristics corresponding to the subjects in the delimited area based on those sensor signals. Such capability, systems, devices, methods, and / or techniques may be useful for such purposes, as well as other purposes, such as providing data for multi-variable analytical techniques to determine / estimate subject behavior and / or health, among other subject characteristics.

[0078] FIG. 2 is an example illustration of a smart room / delimited area 202 in which subject canines (not shown) may congregate, be separated for feeding, drinking, and / or be penned for a sleeping / rest period, stool collection, urine collection, and / or medical / wellbeing evaluation. In FIG. 2, the delimited area 202 may comprise one or more sleeping pens 206, 208. The delimited area 202 may comprise one or more feeding pens 210. The delimited area may comprise one or more observation stations 218. The delimited area 202 may comprise one or more congregate spaces 212, 214. The delimited area 202 may comprise one or more cameras 216 (e.g., that may be the same or similar as other cameras disclosed herein). The delimited area 202 may comprise one or more other sensors (not shown) such as microphones, proximity sensors, wearable sensors,among other sensors, for example. Any of the sensors in the delimited area 202 may be configured for wired and / or wireless transmission via the Condition Monitoring Communication Network 130.

[0079] FIG. 5 is an example illustration of a delimited area 502 in which subject canines (not shown) may congregate and / or be penned for a sleeping / rest period. The delimited area 502 may comprise at least one congregate space 512 and / or one or more isolated sleeping pens 514. The delimited area 502 may comprise one or more cameras 508. The delimited area 502 may comprise one or more other sensors (not shown) such as microphones, proximity sensors, wearable sensors, among other sensors, for example. Any of the sensors in the delimited area 502 may be configured for wired and / or wireless transmission via the Condition Monitoring Communication Network 130.

[0080] FIG. 6 is an example illustration of a delimited area 602 (e.g., a “cat condo”) in which one or more subject felines (not shown) may congregate, take in nutrition, and / or be penned for a sleeping / rest period, stool collection, urine collection, and / or medical / wellbeing evaluation. The delimited area 602 may comprise one or more cameras 604 (e.g., focused on the general area, litter boxes, nutrition dispensing stations, etc.). The delimited area 602 may comprise a food distribution station 608 and / or a fluid (e.g., water, milk, rehydration fluid, etc.) distribution station 610. The delimited area 602 may comprise a waste collection station 606 and / or a sleeping surface 612. The delimited area 602 may comprise one or more other sensors (not shown) such as microphones, proximity sensors, cameras, wearable sensors, among other sensors, for example. Any of the sensors in the delimited area 602 may be configured for wired and / or wireless transmission via the Condition Monitoring Communication Network 130.

[0081] FIG. 7 illustrates an example accelerometer and corresponding signal 702 as may be disposed in a wearable device on a subject of the delimited area (not shown). Accelerometer 706 may be disposed on a cat and / or dog collar (not shown). The characteristic 708 may correspond to a wired and / or wireless signal from the accelerometer 706. The accelerometer 707 may be at least one of one or more types of accelerometers. The accelerometer 706 may be configured for wired and / or wireless transmission via the Condition Monitoring Communication Network 130.

[0082] FIG. 8 is an example illustration 802 of one or more algorithms / neural networks 804 processing an accelerometer signal 806 (e.g., triaxial accelerometer data) to determine one or more subject motions / behaviors (e.g., characteristics) 808. In one or more scenarios, a random forestalgorithm may be used (not shown), among other types of algorithms. Other types of behaviors can be labelled in addition to, or in lieu of, those shown in FIG. 8.

[0083] Different analytical techniques may utilize different aspects of the various sensor data from the delimited area. One or more different analytic methods make use of different features of the data. Some analytic methods may rely on summary measures to make inferences. Other analytic methods may use more details in the data and / or may aim to describe patterns with or without making inferences. Other methods may use details in the data to create data features and / or examine patterns in these data features, with or without making inferences. In one or more scenarios, combinations of these approaches can be used.

[0084] FIG. 9 depicts an example illustration 1002 of a subject food change analytical technique that utilize different aspects of the various sensor data from the delimited area (not shown). Sensor 1008 (e.g., a wearable accelerometer) may capture data corresponding to a subject dog’s consumption of usual food 1012. The sensor 1008 may capture data corresponding to the subject dog’s consumption of new food 1014. One or more algorithms may process data from sensor 1008 (and / or other sensor data not shown) to determine the dog’s behavior with the usual food consumption and the new food consumption. The processing may provide some insight as to if the behavior is unusual for the dog. The processing may provide some insight as to if the behavior change meets a minimum threshold (e.g., health threshold, activity threshold, etc.). The processing may provide insight as to if there was a change in a group of behaviors that characterize dermatitis, or other health conditions, for example. More generally, one or more of the sensors described herein may be used to understand (e.g., typical) behavior patterns and / or changes in behavior patterns, perhaps for example after a change such as a food, medication, therapy, etc., may be introduced. Comparisons of pre and / or post changes / introductions of the food, medication, and / or therapy, etc., may be made to understand the effect of the changes, among other reasons.

[0085] FIG. 10 depicts an illustration 1402 of a characteristic of an accelerometer signal 1404 as disposed in a wearable device (not shown) on a subject feline 1406 of the delimited area (not shown). For example, analysis of the accelerometer signal 1404 may be interpreted as “post scratching” by the subject feline 1406.

[0086] FIG. 11 is an example illustration 1602 of a wearable sensors 1604, 1606 attached to feline subjects 1610, 1612 in a delimited area (not shown).

[0087] FIG. 12 depicts an example illustration of canine subjects 1704 being moved from an interior congregate space 1708 to an isolated space 1710 (e.g., a feeding pen) in a delimited area 1702. The delimited area 1702 may comprise one or more other sensors (not shown) such as microphones, proximity sensors, wearable sensors, among other sensors, for example. Any of the sensors in the delimited area 1702 may be configured for wired and / or wireless transmission via the Condition Monitoring Communication Network 130.

[0088] FIG. 13 depicts an example illustration of canine subjects 1804 in an interior congregate space 1806 and one or more isolated spaces 1808 in a delimited area 1802. The delimited area 1802 may comprise one or more other sensors (not shown) such as microphones, proximity sensors, wearable sensors, among other sensors, for example. Any of the sensors in the delimited area 1802 may be configured for wired and / or wireless transmission via the Condition Monitoring Communication Network 130.

[0089] FIG. 14 is an example illustration of a canine subject 1904 feeding from a food dispensing station 1906 (e.g., a nutrition station) in an isolated space of a delimited area 1902. The delimited area 1902 may comprise one or more other sensors (not shown) such as microphones, proximity sensors, wearable sensors, among other sensors, for example. Any of the sensors in the delimited area 1902 may be configured for wired and / or wireless transmission via the Condition Monitoring Communication Network 130.

[0090] FIG. 15 depicts an example illustration of canine subjects 2004 in one or more exterior congregate spaces 2006, 2008 in a delimited area 2002. The delimited area 2002 may comprise one or more other sensors (not shown) such as microphones, proximity sensors, wearable sensors, among other sensors, for example. Any of the sensors in the delimited area 2002 may be configured for wired and / or wireless transmission via the Condition Monitoring Communication Network 130.

[0091] FIG. 16 is an example illustration of a canine subject 2104 resting and / or sleeping in an isolated space 2106 of a delimited area 2102. The isolated space 2106 may comprise a food dispensing station 2108 and / or a fluid (e.g., water, milk, rehydration fluid, etc.) dispensing station 2110 that may be configured to communicate wirelessly or via wired communication. The delimited area 2102 may comprise one or more other sensors (not shown) such as microphones, proximity sensors, wearable sensors, among other sensors, for example. Any of the sensors in thedelimited area 2102 may be configured for wired and / or wireless transmission via the Condition Monitoring Communication Network 130.

[0092] FIG. 17 is an example illustration of a surveillance dashboard 2202 that may provide visualizations of one or more sensors and analytical techniques that utilize the various sensor data from the delimited area.

[0093] FIG. 18 is an example illustration of a surveillance dashboard 2302 that may provide visualizations of one or more sensors and analytical techniques that utilize the various sensor data from the delimited area.

[0094] FIG. 19 is an example illustration of a surveillance dashboard 2402 that may provide visualizations of one or more sensors and analytical techniques that utilize the various sensor data from the delimited area. Video can help track the subject dogs’ locations, where each dog may be tracked using a number and / or an identifying line so it can be determined where the dogs are, how long they stayed there, and where they went next. It can also be learned about how the dogs socialize, such as positive and / or negative social interactions in the group. That may allow for relationship maps like the one on the right the dashboard 2402. By integrating video, microphone and / or wearables data it can also see when something exciting may be happening in the smart room and / or measure those events using room metrics, for example.

[0095] FIG. 20 is an example illustration of a surveillance dashboard 2502 that may provide visualizations of one or more camera sensors from exterior congregate spaces, interior congregate spaces, and interior isolated spaces in a delimited area.

[0096] In one or more scenarios, one or more of the accelerometers may be commercially available wearable accelerometers. In one or more scenarios, the one or more cameras may be commercially available YI 1080P Home Camera, for example, among other cameras. In one or more scenarios, the weight scale may be a commercially available scale and / or a custom built / modified scale, for example, among other scales.

[0097] In view of FIG. 1, FIG. 2, and FIG. 5 to FIG. 20, it can be understood that technologies are disclosed herein for a condition monitoring system. The condition monitoring system may be configured to monitor one or more characteristics of one or more subjects in a delimited area (e.g., smart room). One or more devices may be implemented within the system, and / or one or more methods / techniques corresponding to the system may be implemented. One or more first sensor devices may be disposed in one or more substantially stationary (e.g., mounted on typically non-movable objects, wired connections, etc.) locations proximate (e.g., inside, or within thirty feet, etc.) to the delimited area. The one or more first sensor devices may be configured to capture a first data corresponding to the one or more subjects.

[0098] One or more second sensor devices may be disposed in one or more substantially non- stationary (e.g., mounted or attached to typically movable / moving objects / subjects, wireless connections, etc.) locations proximate to the delimited area. The one or more second sensor devices may be configured to capture a second data corresponding to the one or more subjects.

[0099] A control device may comprise a memory, a display, and / or a transceiver. The transceiver may be configured to communicate with the first sensor devices and / or the second sensor devices via a wireless communication network, and / or a wired communication network.

[0100] The control device may comprise a processor. The processor may be configured to receive one or more first signals from the one or more first sensor devices. The one or more first signals may correspond to the first data. The processor may be configured to receive one or more second signals from the one or more second sensor devices. The one or more second signals may correspond to the second data.

[0101] The processor may be configured to process the one or more first signals to determine one or more first characteristics of the one or more subjects. The processor may be configured to process the one or more second signals to determine one or more second characteristics of the one or more subjects.

[0102] The processor may be configured to process the first data, and / or the second data, via one or more algorithms to determine one or more first secondary characteristics of the one or more subjects.

[0103] The processor may be configured to output to the display the one or more first characteristics, the one or more second characteristics, and / or the one more first secondary characteristics (e.g., the dashboards of FIG. 17 and / or FIG. 18).

[0104] In one or more scenarios, one or more nutrition distribution stations may be disposed in one or more locations proximate to the delimited area. The one or more nutrition stations may be configured to capture a third data corresponding to the one or more subjects. The one or more nutrition distribution stations may comprise weight scales, load cells, flow metering, etc., that may be configured for wired and / or wireless communication to signal how much, how frequently,and / or what kind of nutrition the subjects may consume in real time and / or over various periods of time, for example.

[0105] One or more sleeping / resting surfaces may be disposed in one or more locations proximate to the delimited area. The one or more sleeping surfaces may be configured to capture a fourth data corresponding to the one or more subjects. The one or more sleeping surfaces may comprise weight scales, load cells, etc., that may be configured for wired and / or wireless communication to signal how much, how frequently, and / or what kind of rest / sleep the subjects may obtain in real time and / or over various periods of time, for example.

[0106] The processor may be configured to receive one or more third signals from the one or more nutrition distribution stations. The one or more third signals may correspond to the third data. The processor may be configured to receive one or more fourth signals from the one or more sleeping surfaces. The one or more fourth signals may correspond to the fourth data.

[0107] The processor may be configured to process the one or more third signals to determine one or more third characteristics of the one or more subjects. The processor may be configured to process the one or more fourth signals to determine one or more fourth characteristics of the one or more subjects. The processor may be configured to process the first data, the second data, the third data, and / or the fourth data via the one or more algorithms to determine one or more second secondary characteristics of the one or more subjects.

[0108] The processor may be configured to output to the display the one or more third characteristics, the one or more fourth characteristics, and / or the one or more second secondary characteristics (e.g., the dashboards of FIG. 17 and / or FIG. 18).

[0109] In one or more scenarios, the one or more first sensor devices may comprise one or more cameras, one or more weight sensors, one or more first proximity sensors, one or more microphones, and / or one or more first temperature sensors.

[0110] In one or more scenarios, the one or more second sensor devices may comprise one or more wearable devices. The one or more wearable devices may comprise an accelerometer, a heart rate monitor, a radio frequency identification (RFID) tracking device, breathing rate monitor, a caloric consumption sensor, a second temperature sensor, and / or a second proximity sensor.

[0111] In one or more scenarios, the one or more nutrition distribution stations may comprise one or more feeding dispensers, and / or one or more fluid (e.g., water, milk, rehydration fluid, etc.) dispensers. The system may further comprise one or more waste collection containers that maybe disposed in one or more locations proximate to the delimited area. The one or more waste collection containers may be configured to capture a fifth data corresponding to the one or more subjects. The one or more waste collection containers may comprise weight scales, load cells, etc., that may be configured for wired and / or wireless communication to signal how much, how frequently, and / or what kind of waste effluent the subjects may pass in real time and / or over various periods of time, for example.

[0112] The processor may be configured to receive one or more fifth signals from the one or more waste collection containers. The one or more fifth signals may correspond to the fifth data. The processor may be configured to process the one or more fifth signals to determine one or more fifth characteristics of the one or more subjects. The processor may be configured to process the first data, the second data, the third data, the fourth data, and / or the fifth data via the one or more algorithms to determine one or more third secondary characteristics of the one or more subjects.

[0113] The processor may be configured to output to the display the one or more fifth characteristics, and / or the one or more third secondary characteristics.

[0114] In one or more scenarios, the one or more algorithms may comprise algorithms that may identify and / or measure objects and / or subjects.

[0115] In one or more scenarios, at least some of the one or more wearable devices may be in physical attachment to one or more of the subjects. The one or more subjects may comprise at least some animals. At least some of the animals may be one or more cats, and / or one or more dogs.

[0116] In one or more scenarios, at least one of the first data, the second data, the third data, the fourth data, and / or the fifth data may comprise individual subject data, interactive subject data, aggregate subject data, subject defecation data, eating data, drinking data, drinking data, and / or subject urination data.

[0117] In one or more scenarios, the delimited area may comprise a delimited congregate subject area, and / or a delimited individual subject area. The delimited area may be configured to contain the one or more subjects substantially within the delimited area. The delimited area may comprise an enclosed area, and / or an unenclosed area.

[0118] In one or more scenarios, the processor may be further configured such that at least one of the one or more first characteristics, the one or more second characteristics, the one or more third characteristics, the one or more fourth characteristics, and / or the one or more fifthcharacteristics may comprise a temperature of one or more subjects, a heart rate of one or more subjects, a weight of one or more subjects, a location in the delimited area of one or more subjects, a fluid (e.g., water, milk, rehydration fluid, etc.) consumption of one or more subjects, a food consumption of one or more subjects, a resting time of one or more subjects, a sleeping time of one or more subjects, and / or a waste measurement of one or more subjects (e.g., solid waste, liquid waste, vomit discharge, hairball discharge, etc.).

[0119] In one or more scenarios, the control device may be a first control device. The first control device may comprise one or more second control devices in communication via a condition monitoring communication network. The condition monitoring communication network may comprise the wireless communication network, and / or the wired communication network. For example, the condition monitoring communication network may be the Condition Monitoring Communication Network 130.

[0120] In one or more scenarios, the processor may be further configured such that at least one of the one or more first secondary characteristics, the one or more second secondary characteristics, and / or the one or more third secondary characteristics may comprise a behavior of one or more subjects, an identification of one or more subjects, and / or a posture of one or more subjects.

[0121] In one or more scenarios, the processor may be configured to generate one or more alerts and / or alarms (e.g., for display on a “dashboard” and / or alarm panel, etc.) based on any of the characteristics and / or signals described herein.

[0122] Referring now to FIG. 3, a diagram 300 illustrates an example technique for monitoring one or more characteristics of one or more subjects in a delimited area via a condition monitoring communication network. The method may be performed by a condition monitoring control device (CMCD), among other devices. For example, the condition monitoring control device may be a process control device / logic controller 110b, among other devices HOa-l lOd and / or 140a- 140i, and / or a cloud computing device. The condition monitoring control device (CMCD) may be in communication with any of the devices of the Condition Monitoring Communication System Network (CMCSN) 100. At 302, the process may star! or restart.

[0123] At 304, the condition monitoring control device dispose one or more first sensor devices in one or more substantially stationary locations proximate to the delimited area. The one or more first sensor devices may capture a first data corresponding to the one or more subjects. At 306, the condition monitoring control device may dispose one or more second sensor devices in one ormore substantially non-stationary locations proximate to the delimited area. The one or more second sensor devices may capture a second data corresponding to the one or more subjects.

[0124] At 308, the condition monitoring control device may receive one or more first signals from the one or more first sensor devices. The one or more first signals may correspond to the first data. At 310, the condition monitoring control device may receive one or more second signals from the one or more second sensor devices. The one or more second signals may correspond to the second data.

[0125] At 312, the condition monitoring control device may determine (e.g., via at least one processor) one or more first characteristics of the one or more subjects based on the one or more first signals. At 314, the condition monitoring control device may determine (e.g., via the least one processor) one or more second characteristics of the one or more subjects based on the one or more second signals.

[0126] At 316, the condition monitoring control device may process (e.g., via the at least one processor) at least one of: the first data, or the second data via one or more algorithms to determine one or more first secondary characteristics of the one or more subjects. At 318, the condition monitoring control device may display (e.g., via at least one display) at least one of: the one or more first characteristics, the one or more second characteristics, and / or the one more first secondary characteristics. At 320, the process may stop or restart.

[0127] FIG. 4 is a block diagram of a hardware configuration of an example device that may function as a process control device / logic controller, such as the Condition Monitoring Control Device 110b of FIG. 1, among other devices such asl40a-140i, and any of the devices 110a-l lOd, for example. The hardware configuration 400 may be operable to facilitate delivery of information from an internal server of a device. The hardware configuration 400 can include a processor 410, a memory 420, a storage device 430, and / or an input / output device 440. One or more of the components 410, 420, 430, and 440 can, for example, be interconnected using a system bus 450. The processor 410 (e.g., CPU. GPU, etc.) can process instructions for execution within the hardware configuration 400. The processor 410 can be a single-threaded and / or single core processor or the processor 410 can be a multi-threaded and / or multi-core processor. The processor 410 can be capable of processing instructions stored in the memory 420 and / or on the storage device 430.

[0128] The memory 420 can store information within the hardware configuration 400. The memory 420 can be a computer-readable medium (CRM), for example, a non-transitory CRM. The memory 420 can be a volatile memory unit, and / or can be a non-volatile memory unit.

[0129] The storage device 430 can be capable of providing mass storage for the hardware configuration 400. The storage device 430 can be a computer-readable medium (CRM), for example, a non-transitory CRM. The storage device 430 can, for example, include a hard disk device, an optical disk device, flash memory and / or some other large capacity storage device. The storage device 430 can be a device external to the hardware configuration 400.

[0130] The input / output device 440 may provide input / output operations for the hardware configuration 400. The input / output device 440 e.g., a transceiver device) can include one or more of a network interface device (e.g., an Ethernet card), a serial communication device (e.g., an RS-232 port), one or more universal serial bus (USB) interfaces (e.g., a USB 2.0 / 3.0 port) and / or a wireless interface device (e.g., an 802.11 card). The input / output device can include driver devices configured to send communications to, and / or receive communications from one or more networks (e.g., Condition Monitoring Communication Network 130 of FIG. 1). The input / output device 400 may be in communication with one or more input / output modules (not shown) that may be proximate to the hardware configuration 400 and / or may be remote from the hardware configuration 400. The one or more output modules may provide input / output functionality in the digital signal form, discrete signal form, TTL form, analog signal form, serial communication protocol, fieldbus protocol communication and / or other open or proprietary communication protocol, and / or the like.

[0131] The camera device 460 may provide digital video input / output capability for the hardware configuration 400. The camera device 460 may communicate with any of the elements of the hardware configuration 400, perhaps for example via system bus 450. The camera device 460 may capture digital images and / or may scan images of various kinds, such as Universal Product Code (UPC) codes and / or Quick Response (QR) codes, for example, among other images as described herein. In one or more scenarios, the camera device 460 may be the same and / or substantially similar to any of the other camera devices described herein.

[0132] The camera device 460 may include at least one microphone device and / or at least one speaker device (not shown). The input / output of the camera device 460 may include audiosignals / packets / components, perhaps for example separate / separable from, or in some (e.g., separable) combination with, the video signals / packets / components the camera device 460.

[0133] The camera device 460 may also detect the presence of one or more subjects that may be proximate to the camera device 460 and / or may be in the same general space (e.g., the same room, delimited area, etc.) as the camera device 460. The camera device 460 may gauge a general activity level (e.g., high activity, medium activity, and / or low activity) of one or more subjects that may be detected by the camera device 460. The camera device 460 may detect one or more general characteristics (e.g., height, body shape, skin color, pulse, fur, fur type / thickness, heart rate, breathing count, weight, gait parameters, etc.) of the one or more subjects detected by the camera device 460. The camera device 460 may be configured to recognize one or more specific subjects, for example.

[0134] The camera device 460 may be in wired and / or wireless communication with the hardware configuration 400. In one or more scenarios, the camera device 460 may be external to the hardware configuration 400. In one or more scenarios, the camera device 460 may be internal to the hardware configuration 400.

[0135] The subject matter of this disclosure, and components thereof, can be realized by instructions that upon execution cause one or more processing devices to carry out the processes and / or functions described herein. Such instructions can, for example, comprise interpreted instructions, such as script instructions, e.g., lavaScript or ECMAScript instructions, or executable code, and / or other instructions stored in a computer readable medium.

[0136] Implementations of the subject matter and / or the functional operations described in this specification and / or the accompanying figures can be provided in digital electronic circuitry, in computer software, firmware, and / or hardware, including the structures disclosed in this specification and their structural equivalents, and / or in combinations of one or more of them. The subject matter described in this specification can be implemented as one or more computer program products, e.g., one or more modules of computer program instructions encoded on a tangible program carrier for execution by, and / or to control the operation of, data processing apparatus.

[0137] A computer program (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted languages, and / or declarative or procedural languages. It can be deployed in any form, includingas a stand-alone program or as a module, component, subroutine, and / or other unit suitable for use in a computing environment. A computer program may or might not correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs and / or data (e. ., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, and / or in multiple coordinated files (e.g., files that store one or more modules, sub programs, or portions of code). A computer program can be deployed to be executed on one computer or on multiple computers that may be located at one site or distributed across multiple sites and / or interconnected by a communication network.

[0138] The processes and / or logic flows described in this specification and / or in the accompanying figures may be performed by one or more programmable processors executing one or more computer programs to perform functions by operating on input data and / or generating output, thereby tying the process to a particular machine (e.g., a machine programmed to perform the processes described herein). The processes and / or logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) and / or an ASIC (application specific integrated circuit).

[0139] Computer readable media suitable for storing computer program instructions and / or data may include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices (e.g., EPROM, EEPROM, and / or flash memory devices); magnetic disks (e.g., internal hard disks or removable disks); magneto optical disks; and / or CD ROM and DVD ROM disks. The processor and / or the memory can be supplemented by, or incorporated in, special purpose logic circuitry.

[0140] While this specification and the accompanying figures contain many specific implementation details, these should not be construed as limitations on the scope of any invention and / or of what may be claimed, but rather as descriptions of features that may be specific to described example implementations. Certain features that are described in this specification in the context of separate implementations can also be implemented in combination in perhaps one implementation. Various features that are described in the context of perhaps one implementation can also be implemented in multiple combinations separately or in any suitable sub-combination. Although features may be described above as acting in certain combinations and / or perhaps even (e.g., initially) claimed as such, one or more features from a claimed combination can in somecases be excised from the combination. The claimed combination may be directed to a subcombination and / or variation of a sub-combination.

[0141] While operations may be depicted in the drawings in an order, this should not be understood as requiring that such operations be performed in the particular order shown and / or in sequential order, and / or that all illustrated operations be performed, to achieve useful outcomes. The described program components and / or systems can generally be integrated together in a single software product and / or packaged into multiple software products.

[0142] Examples of the subject matter described in this specification have been described. The actions recited in the claims can be performed in a different order and still achieve useful outcomes, unless expressly noted otherwise. For example, the processes depicted in the accompanying figures do not require the particular order shown, and / or sequential order, to achieve useful outcomes. Multitasking and parallel processing may be advantageous in one or more scenarios.

[0143] Non-Limiting and Combinable Examples:

[0144] Example 1 : A condition monitoring system configured to monitor one or more characteristics of one or more subjects in a delimited area. The system comprising: one or more first sensor devices disposed in one or more substantially stationary locations proximate to the delimited area. The one or more first sensor devices configured to capture a first data corresponding to the one or more subjects. The system comprising one or more second sensor devices disposed in one or more substantially non- stationary locations proximate to the delimited area. The one or more second sensor devices configured to capture a second data corresponding to the one or more subjects. The system comprising a control device.

[0145] The control device comprising a memory; a display; and at least one transceiver. The transceiver configured to communicate with the first sensor devices and the second sensor devices via at least one of: a wireless communication network, or a wired communication network. The control device comprising a processor. The processor configured at least to receive one or more first signals from the one or more first sensor devices. The one or more first signals corresponding to the first data. The processor configured to receive one or more second signals from the one or more second sensor devices. The one or more second signals corresponding to the second data. The processor configured to: process the one or more first signals to determine one or more first characteristics of the one or more subjects; process the one or more second signals to determine one or more second characteristics of the one or more subjects; process at least one of: the firstdata, or the second data, via one or more algorithms to determine one or more first secondary characteristics of the one or more subjects; and output to the display at least one of: the one or more first characteristics, the one or more second characteristics, or the one more first secondary characteristics.

[0146] Example 2: The system of example 1, further comprising: one or more nutrition distribution stations disposed in one or more locations proximate to the delimited area. The one or more nutrition stations configured to capture a third data corresponding to the one or more subjects. The system further comprising one or more sleeping surfaces and / or resting surfaces disposed in one or more locations proximate to the delimited area. The one or more sleeping surfaces configured to capture a fourth data corresponding to the one or more subjects.

[0147] The processor is further configured to: receive one or more third signals from the one or more nutrition distribution stations. The one or more third signals corresponding to the third data. The processor is further configured to receive one or more fourth signals from the one or more sleeping surfaces. The one or more fourth signals corresponding to the fourth data. The processor is further configured to process the one or more third signals to determine one or more third characteristics of the one or more subjects. The processor is further configured to process the one or more fourth signals to determine one or more fourth characteristics of the one or more subjects. The processor is further configured to process at least one of: the first data, the second data, the third data, or the fourth data via the one or more algorithms to determine one or more second secondary characteristics of the one or more subjects. The processor is further configured to output to the display at least one of: the one or more third characteristics, the one or more fourth characteristics, or the one or more second secondary characteristics.

[0148] Example 3: The system of examples 1 or 2, wherein the one or more first sensor devices comprise one or more of: one or more cameras, one or more weight sensors, one or more first proximity sensors, one or more microphones, or one or more first temperature sensors.

[0149] Example 4: The system of any of the examples 1 to 3, wherein the one or more second sensor devices comprise one or more of: one or more wearable devices. The one or more wearable devices comprising one or more of: an accelerometer, a heart rate monitor, a radio frequency identification (RFID) tracking device, breathing rate monitor, a caloric consumption sensor, a second temperature sensor, or a second proximity sensor.

[0150] Example 5: The system of any of examples 1 to 4, wherein the one or more nutritiondistribution stations comprise: one or more feeding dispensers, or one or more fluid dispensers. The system further comprising one or more waste collection containers disposed in one or more locations proximate to the delimited area. The one or more waste collection containers configured to capture a fifth data corresponding to the one or more subjects.

[0151] The processor further configured to: receive one or more fifth signals from the one or more waste collection containers. The one or more fifth signals corresponding to the fifth data. The processor further configured to process the one or more fifth signals to determine one or more fifth characteristics of the one or more subjects; process at least one of: the first data, the second data, the third data, the fourth data, or the fifth data via the one or more algorithms to determine one or more third secondary characteristics of the one or more subjects; and output to the display at least one of: the one or more fifth characteristics, or the one or more third secondary characteristics.

[0152] Example 6: The system of any of examples 1 to 5, wherein the one or more algorithms comprise one or more of: a subject group identification algorithm, an individual subject identified algorithm, a subject behavioral algorithm, or an object recognition algorithm.

[0153] Example 7: The system of any of examples 1 to 6, wherein at least some of the one or more wearable devices are in physical attachment to one or more of the subjects.

[0154] Example 8: The system of any of examples 1 to 7, wherein the one or more subjects comprise at least some animals.

[0155] Example 9: The system of example 8, wherein the at least some animals are at least one of: one or more cats, or one or more dogs.

[0156] Example 10: The system of examples 1 to 9, wherein at least one of the first data, the second data, the third data, the fourth data, or the fifth data comprise one or more of: individual subject data, interactive subject data, aggregate subject data, subject defecation data, eating data, drinking data, or subject urination data.

[0157] Example 11: The system of any of examples 1 to 10, wherein the delimited area comprises at least one of: a delimited congregate subject area, or a delimited individual subject area.

[0158] Example 12: The system of any of examples 1 to 11, wherein the delimited area is configured to contain the one or more subjects substantially within the delimited area.

[0159] Example 13: The system of any of examples 1 to 12, wherein the delimited areacomprises at least one of: an enclosed area, or an unenclosed area.

[0160] Example 14: The system of any of examples 5 to 13, wherein the processor is further configured such that at least one of: the one or more first characteristics, the one or more second characteristics, the one or more third characteristics, the one or more fourth characteristics, or the one or more fifth characteristics comprise one or more of: a temperature of one or more subjects, a heart rate of one or more subjects, a weight of one or more subjects, a location in the delimited area of one or more subjects, a fluids consumption of one or more subjects, a food consumption of one or more subjects, a resting time of one or more subjects, a sleeping time of one or more subjects, or a waste measurement of one or more subjects.

[0161] Example 15: The system of any of examples 1 to 14, wherein the control device is a first control device. The first control device comprising one or more second control devices in communication via a condition monitoring communication network.

[0162] Example 16: The system of example 15, wherein the condition monitoring communication network comprises at least one of: the wireless communication network, or the wired communication network.

[0163] Example 17: The system of any of examples 5 to 16, wherein the processor is further configured such that at least one of: the one or more first secondary characteristics, the one or more second secondary characteristics, or the one or more third secondary characteristics comprise one or more of: a behavior of one or more subjects, an identification of one or more subjects, or a posture of one or more subjects.

[0164] Example 18 : A method for monitoring one or more characteristics of one or more subjects in a delimited area via a condition monitoring communication network, the method comprising: disposing one or more first sensor devices in one or more substantially stationary locations proximate to the delimited area. The one or more first sensor devices capturing a first data corresponding to the one or more subjects. The method comprising disposing one or more second sensor devices in one or more substantially non- stationary locations proximate to the delimited area. The one or more second sensor devices capturing a second data corresponding to the one or more subjects. The method comprising communicating, via at least one transceiver, with the first sensor devices and the second sensor devices via at least one of: a wireless communication network, or a wired communication network; and receiving one or more first signals from the one or more first sensor devices. The one or more first signals corresponding to the first data.

[0165] The method comprising receiving one or more second signals from the one or more second sensor devices. The one or more second signals corresponding to the second data. The method comprising determining, via at least one processor, one or more first characteristics of the one or more subjects based on the one or more first signals; determining, via the least one processor, one or more second characteristics of the one or more subjects based on the one or more second signals; processing, via the at least one processor, at least one of: the first data, or the second data via one or more algorithms to determine one or more first secondary characteristics of the one or more subjects; and displaying, via at least one display, at least one of: the one or more first characteristics, the one or more second characteristics, or the one more first secondary characteristics.

[0166] Example 19: The method of example 18, further comprising disposing one or more nutrition distribution stations in one or more locations proximate to the delimited area. The one or more nutrition stations capturing a third data corresponding to the one or more subjects. The method further comprising disposing one or more sleeping surfaces in one or more locations proximate to the delimited area. The one or more sleeping surfaces capturing a fourth data corresponding to the one or more subjects. The method further comprising receiving one or more third signals from the one or more nutrition distribution stations. The one or more third signals corresponding to third data. The method further comprising receiving one or more fourth signals from the one or more sleeping surfaces. The one or more fourth signals corresponding to fourth data.

[0167] The method further comprising determining, via the at least one processor, one or more third characteristics of the one or more subjects based on the one or more third signals; determining, via the at least one processor, one or more fourth characteristics of the one or more subjects based on the one or more fourth signals; processing, via the at least one processor, at least one of: the first data, the second data, the third data, or the fourth data via the one or more algorithms to determine one or more second secondary characteristics of the one or more subjects; and displaying, via the at least one display, at least one of: the one or more third characteristics, the one or more fourth characteristics, or the one or more second secondary characteristics.

[0168] Example 20: The method of examples 18 or 19, wherein the one or more first sensor devices comprise one or more of: one or more cameras, one or more weight sensors, one or more first proximity sensors, one or more microphones, or one or more first temperature sensors.

[0169] Example 21 : The method of any of the examples 18 to 20, wherein the one or more second sensor devices comprise one or more of: one or more wearable devices. The one or more wearable devices comprising one or more of: an accelerometer, a heart rate monitor, a radio frequency identification (RFID) tracking device, breathing rate monitor, a caloric consumption sensor, a second temperature sensor, or a second proximity sensor.

[0170] Example 22: The method of any of examples 18 to 21, wherein the one or more nutrition distribution stations comprise: one or more feeding dispensers, or one or more fluid dispensers. The method further comprising disposing one or more waste collection containers in one or more locations proximate to the delimited area. The one or more waste collection containers capturing a fifth data corresponding to the one or more subjects. The method further comprising receiving one or more fifth signals from the one or more waste collection containers. The one or more fifth signals corresponding to the fifth data. The method further comprising determining, via the at least one processor, one or more fifth characteristics of the one or more subjects based on the one or more fifth signals; processing, via the at least one processor, at least one of: the first data, the second data, the third data, the fourth data, or the fifth data via the one or more algorithms to determine one or more third secondary characteristics of the one or more subjects; and displaying, via the at least one display, at least one of: the one or more fifth characteristics, or the one or more third secondary characteristics.

[0171] Example 23: The method of any of examples 18 to 22, wherein the one or more algorithms comprise one or more of: a subject segmentation algorithm, an individual subject identified algorithm, a subject behavioral algorithm, or a subject posture estimation algorithm.

[0172] Example 24: The method of any of examples 18 to 23, wherein at least some of the one or more wearable devices are in physical attachment to one or more of the subjects.

[0173] Example 25 : The method of any of examples 18 to 24, wherein the one or more subjects comprise at least some animals.

[0174] Example 26: The method of example 25, wherein the at least some animals are at least one of: one or more cats, or one or more dogs.

[0175] Example 27: The method of example 18 to 26, wherein at least one of the first data, the second data, the third data, the fourth data, or the fifth data comprise one or more of: individual subject data, interactive subject data, aggregate subject data, subject defecation data, eating data, drinking data, or subject urination data.

[0176] Example 28: The method of any of examples 18 to 27, wherein the delimited area comprises at least one of: a delimited congregate subject area, or a delimited individual subject area.

[0177] Example 29: The method of any of examples 18 to 28, wherein the delimited area is configured to contain the one or more subjects substantially within the delimited area.

[0178] Example 30: The method of any of examples 18 to 29, wherein the delimited area comprises at least one of: an enclosed area, or an unenclosed area.

[0179] Example 31 : The method of any of examples 22 to 30, wherein at least one of: the one or more first characteristics, the one or more second characteristics, the one or more third characteristics, the one or more fourth characteristics, or the one or more fifth characteristics comprise one or more of: a temperature of one or more subjects, a heart rate of one or more subjects, a weight of one or more subjects, a location in the delimited area of one or more subjects, a fluid consumption of one or more subjects, a food consumption of one or more subjects, a resting time of one or more subjects, a sleeping time of one or more subjects, or a waste measurement of one or more subjects.

[0180] Example 32: The method of any of examples 18 to 31, wherein the at least one processor is a first processor. The first processor being in communication with one or more second processors via the condition monitoring communication network.

[0181] Example 33: The method of example 32, wherein the condition monitoring communication network comprises at least one of: the wireless communication network, or the wired communication network.

[0182] Example 34: The method of any of examples 22 to 33, wherein at least one of: the one or more first secondary characteristics, the one or more second secondary characteristics, or the one or more third secondary characteristics comprise one or more of: a behavior of one or more subjects, an identification of one or more subjects, or a posture of one or more subjects.

[0183] While the present disclosure has been illustrated and described in detail in the drawings and foregoing description, the same is to be considered as illustrative and not restrictive in character, it being understood that only certain examples have been shown and described, and that all changes and modifications that come within the spirit of the present disclosure are desired to be protected.

Claims

CLAIMSWhat Is Claimed Is:

1. A condition monitoring system configured to monitor one or more characteristics of one or more subjects in a delimited area, the system comprising: one or more first sensor devices disposed in one or more substantially stationary locations proximate to the delimited area, the one or more first sensor devices configured to capture a first data corresponding to the one or more subjects; one or more second sensor devices disposed in one or more substantially non-stationary locations proximate to the delimited area, the one or more second sensor devices configured to capture a second data corresponding to the one or more subjects; and a control device, comprising: a memory; a display; at least one transceiver, the transceiver configured to communicate with the first sensor devices and the second sensor devices via at least one of: a wireless communication network, or a wired communication network; and a processor, the processor configured at least to: receive one or more first signals from the one or more first sensor devices, the one or more first signals corresponding to the first data; receive one or more second signals from the one or more second sensor devices, the one or more second signals corresponding to the second data; process the one or more first signals to determine one or more first characteristics of the one or more subjects; process the one or more second signals to determine one or more second characteristics of the one or more subjects; process at least one of: the first data, or the second data via one or more algorithms to determine one or more first secondary characteristics of the one or more subjects; and output to the display at least one of: the one or more first characteristics, the one or more second characteristics, or the one more first secondary characteristics.

2. The system of claim 1, further comprising: one or more nutrition distribution stations disposed in one or more locations proximate to the delimited area, the one or more nutrition stations configured to capture a third data corresponding to the one or more subjects; and one or more sleeping surfaces and / or resting surfaces disposed in one or more locations proximate to the delimited area, the one or more sleeping surfaces configured to capture a fourth data corresponding to the one or more subjects, wherein the processor is further configured to: receive one or more third signals from the one or more nutrition distribution stations, the one or more third signals corresponding to the third data; receive one or more fourth signals from the one or more sleeping surfaces, the one or more fourth signals corresponding to the fourth data; process the one or more third signals to determine one or more third characteristics of the one or more subjects; process the one or more fourth signals to determine one or more fourth characteristics of the one or more subjects; process at least one of: the first data, the second data, the third data, or the fourth data via the one or more algorithms to determine one or more second secondary characteristics of the one or more subjects; and output to the display at least one of: the one or more third characteristics, the one or more fourth characteristics, or the one or more second secondary characteristics.

3. The system of claims 1 or 2, wherein the one or more first sensor devices comprise one or more of: one or more cameras, one or more weight sensors, one or more first proximity sensors, one or more microphones, or one or more first temperature sensors.

4. The system of any of the claims 1 to 3, wherein the one or more second sensor devices comprise one or more of: one or more wearable devices, the one or more wearable devices comprising one ormore of: an accelerometer, a heart rate monitor, a radio frequency identification (RFTD) tracking device, breathing rate monitor, a caloric consumption sensor, a second temperature sensor, or a second proximity sensor.

5. The system of any of claims 1 to 4, wherein the one or more nutrition distribution stations comprise: one or more feeding dispensers, or one or more fluid dispensers, the system further comprising one or more waste collection containers disposed in one or more locations proximate to the delimited area, the one or more waste collection containers configured to capture a fifth data corresponding to the one or more subjects, the processor being further configured to: receive one or more fifth signals from the one or more waste collection containers, the one or more fifth signals corresponding to the fifth data; process the one or more fifth signals to determine one or more fifth characteristics of the one or more subjects; process at least one of: the first data, the second data, the third data, the fourth data, or the fifth data via the one or more algorithms to determine one or more third secondary characteristics of the one or more subjects; and output to the display at least one of: the one or more fifth characteristics, or the one or more third secondary characteristics.

6. The system of any of claims 1 to 5, wherein the one or more algorithms comprise one or more of: a subject group identification algorithm, an individual subject identified algorithm, a subject behavioral algorithm, or an object recognition algorithm.

7. The system of any of claims 1 to 6, wherein at least some of the one or more wearable devices are in physical attachment to one or more of the subjects.

8. The system of any of claims 1 to 7, wherein the one or more subjects comprise at least some animals.

9. The system of claim 8, wherein the at least some animals are at least one of: one or more cats, or one or more dogs.

10. The system of claims 1 to 9, wherein at least one of the first data, the second data, the third data, the fourth data, or the fifth data comprise one or more of: individual subject data, interactive subject data, aggregate subject data, subject defecation data, eating data, drinking data, or subject urination data.

11. The system of any of claims 1 to 10, wherein the delimited area comprises at least one of: a delimited congregate subject area, or a delimited individual subject area.

12. The system of any of claims 1 to 11, wherein the delimited area is configured to contain the one or more subjects substantially within the delimited area.

13. The system of any of claims 1 to 12, wherein the delimited area comprises at least one of: an enclosed area, or an unenclosed area.

14. The system of any of claims 5 to 13, wherein the processor is further configured such that at least one of: the one or more first characteristics, the one or more second characteristics, the one or more third characteristics, the one or more fourth characteristics, or the one or more fifth characteristics comprise one or more of: a temperature of one or more subjects, a heart rate of one or more subjects, a weight of one or more subjects, a location in the delimited area of one or more subjects, a fluids consumption of one or more subjects, a food consumption of one or more subjects, a resting time of one or more subjects, a sleeping time of one or more subjects, or a waste measurement of one or more subjects.

15. The system of any of claims 1 to 14, wherein the control device is a first control device, the first control device comprising one or more second control devices in communication via a condition monitoring communication network.

16. The system of claim 15, wherein the condition monitoring communication network comprises at least one of: the wireless communication network, or the wired communication network.

17. The system of any of claims 5 to 16, wherein the processor is further configured such that at least one of: the one or more first secondary characteristics, the one or more second secondary characteristics, or the one or more third secondary characteristics comprise one or more of: a behavior of one or more subjects, an identification of one or more subjects, or a posture of one or more subjects.

18. A method for monitoring one or more characteristics of one or more subjects in a delimited area via a condition monitoring communication network, the method comprising: disposing one or more first sensor devices in one or more substantially stationary locations proximate to the delimited area, the one or more first sensor devices capturing a first data corresponding to the one or more subjects; disposing one or more second sensor devices in one or more substantially non- stationary locations proximate to the delimited area, the one or more second sensor devices capturing a second data corresponding to the one or more subjects; communicating, via at least one transceiver, with the first sensor devices and the second sensor devices via at least one of: a wireless communication network, or a wired communication network; receiving one or more first signals from the one or more first sensor devices, the one or more first signals corresponding to the first data; receiving one or more second signals from the one or more second sensor devices, the one or more second signals corresponding to the second data; determining, via at least one processor, one or more first characteristics of the one or more subjects based on the one or more first signals; determining, via the least one processor, one or more second characteristics of the one or more subjects based on the one or more second signals; processing, via the at least one processor, at least one of: the first data, or the second data via one or more algorithms to determine one or more first secondary characteristics of the one or more subjects; and displaying, via at least one display, at least one of: the one or more first characteristics, the one or more second characteristics, or the one more first secondary characteristics.

19. The method of claim 18, further comprising: disposing one or more nutrition distribution stations in one or more locations proximate to the delimited area, the one or more nutrition stations capturing a third data corresponding to the one or more subjects; disposing one or more sleeping surfaces in one or more locations proximate to the delimited area, the one or more sleeping surfaces capturing a fourth data corresponding to the one or more subjects; receiving one or more third signals from the one or more nutrition distribution stations, the one or more third signals corresponding to third data; receiving one or more fourth signals from the one or more sleeping surfaces, the one or more fourth signals corresponding to fourth data; determining, via the at least one processor, one or more third characteristics of the one or more subjects based on the one or more third signals; determining, via the at least one processor, one or more fourth characteristics of the one or more subjects based on the one or more fourth signals; processing, via the at least one processor, at least one of: the first data, the second data, the third data, or the fourth data via the one or more algorithms to determine one or more second secondary characteristics of the one or more subjects; and displaying, via the at least one display, at least one of: the one or more third characteristics, the one or more fourth characteristics, or the one or more second secondary characteristics.

20. The method of claims 18 or 19, wherein the one or more first sensor devices comprise one or more of: one or more cameras, one or more weight sensors, one or more first proximity sensors, one or more microphones, or one or more first temperature sensors.

21. The method of any of the claims 18 to 20, wherein the one or more second sensor devices comprise one or more of: one or more wearable devices, the one or more wearable devices comprising one ormore of: an accelerometer, a heart rate monitor, a radio frequency identification (RFTD) tracking device, breathing rate monitor, a caloric consumption sensor, a second temperature sensor, or a second proximity sensor.

22. The method of any of claims 18 to 21, wherein the one or more nutrition distribution stations comprise: one or more feeding dispensers, or one or more fluid dispensers, the method further comprising: disposing one or more waste collection containers in one or more locations proximate to the delimited area, the one or more waste collection containers capturing a fifth data corresponding to the one or more subjects; receiving one or more fifth signals from the one or more waste collection containers, the one or more fifth signals corresponding to the fifth data; determining, via the at least one processor, one or more fifth characteristics of the one or more subjects based on the one or more fifth signals; processing, via the at least one processor, at least one of: the first data, the second data, the third data, the fourth data, or the fifth data via the one or more algorithms to determine one or more third secondary characteristics of the one or more subjects; and displaying, via the at least one display, at least one of: the one or more fifth characteristics, or the one or more third secondary characteristics.

23. The method of any of claims 18 to 22, wherein the one or more algorithms comprise one or more of: a subject segmentation algorithm, an individual subject identified algorithm, a subject behavioral algorithm, or a subject posture estimation algorithm.

24. The method of any of claims 18 to 23, wherein at least some of the one or more wearable devices are in physical attachment to one or more of the subjects.

25. The method of any of claims 18 to 24, wherein the one or more subjects comprise at least some animals.

26. The method of claim 25, wherein the at least some animals are at least one of: one or morecats, or one or more dogs.

27. The method of claims 18 to 26, wherein at least one of the first data, the second data, the third data, the fourth data, or the fifth data comprise one or more of: individual subject data, interactive subject data, aggregate subject data, subject defecation data, eating data, drinking data, or subject urination data.

28. The method of any of claims 18 to 27, wherein the delimited area comprises at least one of: a delimited congregate subject area, or a delimited individual subject area.

29. The method of any of claims 18 to 28, wherein the delimited area is configured to contain the one or more subjects substantially within the delimited area.

30. The method of any of claims 18 to 29, wherein the delimited area comprises at least one of: an enclosed area, or an unenclosed area.

31. The method of any of claims 22 to 30, wherein at least one of: the one or more first characteristics, the one or more second characteristics, the one or more third characteristics, the one or more fourth characteristics, or the one or more fifth characteristics comprise one or more of: a temperature of one or more subjects, a heart rate of one or more subjects, a weight of one or more subjects, a location in the delimited area of one or more subjects, a fluid consumption of one or more subjects, a food consumption of one or more subjects, a resting time of one or more subjects, a sleeping time of one or more subjects, or a waste measurement of one or more subjects.

32. The method of any of claims 18 to 31 , wherein the at least one processor is a first processor, the first processor being in communication with one or more second processors via the condition monitoring communication network.

33. The method of claim 32, wherein the condition monitoring communication network comprises at least one of: the wireless communication network, or the wired communication network.

34. The method of any of claims 22 to 33, wherein at least one of: the one or more first secondary characteristics, the one or more second secondary characteristics, or the one or more third secondary characteristics comprise one or more of: a behavior of one or more subjects, an identification of one or more subjects, or a posture of one or more subjects.

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