Smart environment for condition monitoring of one or more subjects within defined area

Abstract

Techniques are disclosed for a condition monitoring system configured to monitor one or more characteristics of one or more subjects in a defined area. The first sensor device is disposed at one or more substantially fixed locations proximate the defined area. One or more first sensor devices capture first data corresponding to one or more subjects. The second sensor device is disposed in one or more substantially non-fixed locations proximate the defined area. A second sensor device captures second data corresponding to one or more subjects. The control device receives and processes signals corresponding to the first data and / or the second data to determine a first feature, a second feature, and / or a first secondary feature of the one or more subjects. The first feature, the second feature, and / or the first secondary feature are output for display and / or further processing.

Description

[0001] Cross-references to related applications

[0002] 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 herein by reference for all purposes. Background Technology

[0003] Subjects, such as animals, may suffer from a number of health problems, such as anxiety, dermatitis, and / or allergies. Collecting physical parameters from animals for the diagnosis and treatment of these conditions can be difficult and, in some respects, relatively expensive for pet owners and / or other animal owners / managers.

[0004] Animals, such as pets, may exhibit behaviors and other symptoms related to their individual health conditions. Pets may exhibit certain behaviors related to their individual health conditions when in a closed / isolated environment (such as a home environment). In some cases, pets may exhibit certain additional and / or different behaviors when in a group environment with other animals / pets. Summary of the Invention

[0005] A technique for a condition monitoring system is disclosed, which can be configured to monitor one or more characteristics of one or more subjects within a defined 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 can be positioned at one or more substantially fixed locations (e.g., mounted on a normally immovable object, wired connection, etc.) close to (e.g., inside, or within thirty feet of the defined area). The one or more first sensor devices can be configured to capture first data corresponding to one or more subjects.

[0006] One or more second sensor devices may be positioned at one or more substantially non-fixed locations near the defined area (e.g., mounted or attached to a typically movable / mobile object / subject, wireless connection, etc.). The one or more second sensor devices may be configured to capture second data corresponding to one or more subjects.

[0007] The control device may include a memory, a display, and / or a transceiver. The transceiver may be configured to communicate with the first sensor device and / or the second sensor device via a wireless communication network and / or a wired communication network.

[0008] The control device may include a processor. The processor may be configured to receive one or more first signals from one or more first sensor devices. The one or more first signals may correspond to first data. The processor may also be configured to receive one or more second signals from one or more second sensor devices. The one or more second signals may correspond to second data.

[0009] The processor can be configured to process one or more first signals to determine one or more first characteristics of one or more subjects. The processor can be configured to process one or more second signals to determine one or more second characteristics of one or more subjects.

[0010] The processor can be configured to process first and / or second data via one or more algorithms to determine one or more primary features of one or more subjects.

[0011] The processor can be configured to output one or more first features, one or more second features, and / or one or more first features to a display.

[0012] In one or more cases, one or more nutrition distribution stations may be located near one or more defined areas. One or more nutrition stations may be configured to capture third data corresponding to one or more subjects.

[0013] One or more sleep surfaces may be positioned at one or more locations near the defined area. One or more sleep surfaces may be configured to capture fourth data corresponding to one or more subjects.

[0014] The processor can be configured to receive one or more third signals from one or more nutrient distribution stations. These one or more third signals may correspond to third data. The processor can also be configured to receive one or more fourth signals from one or more sleep surfaces. These one or more fourth signals may correspond to fourth data.

[0015] The processor can be configured to process one or more third signals to determine one or more third features of one or more subjects. The processor can be configured to process one or more fourth signals to determine one or more fourth features of one or more subjects. The processor can be configured to process first, second, third, and / or fourth data via one or more algorithms to determine one or more secondary features of one or more subjects.

[0016] The processor can be configured to output one or more third features, one or more fourth features, and / or one or more second features to the display.

[0017] In one or more cases, one or more first sensor devices may include 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.

[0018] In one or more cases, one or more second sensor devices may include one or more wearable devices. One or more wearable devices may include an accelerometer, a heart rate monitor, a radio frequency identification (RFID) tracking device, a respiratory rate monitor, a calorie consumption sensor, a second temperature sensor, a gyroscope, a magnetometer, a thermometer, one or more optical sensors, devices with Wi-Fi, Bluetooth, LAN, cellular, satellite, sub-GHz radio, low-power wide-area network (LPWAN) communication, low-power mesh network communication protocols (such as Zigbee), and / or a second proximity sensor.

[0019] In one or more cases, one or more nutrition distribution stations may include one or more feeding dispensers and / or one or more fluid dispensers (e.g., water, milk, rehydration fluid, etc.). The system may also include one or more waste collection containers, which may be located at one or more sites near the defined area. The one or more waste collection containers may be configured to capture fifth data corresponding to one or more subjects.

[0020] The processor can be configured to receive one or more fifth signals from one or more waste collection containers. The one or more fifth signals may correspond to fifth data. The processor can be configured to process the one or more fifth signals to determine one or more fifth characteristics of one or more subjects. The processor can be configured to process first data, second data, third data, fourth data, and / or fifth data via one or more algorithms to determine one or more third key characteristics of one or more subjects.

[0021] The processor can be configured to output one or more fifth features and / or one or more third features to the display.

[0022] In one or more cases, one or more algorithms may include subject segmentation algorithms, individual subject identification algorithms, subject behavior algorithms, and / or subject posture estimation algorithms.

[0023] In one or more scenarios, at least some of the one or more wearable devices may be physically attached to one or more subjects. The one or more subjects may include at least some animals. The at least some animals may be one or more cats and / or one or more dogs.

[0024] In one or more cases, at least one of the first data, second data, third data, fourth data and / or fifth data may include individual subject data, interactive subject data, aggregated subject data, subject defecation data, food date, water intake data and / or subject urination data.

[0025] In one or more cases, the defined region may include a defined area for aggregated subjects and / or a defined area for individual subjects. The defined region may be configured to substantially include one or more subjects within it. The defined region may include a closed region and / or a non-closed region.

[0026] In one or more cases, the processor may also be configured such that at least one of one or more first features, one or more second features, one or more third features, one or more fourth features, and / or one or more fifth features may include the temperature of one or more subjects, the heart rate of one or more subjects, the weight of one or more subjects, the location of one or more subjects in the defined area, the fluid consumption (e.g., water, milk, rehydrated fluid, etc.) of one or more subjects, the food consumption of one or more subjects, the resting time of one or more subjects, the sleep time of one or more subjects, and / or the waste measurement (e.g., solid waste, liquid waste, vomit discharge, hairball discharge, etc.) of one or more subjects.

[0027] In one or more cases, the control device may be a first control device. The first control device may include one or more second control devices communicating via a condition monitoring communication network. The condition monitoring communication network may include a wireless communication network and / or a wired communication network.

[0028] In one or more cases, the processor may also be configured such that at least one of one or more primary features, one or more secondary features, and / or one or more tertiary features may include the behavior of one or more subjects, the identification of one or more subjects, and / or the posture of one or more subjects. Attached Figure Description

[0029] The elements and other features, advantages, and disclosures contained herein, as well as the ways in which they are implemented, will become apparent from the following description of various examples of this disclosure taken in conjunction with the accompanying drawings, and the disclosure will be better understood, wherein:

[0030] Figure 1 This 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) and other devices.

[0031] Figure 2 This is an example illustration of a defined area where test dogs can be grouped together, fed separately, and / or kept in captivity for sleep / rest periods.

[0032] Figure 3A and Figure 3B This is an example flowchart of at least one technique for capturing data corresponding to one or more subjects in a condition monitoring system.

[0033] Figure 4 It is an example device that can control one or more parts of a condition monitoring system / communication network (such as...) Figure 1 A block diagram of the hardware configuration of a CMCD device.

[0034] Figure 5 This is an example illustration of a defined area where test dogs can be gathered and / or kept in captivity for sleep / rest periods.

[0035] Figure 6 This is an example illustration of a defined area where the test cats can gather, receive nutrition, and / or be confined for sleep / rest periods.

[0036] Figure 7 An example of an accelerometer signal from a wearable device placed on a subject within a defined area is shown.

[0037] Figure 8 This is an example illustration of one or more algorithms that process accelerometer signals to determine the motion / behavior of one or more subjects.

[0038] Figure 9 An example illustration depicts a technique for analyzing subject food changes that can utilize various aspects of sensor data from a defined area.

[0039] Figure 10 An example depicting the characteristics of an accelerometer signal from a wearable device placed on a subject within a defined area.

[0040] Figure 11 This is an example of a wearable sensor attached to a feline subject within a defined area.

[0041] Figure 12 An example illustration depicts canine subjects moving from an internal gathering space to an isolated space within a defined area.

[0042] Figure 13 Examples of canine subjects are depicted in the internal gathering and isolation spaces within a defined area.

[0043] Figure 14This is an example illustration of canine subjects eating in a defined, isolated space.

[0044] Figure 15 An example illustration depicts canine subjects in one or more external gathering spaces within a defined area.

[0045] Figure 16 This is an example illustration of canine subjects resting in a defined, isolated space.

[0046] Figure 17 This is an example illustration of a monitoring dashboard that provides visualization of one or more sensors and analytical techniques utilizing various sensor data from a defined area.

[0047] Figure 18 This is an example illustration of a monitoring dashboard that provides visualization of one or more sensors and analytical techniques utilizing various sensor data from a defined area.

[0048] Figure 19 This is an example illustration of a monitoring dashboard that provides visualization of one or more sensors and analytical techniques utilizing various sensor data from a defined area.

[0049] Figure 20 This is an example illustration of a monitoring dashboard that provides visualization of one or more camera sensors from external, internal, and internal isolated spaces within a defined area. Detailed Implementation

[0050] To facilitate understanding of the principles of this disclosure, reference will now be made to the examples shown in the accompanying drawings, which will be described using specific language. However, it should be understood that this is not intended to limit the scope of this disclosure.

[0051] Figure 1 This is a block diagram illustrating an example Condition Monitoring Communication System Network (CMCSN) 100 operable to monitor and / or control one or more parts of a Condition Monitoring System (CMS). Digital and / or analog control signals, electronic content, one or more of various input signals and / or various output signals, as well as other condition monitoring system information, can be communicated from / across / within the Condition Monitoring Communication System Network 100. One or more of discrete and / or continuous control schemes, techniques, and / or algorithms can be processed / executed by / across / from the Condition Monitoring Communication System Network 100.

[0052] Electronic content can 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, e-commerce, video components / elements of electronic content and / or audio components / elements of electronic content, and other types of electronic content. Electronic content can include tagging behavior generated by applying one or more machine learning (ML) models to accelerometer data, gyroscope data, still image and / or video data, manual annotation of data, metadata, firmware version, animal identification and / or camera number, etc.

[0053] In one or more cases, CMCSN devices 110a-d send / receive signals and / or communicate and / or may receive data services from a wide area network (WAN) 120 via a connection to a Condition Monitoring Communication Network (CMCN) 130. One or more nodes of the Condition Monitoring Communication Network 130 and / or WAN 120 may communicate with one or more cloud-based nodes (not shown) via the Internet 124. The test animal may (e.g., directly) interact with the video display device (such as 140a, 140b, 140c, or 140d), such as by touching the device with its nose, paws, or body, and / or simply by looking at it. This may involve turning the video on / off, changing channels, starting or stopping audio players and / or microphone recording devices, distributing food, displaying toys, and generating positive feedback such as petting and / or praise.

[0054] CMCN devices may include, for example, modem 110a, process control device / logic controller 110b, wireless router or media gateway 110d including embedded modem 110c, and many other devices (e.g., Digital Subscriber Line (DSL) modem, Voice over Internet Protocol (VoIP) terminal adapter, video game console, Digital Multifunction Disc (DVD) player, communication equipment, hotspot device, etc.). For example, communication monitoring communication network 130 may be a hybrid fiber-coaxial cable (HFC) network, local area network (LAN), wireless local area network (WLAN), cellular network and / or personal area network (PAN), and other networks. As used herein, condition monitoring control device (CMCD) may be any of devices 110a-110d and / or 140a-140i, internet gateway, router device, set-top box (STB), process control device / logic controller, smart media device (SMD), cloud computing device, any type of CMCD, and / or any other suitable device (e.g., wired and / or wireless) that can be configured to perform one or more of the technologies and / or functions disclosed herein.

[0055] A CMCD device can facilitate communication between WAN 120 and devices 140a-140i. A cable modem or embedded MTA (eMTA) 110a can facilitate communication between WAN 120 and computer 140a. A process control device / logic controller 110b can facilitate communication between WAN 120 and television / monitor / display 140b (e.g., media presentation device, graphical user interface, process control interface, etc.) and / or digital video recorder (DVR). A wireless router 110c can facilitate communication between computer 140c and WAN 120.

[0056] Media gateway 110d facilitates communication between mobile devices 140d (e.g., tablet computing devices, smartphones, personal digital assistant (PDA) devices, laptop computing devices, etc.; one or more devices based on PC, iOS, Linux, Unix-like, and / or Android, etc.) and WAN 120. One or more speaker devices (e.g., sound radiating devices / systems) 140e can communicate with condition monitoring communication network 130, process control devices / logic controllers 110b, and / or televisions / monitors / displays 140b, etc. For example, camera devices 140g, 140h, and / or 140i can communicate with computer 140a, televisions / monitors / displays 140b, computer 140c, and / or condition monitoring communication network 130, as well as other devices and networks.

[0057] One or more speaker devices 140e (e.g., surround sound speakers, home theater speakers, other external wired / wireless speakers, amplifiers, full-range drivers, subwoofers, woofers, mid-range drivers, tweeters, coaxial drivers, etc.) can broadcast at least one audio component of electronic content / media content, as well as other audio signals, processes, and / or applications. One or more speaker devices 140e may have the ability to radiate sound in a pre-configured acoustic / physical pattern (e.g., cone pattern, directional pattern, etc.). For example, a process control equipment / logic controller condition monitoring audible alarm can communicate via one or more of the speaker devices 140e.

[0058] One or more microphone devices 140f can be external / standalone microphone devices. One or more microphone devices 140f can communicate with a communication monitoring network 130, a process control device / logic controller 110b, a television / monitor / display 140b, a computer 140a, a computer 140c, a mobile device 140a, etc. Any of devices 110a-110d and / or devices 140a-140i may include internal microphone devices. One or more speaker devices 140e (e.g., “speakers”) and / or one or more microphone devices 140f (e.g., “microphones”, which may be “high-quality” devices such as far-field microphones, noise-canceling microphones, shotgun microphones, dynamic microphones, ribbon microphones and / or diaphragm microphones of various sizes, Bluetooth™-based remote / control devices, RF4CE-based remote / control devices, etc.) may have wired and / or wireless connections (e.g., Bluetooth, Wi-Fi, proprietary protocol communication networks, etc.) to any other devices 140a-140i, condition monitoring communication network 130, WAN 120 and / or Internet 124.

[0059] Camera devices 140g-140i can provide digital video input / output capabilities for devices 110a-110d and / or one or more of devices 140a-140d. Camera devices 140g-140i can communicate with any of devices 110a-110d and / or devices 140a-140f, for example, via wired and / or wireless connections. One or more of camera devices 140g-140i can capture digital images, digital video streams, and / or can scan various types of images, such as Universal Product Code (UPC) codes and / or Quick Response (QR) codes, and other images. One or more of camera devices 140g-140i can provide video input / output (e.g., can be used as a network camera, etc.), for example, for video surveillance and other video functions.

[0060] Any of the camera devices 140g-140i may include a microphone device and / or a speaker device. The input / output of any of the camera devices 140g-140i may include audio signals / data packets / components, which may be, for example, separate / separable from, or in some (e.g., separable) combination with the video signals / data packets / components of any of the camera devices 140g / 100i.

[0061] One or more of the camera devices 140g-140i can detect the presence of one or more subjects and / or objects that may be near the camera device 140g-140i and / or may be in the same general space (e.g., the same room, the same space, the same room and the same defined area, etc.) as the camera device 140g-140i. One or more of the camera devices 140g-140i can measure the general activity level (e.g., high activity, moderate activity, and / or low activity) of one or more subjects that can be detected by the camera device 140g-140i. One or more of the camera devices 140g-140i can detect one or more general characteristics (e.g., height, body shape, skin color, pulse, heart rate, respiratory count, object size, object volume, object mass, etc.) of one or more subjects detected by the camera device 140g-140i. For example, one or more of the camera devices 140g-140i can be configured to identify one or more specific subjects. One or more of the camera devices 140g-140i can 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 and / or gaze toward another subject or object).

[0062] One or more of the camera devices 140g-140i can use wireless communication with any of the devices 110a-110d and / or 140a-140d, such as Bluetooth™ and / or Wi-Fi™, and other wireless communication protocols. One or more of the camera devices 140g-140i can be external to any of the devices 110a-110d and / or 140a-140d. One or more of the camera devices 140g-140i can be internal to any of the devices 110a-110d and / or 140a-140d.

[0063] One or more of the camera devices 140g-140i can be (e.g., industrial and / or commercial and / or residential) vision camera devices. The vision camera can be a Gigabit Ethernet compatible device (e.g., 10GbE Ethernet, etc.). The vision camera can operate in black and white and / or color. The vision camera can have a capacity of at least 8.8 megapixels, etc. The vision camera can have a resolution of 4096 x 2160 pixels, etc. For example, the vision camera can be a camera (e.g., a Baumer-manufactured VLXT-90C.ILX series, or similar / equivalent or other devices mentioned herein) capable of capturing product images in various forms, such as digital still image frames and / or video streams, possibly from, for example, ninety-five (95) frames per second (fps). The vision camera can have one or more parameters that can be configured remotely and / or locally.

[0064] CMCD devices, such as process control devices / logic controller devices, media gateway devices, etc., can support visual and / or voice interfaces with users, viewers, and / or operators of the condition monitoring communication network. This interface can support intelligent enhancements to the user / viewer / operator experience, for example, in a condition monitoring network environment, or in any network environment. One or more traditional and / or current viewer experiences can be enriched to leverage the visual and / or voice interface, potentially, for example, deriving intelligent actions and / or results.

[0065] In one or more cases, any of devices 110a-110d, 140a-140i, and other devices may be used to implement any of the capabilities, techniques, methods, and / or devices described herein.

[0066] The WAN network 120 and / or the condition monitoring communication network 130 can 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 (Internet), etc. Therefore, the WAN network 120 and / or the condition monitoring communication network 130 may include one or more communication-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.

[0067] This document describes a subject's living / delimited area, where the subject may be an animal, such as a canine or feline. The defined area may incorporate technologies to stream most of the subject's daytime and / or nighttime content, perhaps every segment. One or more cameras may be pointed at / focused on one or more different spaces within the area, an isolated sleeping enclosure, and / or the subject's feeder, elimination areas (such as litter boxes), and / or other areas of interest (such as outdoor spaces, toys), etc. The defined area may include microphones, proximity sensors, smart subject beds, and other sensors and / or smart technologies. One or more wearable devices may be attached to one or more subjects, and these wearable devices may include one or more sensors.

[0068] The connected ecosystem, such as the defined area, can be a canine / dog smart room and / or a feline / cat smart room, which may include various sensor patterns. The defined area / smart room may have technologies that can learn as much as possible about the health of the subject / pet. Wearable devices (e.g., collars), proximity sensors, and cameras (e.g., those mounted on the walls / ceiling of the smart room), microphones, and / or other smart devices / sensors can provide data for understanding the subject's emotional state, social interactions, and / or behavioral patterns. Sensors within and / or around the smart room can capture data corresponding to most / every part of the subject's day, such as eating, drinking, playing, running, napping, and / or sleeping, as well as other subject activities. This data can be used to determine one or more characteristics corresponding to one or more subjects. This data can support the enabling / development of one or more algorithms and / or can quantify subject behavioral patterns. Data collected in the room can provide an on-site / real-time monitoring / recording system for use by the subject's caregiver. Any cameras described herein can be placed in substantially fixed locations and / or substantially mobile environments (e.g., on mobile devices, etc.). Any camera described herein, regardless of its placement, can be controlled (e.g., locally and / or remotely) to pan, zoom, tilt, focus, etc. Any camera described herein, regardless of its placement, can be a black-and-white, color, infrared, or other type of camera.

[0069] Subjects within a defined area / smart room can be grouped and / or move freely indoors and / or outdoors as desired. Subjects are free to behave and / or can socially interact with other subjects and / or non-subjects (e.g., humans and / or other animals) in ways impossible in isolated subject accommodations. The smart room can track subject behavior to understand subject movement and / or social interactions, and / or can link this information / data to connected devices set up, developed, prototyped, and / or tested within the smart room, as well as a subject health database. This data can enable device and / or algorithm development to track early indicators of disease and / or changes in subject health status (e.g., detection of subclinical and clinical indicators), and / or track behavior changes over time. The smart room can collect room, sleep fence camera data, feeder camera data, audio data, weight data, and location data, as well as other sensor data, via RFID tracking. The fence can be used for sleep, rest, eating, drinking, sample collection, medical procedures, mandatory isolation, etc.

[0070] Collar-style wearable devices can capture valuable information about a subject's / pet's behavior through head and / or neck movements. They can measure other behaviors such as location in the room, distance from other subjects / animals, proximity to feeders and / or sleeping surfaces / beds, information about eating, drinking, urinating, defecating, pet weight, etc., and may benefit from an interconnected ecosystem embedded with various smart technologies / sensors to stream / record data over daily / weekly / yearly periods. Information about individual subjects / pets and groups of subjects / pets can be tracked / studied / observed over time to identify changes. This data may be correlated with other subject / pet health information.

[0071] One or more algorithms may help interpret sensor data from smart rooms / defined areas. For example, one or more algorithms can be deployed to infer / interpret subject / animal behavior. For instance, a dog / cat / subject segmentation algorithm could allow for the isolation of subject / dog / cat images from arbitrary settings. Individual recognition algorithms could allow for continuous monitoring of designated individuals / subjects in a group living environment. Behavior recognition algorithms could allow for the identification of time periods containing data on the behavior of subjects of interest. Pose estimation algorithms could provide pose information that can supplement behavior recognition, etc.

[0072] For example, if the bed sensor detects that the dog's weight has increased or decreased compared to its typical weight, a camera can be used to determine if the dog is only partially on the bed, if there are multiple dogs on the bed, if the dog has brought toys to the bed, and / or if the dog is alone on the bed (in which case the dog may have gained or lost weight). This allows owners to better interpret the weight data and, if useful, manage the dog's food intake and exercise to support optimal weight.

[0073] For example, if the sensors detect that the dog's walking is different from usual, the bed sensor can be used to see if the dog is gaining weight. This allows the owner to manage the dog's food intake and / or exercise to support an optimal weight, and / or seek veterinary advice as needed.

[0074] For example, if the sensor detects little or no movement, a temperature sensor can be used to determine if a dog has a fever / is sick. This allows the owner to recognize early signs of illness and / or seek appropriate care for their pet.

[0075] For example, if bed sensors indicate poor sleep in a dog, the bed sensors (e.g., weight and / or proximity sensors, cameras, etc.) can be used to determine if the dog spent a lot of time resting and / or sleeping the following day. This information (e.g., poor sleep followed by sleep / rest) can allow the owner to better manage the day's activities and / or plans.

[0076] For example, if bed sensors or other sensors detect that the dog is restless / not sleeping well at night, one or more microphones can be used to determine if the dog is howling / whining (e.g., indicating anxiety) and / or if there are environmental sounds causing the dog to sleep poorly (e.g., thunder or traffic noise). There may be various solutions to these problems. For example, if the dog is anxious, behavioral programs and / or medication may be helpful. For example, if there is environmental noise like traffic, moving the dog's bed and / or soundproofing may be helpful.

[0077] Defined areas / smart rooms can include smart cat apartments for feline communities and / or complete smart pet rooms for canine communities (e.g., puppies). An example smart cat apartment could include individual rooms with 15 cat apartments, such as... Figure 6As shown. One or more, or each apartment, may include a nutrition scale (e.g., a water / fluid and / or food scale), a litter box scale, one or more cameras that can be aligned / focused on the scale, food and / or water / fluid bowls, waste collection stations, etc. Cats may wear wearable devices. For example, a smart pet room for canines may include multiple partitions / spaces to accommodate up to sixteen dogs and an additional number of other dogs. The smart room may use room and fence cameras, feeder scales, feeder cameras, wearable devices, and / or other sensors capable of measuring most / every aspect of a subject's / pet's day, while collecting data regularly and / or continuously during the day / night. Metrics related to the location and / or social behavior of the subject / pet can be determined from the data generated by the smart room. Video data may be collected corresponding events, such as feeding and / or spontaneous events (e.g., "butt mopping"), as well as other subject events. These metrics derived from this information and / or video may be displayed in a dashboard format, such as in Figure 16 , Figure 17 , Figure 19 and / or Figure 20 middle.

[0078] Without the capabilities, techniques, methods, systems, and / or devices described herein, those skilled in the art would not understand how to determine various characteristics corresponding to multiple subjects within a defined area. This disclosure provides those skilled in the art with the capability, systems, devices, methods, and / or techniques for deploying various sensors in internal / external aggregated spaces and / or external / internal isolated spaces within a defined area. This disclosure also provides those skilled in the art with the capability, systems, devices, methods, and / or techniques for collecting signals from various sensors and determining one or more characteristics corresponding to subjects within a defined area based on those sensor signals. Such capabilities, systems, devices, methods, and / or techniques can be used for these purposes, as well as others, such as providing data for multivariate analysis techniques to determine / estimate subject behavior and / or health, and other subject characteristics.

[0079] Figure 2 This is an example illustration of a smart room / defined area 202, in which test dogs (not shown) can be gathered together, separated for feeding and watering, and / or confined for sleep / resting periods, feces collection, urine collection, and / or medical / health assessments. Figure 2In this context, the defined area 202 may include one or more sleep fences 206, 208. The defined area 202 may include one or more feeding fences 210. The defined area may include one or more observation posts 218. The defined area 202 may include one or more gathering spaces 212, 214. The defined area 202 may include one or more cameras 216 (e.g., which may be the same as or similar to other cameras disclosed herein). The defined area 202 may include one or more other sensors (not shown), such as microphones, proximity sensors, wearable sensors, and other sensors. Any sensor in the defined area 202 may be configured to transmit wired and / or wirelessly via the condition monitoring communication network 130.

[0080] Figure 5 This is an example illustration of a defined area 502, in which test dogs (not shown) may gather and / or be confined for sleep / resting periods. Defined area 502 may include at least one gathering space 512 and / or one or more isolated sleep enclosures 514. Defined area 502 may include one or more cameras 508. Defined area 502 may include one or more other sensors (not shown), such as microphones, proximity sensors, wearable sensors, and other sensors. Any sensor in defined area 502 may be configured to transmit wired and / or wirelessly via a situation monitoring communication network 130.

[0081] Figure 6 This is an example illustration of a defined area 602 (e.g., a "cat apartment") where one or more test cats (not shown) may gather, receive nutrition, and / or be confined for sleep / rest periods, fecal collection, urine collection, and / or medical / health assessments. Defined area 602 may include one or more cameras 604 (e.g., focused on a general area, litter box, nutrition dispensing station, etc.). Defined area 602 may include a food dispensing station 608 and / or a fluid (e.g., water, milk, rehydrated fluid, etc.) dispensing station 610. Defined area 602 may include a waste collection station 606 and / or a sleeping surface 612. Defined area 602 may include one or more other sensors (not shown), such as microphones, proximity sensors, cameras, wearable sensors, and other sensors. Any sensors in defined area 602 may be configured to transmit wired and / or wirelessly via a condition monitoring communication network 130.

[0082] Figure 7An example accelerometer and corresponding signal 702 are shown, which can be placed in a wearable device on a subject within a defined area (not shown). Accelerometer 706 can be placed on a cat and / or dog collar (not shown). Feature 708 can correspond to wired and / or wireless signals from accelerometer 706. Accelerometer 707 can be at least one of one or more types of accelerometers. Accelerometer 706 can be configured to transmit wired and / or wirelessly via situation monitoring communication network 130.

[0083] Figure 8 This is an example illustration 802 of one or more algorithms / neural networks 804 that process accelerometer signals 806 (e.g., triaxial accelerometer data) to determine the motion / behavior (e.g., characteristics) 808 of one or more subjects. In one or more cases, a random forest algorithm (not shown), as well as other types of algorithms, may be used. Besides... Figure 8 In addition to, or instead of, the behavior shown Figure 8 The behavior shown can be used to label other types of behavior.

[0084] Different analytical techniques can utilize different aspects of various sensor data from a defined area. One or more different analytical methods utilize different characteristics of the data. Some analytical methods may rely on generalization measures to make inferences. Other analytical methods may use more detail in the data and / or may be designed to describe patterns, with or without inference. Other methods may use detail in the data to create data features and / or examine patterns in these data features, with or without inference. In one or more cases, a combination of these methods may be used.

[0085] Figure 9Example illustration 1002 depicts a subject food change analysis technique utilizing different aspects of data from various sensors from a defined area (not shown). Sensor 1008 (e.g., a wearable accelerometer) can capture data corresponding to the consumption of a dog's usual food 1012. Sensor 1008 can capture data corresponding to the dog's consumption of a new food 1014. One or more algorithms can process the data from sensor 1008 (and / or other sensor data not shown) to determine the dog's behavior under both usual and new food consumption. This processing can provide some insight into whether the dog's behavior is abnormal. This processing can provide some insight into whether the behavioral change meets a minimum threshold (e.g., a health threshold, an activity threshold, etc.). For example, this processing can provide insight into whether a set of behaviors characterizing dermatitis or other health conditions has changed. More generally, one or more of the sensors described herein can be used to understand (e.g., typical) behavioral patterns and / or changes in behavioral patterns, perhaps after the introduction of changes such as food, medication, treatment, etc. Changes in food, medication, and / or treatment, etc., before and / or after introduction, can be compared to understand the effects of the changes and other causes.

[0086] Figure 10 A diagram 1402 depicts the characteristics of an accelerometer signal 1404 in a wearable device (not shown) placed on a test cat 1406 within a defined area (not shown). For example, analysis of the accelerometer signal 1404 can be interpreted as being "scratched" by the test cat 1406.

[0087] Figure 11 Example illustration 1602 shows wearable sensors 1604 and 1606 attached to feline subjects 1610 and 1612 in a defined area (not shown).

[0088] Figure 12 An illustrative diagram depicts a canine subject 1704 moving from an internal gathering space 1708 to an isolation space 1710 (e.g., a feeding enclosure) within a defined area 1702. The defined area 1702 may include one or more other sensors (not shown), such as microphones, proximity sensors, wearable sensors, and other sensors. Any sensor in the defined area 1702 may be configured to transmit wired and / or wirelessly via a condition monitoring communication network 130.

[0089] Figure 13An example illustration depicts a canine subject 1804 within an internal gathering space 1806 and one or more isolation spaces 1808 in a defined area 1802. The defined area 1802 may include one or more other sensors (not shown), such as microphones, proximity sensors, wearable sensors, and other sensors. Any sensor in the defined area 1802 may be configured to transmit wired and / or wirelessly via a situation monitoring communication network 130.

[0090] Figure 14 This is an example illustration of a canine subject 1904 feeding from a food dispensing station 1906 (e.g., a nutrient station) within an isolated space of a defined area 1902. The defined area 1902 may include one or more other sensors (not shown), such as microphones, proximity sensors, wearable sensors, and other sensors. Any sensor in the defined area 1902 may be configured to transmit wired and / or wirelessly via a condition monitoring communication network 130.

[0091] Figure 15 An example illustration depicts a canine subject 2004 within one or more external gathering spaces 2006, 2008 in a defined area 2002. The defined area 2002 may include one or more other sensors (not shown), such as microphones, proximity sensors, wearable sensors, and other sensors. Any sensor in the defined area 2002 may be configured to transmit wired and / or wirelessly via a situation monitoring communication network 130.

[0092] Figure 16 This is an example illustration of a canine subject 2104 resting and / or sleeping in an isolation space 2106 within a defined area 2102. The isolation space 2106 may include a food dispensing station 2108 and / or a fluid (e.g., water, milk, rehydrated fluid, etc.) dispensing station 2110, which may be configured to communicate wirelessly or via wired communication. The defined area 2102 may include one or more other sensors (not shown), such as microphones, proximity sensors, wearable sensors, and other sensors. Any sensors in the defined area 2102 may be configured to transmit wired and / or wirelessly via a condition monitoring communication network 130.

[0093] Figure 17 This is an example illustration of a monitoring dashboard 2202, which can provide visualization of one or more sensors and analytical techniques utilizing various sensor data from a defined area.

[0094] Figure 18 This is an example illustration of a monitoring dashboard 2302, which can provide visualization of one or more sensors and analytical techniques utilizing various sensor data from a defined area.

[0095] Figure 19 This is an example illustration of a monitoring dashboard 2402, which can provide visualizations of one or more sensors and analytical techniques utilizing data from various sensors within a defined area. Video can help track the location of the test dogs, where each dog can be tracked using digital and / or identification lines to determine where the dogs are, how long they stay there, and where they go next. It can also understand how the dogs socialize, such as positive and / or negative social interactions within the group. This can allow for a relationship diagram similar to the one on the right side of dashboard 2402. For example, by integrating video, microphone, and / or wearable device data, it can also see when exciting things might happen in the smart room and / or use room metrics to measure these events.

[0096] Figure 20 This is an example illustration of a monitoring dashboard 2502, which can provide visualization of one or more camera sensors from external gathering spaces, internal gathering spaces, and internal isolation spaces within a defined area.

[0097] In one or more cases, one or more of the accelerometers may be commercially available wearable accelerometers. In one or more cases, one or more cameras may be, for example, a commercially available YI 1080P home camera and other cameras. In one or more cases, the scale may be, for example, a commercially available scale and / or a custom / modified scale and other scales.

[0098] Reference Figure 1 , Figure 2 and Figures 5 to 20 It is understood that this document discloses techniques for use in condition monitoring systems. A condition monitoring system can be configured to monitor one or more characteristics of one or more subjects in a defined area (e.g., a smart room). One or more devices can be implemented within the system, and / or one or more methods / techniques corresponding to the system can be implemented. One or more first sensor devices can be positioned at one or more substantially fixed locations (e.g., mounted on normally immovable objects, wired connections, etc.) close to (e.g., inside or within thirty feet of the defined area). One or more first sensor devices can be configured to capture first data corresponding to one or more subjects.

[0099] One or more second sensor devices may be positioned at one or more substantially non-fixed locations near the defined area (e.g., mounted or attached to a typically movable / mobile object / subject, wireless connection, etc.). The one or more second sensor devices may be configured to capture second data corresponding to one or more subjects.

[0100] The control device may include a memory, a display, and / or a transceiver. The transceiver may be configured to communicate with the first sensor device and / or the second sensor device via a wireless communication network and / or a wired communication network.

[0101] The control device may include a processor. The processor may be configured to receive one or more first signals from one or more first sensor devices. The one or more first signals may correspond to first data. The processor may also be configured to receive one or more second signals from one or more second sensor devices. The one or more second signals may correspond to second data.

[0102] The processor can be configured to process one or more first signals to determine one or more first characteristics of one or more subjects. The processor can be configured to process one or more second signals to determine one or more second characteristics of one or more subjects.

[0103] The processor can be configured to process first and / or second data via one or more algorithms to determine one or more primary features of one or more subjects.

[0104] The processor can be configured to output one or more first features, one or more second features, and / or one or more first features to the display (e.g., Figure 17 and / or Figure 18 (The dashboard).

[0105] In one or more scenarios, one or more nutrition dispensing stations may be located near one or more defined areas. One or more nutrition stations may be configured to capture third data corresponding to one or more subjects. The one or more nutrition dispensing stations may include scales, weighing sensors, flow meters, etc., and may be configured for wired and / or wireless communication to, for example, transmit signals in real time and / or at different time intervals, indicating how much nutrition a subject can consume, the frequency of nutrient consumption, and / or the type of nutrition.

[0106] One or more sleep / resting surfaces may be positioned at one or more locations near the defined area. One or more sleep surfaces may be configured to capture fourth data corresponding to one or more subjects. One or more sleep surfaces may include a scale, weighing sensor, etc., which may be configured for wired and / or wireless communication to, for example, transmit signals in real time and / or at different time intervals, indicating how much rest / sleep the subject can obtain, the frequency of obtaining rest / sleep, and / or the type of rest / sleep.

[0107] The processor can be configured to receive one or more third signals from one or more nutrient distribution stations. These one or more third signals may correspond to third data. The processor can also be configured to receive one or more fourth signals from one or more sleep surfaces. These one or more fourth signals may correspond to fourth data.

[0108] The processor can be configured to process one or more third signals to determine one or more third features of one or more subjects. The processor can be configured to process one or more fourth signals to determine one or more fourth features of one or more subjects. The processor can be configured to process first, second, third, and / or fourth data via one or more algorithms to determine one or more secondary features of one or more subjects.

[0109] The processor can be configured to output one or more third features, one or more fourth features, and / or one or more second features to the display (e.g., Figure 17 and / or Figure 18 (The dashboard).

[0110] In one or more cases, the one or more first sensor devices may include 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.

[0111] In one or more cases, the one or more second sensor devices may include one or more wearable devices. The one or more wearable devices may include an accelerometer, a heart rate monitor, a radio frequency identification (RFID) tracking device, a respiratory rate monitor, a calorie consumption sensor, a second temperature sensor, and / or a second proximity sensor.

[0112] In one or more cases, one or more nutrition distribution stations may include one or more feeding dispensers and / or one or more fluid dispensers (e.g., water, milk, rehydration fluid, etc.). The system may also include one or more waste collection containers, which may be positioned at one or more locations near a defined area. The one or more waste collection containers may be configured to capture fifth data corresponding to one or more subjects. The one or more waste collection containers may include scales, weighing sensors, etc., which may be configured for wired and / or wireless communication to signal in real time and / or at different time intervals how much waste effluent a subject can excrete, the frequency of waste effluent excretion, and / or the type of waste effluent.

[0113] The processor can be configured to receive one or more fifth signals from one or more waste collection containers. The one or more fifth signals may correspond to fifth data. The processor can be configured to process the one or more fifth signals to determine one or more fifth characteristics of one or more subjects. The processor can be configured to process first data, second data, third data, fourth data, and / or fifth data via one or more algorithms to determine one or more third key characteristics of one or more subjects.

[0114] The processor can be configured to output one or more fifth features and / or one or more third features to the display.

[0115] In one or more cases, one or more algorithms may include algorithms that can identify and / or measure objects and / or subjects.

[0116] In one or more of these cases, at least some of the wearable devices may be physically connected to one or more subjects. The one or more subjects may include at least some animals. The at least some animals may be one or more cats and / or one or more dogs.

[0117] In one or more cases, at least one of the first data, second data, third data, fourth data and / or fifth data may include individual subject data, interactive subject data, aggregated subject data, subject defecation data, food intake data, water intake data and / or subject urination data.

[0118] In one or more cases, the defined region may include a defined area for aggregated subjects and / or a defined area for individual subjects. The defined region may be configured to substantially encompass one or more subjects within it. The defined region may include a closed region and / or a non-closed region.

[0119] In one or more cases, the processor may also be configured such that at least one of one or more first features, one or more second features, one or more third features, one or more fourth features, and / or one or more fifth features may include the temperature of one or more subjects, the heart rate of one or more subjects, the weight of one or more subjects, the location of one or more subjects in the defined area, the fluid consumption (e.g., water, milk, rehydrated fluid, etc.) of one or more subjects, the food consumption of one or more subjects, the resting time of one or more subjects, the sleep time of one or more subjects, and / or the waste measurement (e.g., solid waste, liquid waste, vomit discharge, hairball discharge, etc.) of one or more subjects.

[0120] In one or more cases, the control device may be a first control device. The first control device may include one or more second control devices communicating via a condition monitoring communication network. The condition monitoring communication network may include a wireless communication network and / or a wired communication network. For example, the condition monitoring communication network may be condition monitoring communication network 130.

[0121] In one or more cases, the processor may also be configured such that at least one of one or more primary features, one or more secondary features, and / or one or more tertiary features may include the behavior of one or more subjects, the identification of one or more subjects, and / or the posture of one or more subjects.

[0122] In one or more cases, the processor may be configured to generate one or more alarms and / or alerts based on any of the features and / or signals described herein (e.g., for display on a dashboard and / or alarm panel, etc.).

[0123] Referring now to Figure 3, Figure 300 illustrates an example technique for monitoring one or more characteristics of one or more subjects within a defined area via a situation monitoring communication network. This method can be performed by a situation monitoring control device (CMCD) and other devices. For example, the situation monitoring control device can be a process control device / logic controller 110b, as well as other devices 110a-110d and / or 140a-140i, and / or cloud computing devices. The situation monitoring control device (CMCD) can communicate with any device in the situation monitoring communication system network (CMCSN) 100. At 302, the process can be started or restarted.

[0124] At point 304, the condition monitoring and control device positions one or more first sensor devices at one or more substantially fixed locations near the defined area. The one or more first sensor devices can capture first data corresponding to one or more subjects. At point 306, the condition monitoring and control device can position one or more second sensor devices at one or more substantially non-fixed locations near the defined area. The one or more second sensor devices can capture second data corresponding to one or more subjects.

[0125] At point 308, the condition monitoring and control device can receive one or more first signals from one or more first sensor devices. The one or more first signals may correspond to first data. At point 310, the condition monitoring and control device can receive one or more second signals from one or more second sensor devices. The one or more second signals may correspond to second data.

[0126] At 312, the condition monitoring and control device may determine (e.g., via at least one processor) one or more first characteristics of one or more subjects based on one or more first signals. At 314, the condition monitoring and control device may determine (e.g., via at least one processor) one or more second characteristics of one or more subjects based on one or more second signals.

[0127] At point 316, the condition monitoring and control device may process (e.g., via at least one processor) at least one of the first or second data via one or more algorithms to determine one or more primary characteristics of one or more subjects. At point 318, the condition monitoring and control device may display (e.g., via at least one display) at least one of the following: one or more primary characteristics, one or more second characteristics, and / or one or more primary characteristics. At point 320, the process may be stopped or restarted.

[0128] Figure 4 This is a block diagram of the hardware configuration of an example device that can be used as a process control device / logic controller, such as... Figure 1 The status monitoring and control device 110b, as well as other devices such as any of 140a-140i and devices 110a-110d, are included. Hardware configuration 400 is operable to facilitate the delivery of information from an internal server of the device. Hardware configuration 400 may include processor 410, memory 420, storage device 430, and / or input / output device 440. For example, one or more of components 410, 420, 430, and 440 may be interconnected using system bus 450. Processor 410 (e.g., CPU, GPU, etc.) can process instructions for execution within hardware configuration 400. Processor 410 may be a single-threaded and / or single-core processor, or processor 410 may be a multi-threaded and / or multi-core processor. Processor 410 is capable of processing instructions stored in memory 420 and / or storage device 430.

[0129] Memory 420 may store information within hardware configuration 400. Memory 420 may be a computer-readable medium (CRM), such as a non-transitory CRM. Memory 420 may be a volatile memory cell and / or a non-volatile memory cell.

[0130] Storage device 430 provides high-capacity storage for hardware configuration 400. Storage device 430 may be a computer-readable medium (CRM), such as a non-transitory CRM. Storage device 430 may include, for example, a hard disk drive, an optical disk drive, flash memory, and / or some other high-capacity storage device. Storage device 430 may be an external device to hardware configuration 400.

[0131] Input / output device 440 can provide input / output operations for hardware configuration 400. Input / output device 440 (e.g., a transceiver device) may include one or more of the following: network interface device (e.g., an Ethernet card), serial communication device (e.g., an RS-232 port), one or more Universal Serial Bus (USB) interfaces (e.g., USB 2.0 / 3.0 ports), and / or wireless interface devices (e.g., an 802.11 card). The input / output device may include a driver device configured to output to one or more networks (e.g., Figure 1 The status monitoring communication network 130 sends and / or receives communications from it. Input / output device 400 can communicate with one or more input / output modules (not shown), which may be located close to and / or far from the hardware configuration 400. One or more output modules may provide input / output functionality in digital signal form, discrete signal form, TTL form, analog signal form, serial communication protocol, fieldbus protocol communication, and / or other open or proprietary communication protocols.

[0132] Camera device 460 can provide digital video input / output capabilities to hardware configuration 400. Camera device 460 can communicate with any component of hardware configuration 400, for example, via system bus 450. Camera device 460 can capture digital images and / or can scan various types of images, such as Universal Product Code (UPC) codes and / or Quick Response (QR) codes, as well as other images described herein. In one or more cases, camera device 460 can be identical and / or substantially similar to any other camera device described herein.

[0133] Camera device 460 may include at least one microphone device and / or at least one speaker device (not shown). The input / output of camera device 460 may include audio signals / data packets / components, which may be separate / separable from or in some (e.g., separable) combination with video signals / data packets / components in camera device 460.

[0134] Camera device 460 can also detect the presence of one or more subjects who may be near camera device 460 and / or who may be in the same general space as camera device 460 (e.g., the same room, defined area, etc.). Camera device 460 can measure the general activity level (e.g., high activity, moderate activity, and / or low activity) of one or more subjects that camera device 460 can detect. Camera device 460 can detect one or more general characteristics (e.g., height, body shape, skin color, pulse, hair, hair type / thickness, heart rate, respiratory count, weight, gait parameters, etc.) of one or more subjects detected by camera device 460. For example, camera device 460 can be configured to identify one or more specific subjects.

[0135] Camera device 460 can communicate wirelessly with hardware configuration 400. In one or more cases, camera device 460 can be external to hardware configuration 400. In one or more cases, camera device 460 can be internal to hardware configuration 400.

[0136] The subject matter and components of this disclosure may be implemented by instructions that, when executed, cause one or more processing devices to perform the processes and / or functions described herein. For example, such instructions may include interpreted instructions, such as scripting instructions, such as JavaScript or ECMAScript instructions, or executable code, and / or other instructions stored in a computer-readable medium.

[0137] Embodiments of the subject matter and / or functional operation described in this specification and / or the accompanying drawings may be provided in digital electronic circuits, computer software, firmware, and / or hardware, including the structures disclosed in this specification and their structural equivalents, and / or combinations of one or more of them. The subject matter described in this specification may be implemented as one or more computer program products, for example, one or more modules of computer program instructions encoded on a tangible program carrier for execution by a data processing apparatus and / or control of the operation of the data processing apparatus.

[0138] Computer programs (also known as programs, software, software applications, scripts, or code) can be written in any form of programming language, including compiled or interpreted languages, and / or declarative or procedural languages. They can be deployed in any form, including as standalone programs or as modules, components, subroutines, and / or other units suitable for use in a computing environment. A computer program may or may not correspond to a file in a file system. A program may be stored as a part of a file containing other programs and / or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, and / or in multiple coordination files (e.g., files storing one or more modules, subroutines, or code sections). A computer program can be deployed to be executed on one or more computers, which may be located at a single site or distributed across multiple sites, and / or interconnected via a communication network.

[0139] The processes and / or logic flows described in this specification and / or the accompanying drawings can be executed by one or more programmable processors that perform functions by manipulating input data and / or generating outputs, thereby associating the process with a specific machine (e.g., a machine programmed to perform the processes described herein). The processes and / or logic flows can also be executed by special-purpose logic circuitry, and the apparatus can also be implemented as special-purpose logic circuitry, such as FPGAs (Field-Programmable Gate Arrays) and / or ASICs (Application-Specific Integrated Circuits).

[0140] Computer-readable media suitable for storing computer program instructions and / or data can include all forms of non-volatile memory, media, and storage devices, including, for example, semiconductor memory devices (e.g., EPROM, EEPROM, and / or flash memory devices); magnetic disks (e.g., internal hard disks or removable hard disks); magneto-optical disks; and / or CD-ROMs and DVD-ROMs. The processor and / or memory may be supplemented by or incorporated into dedicated logic circuitry.

[0141] While this specification and accompanying drawings contain numerous specific implementation details, these details should not be construed as limiting any invention and / or the scope of any possible claims, but rather as descriptions of features that may be relevant to the described exemplary embodiments. Certain features described herein may also be implemented in combination in one possible embodiment within the context of individual embodiments. Various features described in one possible embodiment may also be implemented individually in multiple combinations or in any suitable sub-combination. Although the foregoing features may be described as functioning in certain combinations and / or possibly even (e.g., initially) so claimed, in some cases, one or more features from said combinations may be removed from the combination. Claimed combinations may involve sub-combinations and / or variations of sub-combinations.

[0142] Although operations may be depicted sequentially in the accompanying drawings, this should not be construed as requiring these operations to be performed in the specific order and / or sequence shown, and / or performing all of the shown operations to achieve a useful result. The described program components and / or systems may typically be integrated together in a single software product and / or packaged into multiple software products.

[0143] Examples of the subject matter described in this specification have been described. Unless otherwise expressly stated, the actions pursuant to the claims may be performed in a different order and may still achieve useful results. For example, the processes depicted in the figures do not require the specific order and / or sequence shown to achieve useful results. In one or more cases, multitasking and parallel processing may be advantageous.

[0144] Non-restrictive and composable examples:

[0145] Example 1: A condition monitoring system configured to monitor one or more characteristics of one or more subjects within a defined area. The system includes: one or more first sensor devices disposed at one or more substantially fixed locations near the defined area. The one or more first sensor devices are configured to capture first data corresponding to the one or more subjects. The system includes one or more second sensor devices disposed at one or more substantially non-fixed locations near the defined area. The one or more second sensor devices are configured to capture second data corresponding to the one or more subjects. The system includes a control device.

[0146] The control device includes a memory; a display; and at least one transceiver. The transceiver is configured to communicate with a first sensor device and a second sensor device via at least one of a wireless communication network or a wired communication network. The control device includes a processor. The processor is configured to receive one or more first signals from at least one or more first sensor devices. The one or more first signals correspond to first data. The processor is configured to receive one or more second signals from one or more second sensor devices. The one or more second signals correspond to second data. The processor is configured to: process the one or more first signals to determine one or more first features of one or more subjects; process the one or more second signals to determine one or more second features of one or more subjects; process at least one of the first data or second data via one or more algorithms to determine one or more primary features of one or more subjects; and output one or more first features, one or more second features, or at least one of one or more primary features to the display.

[0147] Example 2: The system of Example 1 further includes: one or more nutrition distribution stations disposed at one or more locations near the defined area. The one or more nutrition stations are configured to capture third data corresponding to one or more subjects. The system also includes one or more sleep surfaces and / or resting surfaces disposed at one or more locations near the defined area. The one or more sleep surfaces are configured to capture fourth data corresponding to one or more subjects.

[0148] The processor is also configured to receive one or more third signals from one or more nutrient distribution stations. The one or more third signals correspond to third data. The processor is also configured to receive one or more fourth signals from one or more sleep surfaces. The one or more fourth signals correspond to fourth data. The processor is further configured to process the one or more third signals to determine one or more third characteristics of one or more subjects. The processor is also configured to process the one or more fourth signals to determine one or more fourth characteristics of one or more subjects. The processor is further configured to process at least one of the first data, second data, third data, or fourth data via one or more algorithms to determine one or more secondary primary characteristics of one or more subjects. The processor is further configured to output at least one of the one or more third characteristics, one or more fourth characteristics, or one or more secondary primary characteristics to a display.

[0149] Example 3: The system of Example 1 or 2, wherein one or more first sensor devices include one or more of the following: 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.

[0150] Example 4: A system of any one of Examples 1 to 3, wherein one or more second sensor devices include one or more of the following: one or more wearable devices. The one or more wearable devices include one or more of an accelerometer, a heart rate monitor, a radio frequency identification (RFID) tracking device, a respiratory rate monitor, a calorie consumption sensor, a second temperature sensor, or a second proximity sensor.

[0151] Example 5: A system of any one of Examples 1 to 4, wherein one or more nutrition distribution stations include: one or more feed dispensers, or one or more fluid dispensers. The system also includes one or more waste collection containers disposed at one or more locations near a defined area. The one or more waste collection containers are configured to capture fifth data corresponding to one or more subjects.

[0152] The processor is also configured to: receive one or more fifth signals from one or more waste collection containers. The one or more fifth signals correspond to fifth data. The processor is also configured to process the one or more fifth signals to determine one or more fifth features of one or more subjects; process at least one of first data, second data, third data, fourth data, or fifth data via one or more algorithms to determine one or more third key features of one or more subjects; and output one or more fifth features or at least one of one or more third key features to a display.

[0153] Example 6: A system of any one of Examples 1 to 5, wherein one or more algorithms include one or more of the following algorithms: subject group identification algorithm, individual subject identification algorithm, subject behavior algorithm, or object identification algorithm.

[0154] Example 7: A system of any one of Examples 1 to 6, wherein at least some of one or more wearable devices are physically attached to one or more subjects.

[0155] Example 8: A system of any one of Examples 1 to 7, wherein one or more subjects include at least some animals.

[0156] Example 9: The system of Example 8, wherein at least some of the animals are at least one of the following: one or more cats, or one or more dogs.

[0157] Example 10: The systems of Examples 1 to 9, wherein at least one of the first data, second data, third data, fourth data, or fifth data includes one or more of the following: individual subject data, interactive subject data, aggregated subject data, subject defecation data, food intake data, water intake data, or subject urination data.

[0158] Example 11: A system of any one of Examples 1 to 10, wherein the defined region includes at least one of a defined region of aggregated subjects or a defined region of individual subjects.

[0159] Example 12: A system of any one of Examples 1 to 11, wherein the delimitation region is configured to substantially include one or more subjects within the delimitation region.

[0160] Example 13: A system of any one of Examples 1 to 12, wherein the defined region includes at least one of a closed region or a non-closed region.

[0161] Example 14: A system of any one of Examples 5 to 13, wherein the processor is further configured such that at least one of one or more first features, one or more second features, one or more third features, one or more fourth features, or one or more fifth features includes one or more of the following: temperature of one or more subjects, heart rate of one or more subjects, weight of one or more subjects, location of one or more subjects in a defined area, fluid consumption of one or more subjects, food consumption of one or more subjects, resting time of one or more subjects, sleep time of one or more subjects, or waste measurement of one or more subjects.

[0162] Example 15: A system of any one of Examples 1 to 14, wherein the control device is a first control device. The first control device includes one or more second control devices that communicate via a condition monitoring communication network.

[0163] Example 16: The system of Example 15, wherein the condition monitoring communication network includes at least one of a wireless communication network or a wired communication network.

[0164] Example 17: A system of any one of Examples 5 to 16, wherein the processor is further configured such that at least one of one or more primary features, one or more secondary features, or one or more tertiary features includes one or more of the following: the behavior of one or more subjects, the identification of one or more subjects, and / or the posture of one or more subjects.

[0165] Example 18: A method for monitoring one or more characteristics of one or more subjects within a defined area via a situation monitoring communication network, the method comprising: positioning one or more first sensor devices at one or more substantially fixed locations near the defined area; the one or more first sensor devices capturing first data corresponding to the one or more subjects; the method comprising positioning one or more second sensor devices at one or more substantially non-fixed locations near the defined area; the one or more second sensor devices capturing second data corresponding to the one or more subjects; the method comprising communicating with the first sensor devices and the second sensor devices via at least one transceiver 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 correspond to the first data.

[0166] The method includes receiving one or more second signals from one or more second sensor devices. The one or more second signals correspond to second data. The method includes determining one or more first features of one or more subjects via at least one processor based on one or more first signals; determining one or more second features of one or more subjects via at least one processor based on one or more second signals; processing at least one of the first data or second data via at least one processor and one or more algorithms to determine one or more primary features of one or more subjects; and displaying at least one of the one or more first features, one or more second features, or one or more primary features via at least one display.

[0167] Example 19: The method of Example 18 further includes setting one or more nutrient distribution stations at one or more locations near the defined area. The one or more nutrient stations capture third data corresponding to one or more subjects. The method further includes setting one or more sleep surfaces at one or more locations near the defined area. The one or more sleep surfaces capture fourth data corresponding to one or more subjects. The method further includes receiving one or more third signals from the one or more nutrient distribution stations. The one or more third signals correspond to third data. The method further includes receiving one or more fourth signals from the one or more sleep surfaces. The one or more fourth signals correspond to fourth data.

[0168] The method further includes determining one or more third features of one or more subjects via at least one processor based on one or more third signals; determining one or more fourth features of one or more subjects via at least one processor based on one or more fourth signals; processing at least one of first data, second data, third data, or fourth data via at least one processor and one or more algorithms to determine one or more secondary features of one or more subjects; and displaying at least one of one or more third features, one or more fourth features, or one or more secondary features via at least one display.

[0169] Example 20: The method of Example 18 or 19, wherein one or more first sensor devices include one or more of the following: 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.

[0170] Example 21: A method of any one of Examples 18 to 20, wherein one or more second sensor devices include one or more of the following: one or more wearable devices. The one or more wearable devices include one or more of an accelerometer, a heart rate monitor, a radio frequency identification (RFID) tracking device, a respiratory rate monitor, a calorie consumption sensor, a second temperature sensor, or a second proximity sensor.

[0171] Example 22: A method of any one of Examples 18 to 21, wherein one or more nutrition dispensing stations include: one or more feeding dispensers, or one or more fluid dispensers. The method further includes placing one or more waste collection containers at one or more locations near a defined area. The one or more waste collection containers capture fifth data corresponding to one or more subjects. The method further includes receiving one or more fifth signals from the one or more waste collection containers. The one or more fifth signals correspond to the fifth data. The method further includes determining one or more fifth features of one or more subjects based on the one or more fifth signals via at least one processor; processing at least one of the first data, second data, third data, fourth data, or fifth data via at least one processor and via one or more algorithms to determine one or more third primary features of one or more subjects; and displaying at least one of the one or more fifth features or one or more third primary features via at least one display.

[0172] Example 23: A method of any one of Examples 18 to 22, wherein one or more algorithms include one or more of the following: subject segmentation algorithm, individual subject identification algorithm, subject behavior algorithm, or subject pose estimation algorithm.

[0173] Example 24: A method of any one of Examples 18 to 23, wherein at least some of one or more wearable devices are physically attached to one or more subjects.

[0174] Example 25: The method of any one of Examples 18 to 24, wherein one or more subjects include at least some animals.

[0175] Example 26: The method of Example 25, wherein at least some of the animals are at least one of the following: one or more cats, or one or more dogs.

[0176] Example 27: The methods of Examples 18 to 26, wherein at least one of the first data, second data, third data, fourth data or fifth data includes one or more of the following: individual subject data, interactive subject data, aggregated subject data, subject defecation data, food intake data, water intake data or subject urination data.

[0177] Example 28: A method of any one of Examples 18 to 27, wherein the defined region includes at least one of a defined region of aggregated subjects or a defined region of individual subjects.

[0178] Example 29: A method of any of Examples 18 to 28, wherein the delimited region is configured to substantially include one or more subjects within the delimited region.

[0179] Example 30: A method of any one of Examples 18 to 29, wherein the defined region includes at least one of a closed region or a non-closed region.

[0180] Example 31: The method of any one of Examples 22 to 30, wherein at least one of one or more first features, one or more second features, one or more third features, one or more fourth features, or one or more fifth features includes one or more of the following: temperature of one or more subjects, heart rate of one or more subjects, weight of one or more subjects, location of one or more subjects in the defined area, fluid consumption of one or more subjects, food consumption of one or more subjects, resting time of one or more subjects, sleep time of one or more subjects, or waste measurement of one or more subjects.

[0181] Example 32: A method of any one of Examples 18 to 31, wherein at least one processor is a first processor. The first processor communicates with one or more second processors via a condition monitoring communication network.

[0182] Example 33: The method of Example 32, wherein the condition monitoring communication network includes at least one of a wireless communication network or a wired communication network.

[0183] Example 34: A method of any one of Examples 22 to 33, wherein at least one of one or more primary features, one or more secondary features, or one or more tertiary features includes one or more of the following: behavior of one or more subjects, identification of one or more subjects, or posture of one or more subjects.

[0184] Although this disclosure has been shown and described in detail in the accompanying drawings and the foregoing description, it should be regarded as illustrative rather than restrictive. It should be understood that only certain examples have been shown and described, and it is intended that all variations and modifications within the spirit and scope of this disclosure be protected.

Claims

1. A condition monitoring system configured to monitor one or more characteristics of one or more subjects within a defined area, the system comprising: One or more first sensor devices are disposed at one or more substantially fixed locations near the defined area, the one or more first sensor devices being configured to capture first data corresponding to the one or more subjects; One or more second sensor devices are disposed at one or more substantially non-fixed locations near the defined area, the one or more second sensor devices being configured to capture second data corresponding to the one or more subjects; as well as Control equipment, including: Memory; monitor; At least one transceiver configured to communicate with the first sensor device and the second sensor device via at least one of a wireless communication network or a wired communication network; and Processor, the processor being configured to at least: 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; Processing at least one of the first data or the second data via one or more algorithms to determine one or more primary characteristics of the one or more subjects; and Output at least one of the one or more first features, the one or more second features, or the one or more first features to the display.

2. The system according to claim 1, further comprising: One or more nutrition distribution stations are located at one or more locations near the defined area, and the one or more nutrition stations are configured to capture third data corresponding to the one or more subjects; as well as One or more sleep surfaces and / or resting surfaces are disposed at one or more locations near the defined area, the one or more sleep surfaces being configured to capture 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 nutrient distribution stations, the one or more third signals corresponding to the third data; Receive one or more fourth signals from the one or more sleep 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; Processing 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 secondary key features of the one or more subjects; and Output at least one of the one or more third features, the one or more fourth features, or the one or more second features to the display.

3. The system according to claim 1 or 2, wherein, The one or more first sensor devices include one or more of the following: 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 according to any one of claims 1 to 3, wherein, The one or more second sensor devices include one or more of the following: One or more wearable devices, the one or more of which include an accelerometer, a heart rate monitor, a radio frequency identification (RFID) tracking device, a respiratory rate monitor, a calorie consumption sensor, a second temperature sensor, or a second proximity sensor.

5. The system according to any one of claims 1 to 4, wherein, The one or more nutrition dispensing stations include: one or more feed dispensers or one or more fluid dispensers; the system also includes one or more waste collection containers disposed at one or more locations near the defined area, the one or more waste collection containers being configured to capture fifth data corresponding to the one or more subjects; the processor is 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; Processing at least one of the first data, second data, third data, fourth data, or fifth data via the one or more algorithms to determine one or more third-order key features of the one or more subjects; and Output to the display at least one of the one or more fifth features or the one or more third features.

6. The system according to any one of claims 1 to 5, wherein, The one or more algorithms include one or more of the following: subject group identification algorithm, individual subject identification algorithm, subject behavior algorithm, or object identification algorithm.

7. The system according to any one of claims 1 to 6, wherein, At least some of the one or more wearable devices are physically attached to one or more of the subjects.

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

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

10. The system according to 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 includes one or more of the following: individual subject data, interactive subject data, aggregated subject data, subject defecation data, food intake data, water intake data, or subject urination data.

11. The system according to any one of claims 1 to 10, wherein, The defined region includes at least one of a defined region of aggregated subjects or a defined region of individual subjects.

12. The system according to any one of claims 1 to 11, wherein, The defined region is configured to substantially include the one or more subjects within the defined region.

13. The system according to any one of claims 1 to 12, wherein, The defined area includes at least one of a closed area or a non-closed area.

14. The system according to any one of claims 5 to 13, wherein, The processor is further configured such that at least one of the one or more first features, the one or more second features, the one or more third features, the one or more fourth features, or the one or more fifth features includes one or more of the following: temperature of one or more subjects, heart rate of one or more subjects, weight of one or more subjects, location of one or more subjects in the defined area, fluid consumption of one or more subjects, food consumption of one or more subjects, resting time of one or more subjects, sleep time of one or more subjects, or waste measurement of one or more subjects.

15. The system according to any one of claims 1 to 14, wherein, The control device is a first control device, which includes one or more second control devices that communicate via a condition monitoring communication network.

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

17. The system according to any one of claims 5 to 16, wherein, The processor is further configured such that at least one of the one or more primary features, the one or more secondary features, or the one or more tertiary features includes one or more of the following: the behavior of one or more subjects, the identification of one or more subjects, or the posture of one or more subjects.

18. A method for monitoring one or more characteristics of one or more subjects in a defined area via a situation monitoring communication network, the method comprising: One or more first sensor devices are positioned at one or more substantially fixed locations near the defined area, and the one or more first sensor devices capture first data corresponding to the one or more subjects; One or more second sensor devices are positioned at one or more substantially non-fixed locations near the defined area, and the one or more second sensor devices capture second data corresponding to the one or more subjects; Communicating with the first sensor device and the second sensor device via at least one of a wireless communication network or a wired communication network, and via at least one transceiver; 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; Based on the one or more first signals, one or more first characteristics of the one or more subjects are determined via at least one processor; Based on the one or more second signals, one or more second characteristics of the one or more subjects are determined via the at least one processor; The first data or the second data is processed via the at least one processor and via one or more algorithms to determine one or more primary features of the one or more subjects; as well as The first feature, the second feature, or at least one of the first features is displayed via at least one display.

19. The method of claim 18, further comprising: One or more nutrition distribution stations are set up at one or more locations near the defined area, and the one or more nutrition stations capture third data corresponding to the one or more subjects; One or more sleep surfaces are disposed at one or more locations near the defined area, and the one or more sleep surfaces capture fourth data corresponding to the one or more subjects; Receive one or more third signals from the one or more nutrient distribution stations, the one or more third signals corresponding to third data; Receive one or more fourth signals from the one or more sleep surfaces, the one or more fourth signals corresponding to fourth data; Based on the one or more third signals, one or more third characteristics of the one or more subjects are determined via the at least one processor; Based on the one or more fourth signals, one or more fourth characteristics of the one or more subjects are determined via the at least one processor; The first data, the second data, the third data, or the fourth data are processed via the at least one processor and via the one or more algorithms to determine one or more secondary key features of the one or more subjects; as well as The at least one of the one or more third features, the one or more fourth features, or the one or more second features is displayed via the at least one display.

20. The method according to claim 18 or 19, wherein, The one or more first sensor devices include one or more of the following: 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 according to any one of claims 18 to 20, wherein, The one or more second sensor devices include one or more of the following: One or more wearable devices, the one or more of which include an accelerometer, a heart rate monitor, a radio frequency identification (RFID) tracking device, a respiratory rate monitor, a calorie consumption sensor, a second temperature sensor, or a second proximity sensor.

22. The method according to any one of claims 18 to 21, wherein, The one or more nutrient dispensing stations include: one or more feed dispensers, or one or more fluid dispensers, and the method further includes: One or more waste collection containers are placed at one or more locations near the defined area, and the one or more waste collection containers capture fifth data corresponding to the one or more subjects; 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; Based on the one or more fifth signals, one or more fifth characteristics of the one or more subjects are determined via the at least one processor; Processing at least one of the first data, the second data, the third data, the fourth data, or the fifth data via the at least one processor and via the one or more algorithms to determine one or more third-order key features of the one or more subjects; and The at least one of the one or more fifth features or the one or more third features is displayed via the at least one display.

23. The method according to any one of claims 18 to 22, wherein, The one or more algorithms include one or more of the following: subject segmentation algorithm, individual subject identification algorithm, subject behavior algorithm, or subject posture estimation algorithm.

24. The method according to any one of claims 18 to 23, wherein, At least some of the one or more wearable devices are physically attached to one or more of the subjects.

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

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

27. The method according to 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 includes one or more of the following: individual subject data, interactive subject data, aggregated subject data, subject defecation data, food intake data, water intake data, or subject urination data.

28. The method according to any one of claims 18 to 27, wherein, The defined region includes at least one of a defined region of aggregated subjects or a defined region of individual subjects.

29. The method according to any one of claims 18 to 28, wherein, The defined region is configured to substantially include the one or more subjects within the defined region.

30. The method according to any one of claims 18 to 29, wherein, The defined area includes at least one of a closed area or a non-closed area.

31. The method according to any one of claims 22 to 30, wherein, At least one of the one or more first features, the one or more second features, the one or more third features, the one or more fourth features, or the one or more fifth features includes one or more of the following: temperature of one or more subjects, heart rate of one or more subjects, weight of one or more subjects, location of one or more subjects in the defined area, fluid consumption of one or more subjects, food consumption of one or more subjects, resting time of one or more subjects, sleep time of one or more subjects, or waste measurement of one or more subjects.

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

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

34. The method according to any one of claims 22 to 33, wherein, The one or more primary features, the one or more secondary features, or at least one of the one or more tertiary features include one or more of the following: the behavior of one or more subjects, the identification of one or more subjects, or the posture of one or more subjects.

Images