Method and system for detecting and identifying an animal based on weight

Abstract

A method for identifying an animal using a pet health device including a) monitoring for a presence of the animal at the one or more pet health devices by one or more sensing devices; b) detecting the presence of the animal at the one or more pet health devices by the one or more sensing devices; c) recording a weight of the animal as detected by the one or more sensing devices, wherein the one or more sensing devices include one or more mass sensors, and the weight once recorded is a recorded weight; d) detecting a departure of the animal from the one or more pet health devices by the one or more sensing devices; and e) automatically identifying the animal by automatically associating the recorded weight with an identify of the animal by matching the recorded weight with a substantially similar weight associated with an animal profile.

Description

METHOD AND SYSTEM FOR DETECTING AND IDENTIFYING AN ANIMAL BASED ON WEIGHTCROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims priority from U.S. Provisional Application No. 63 / 517,729, filed on August 4, 2023, which is incorporated herein by reference in its entirety.FIELD

[0002] The disclosure relates to a method and system for detecting and identifying an animal based on weight. The disclosure may be advantageous in identifying which animal is using a pet health device in a multi-animal household. The disclosure may be advantageous in detecting the presence of a specific animal at a litter device, feeder, waterer, and / or the like. The disclosure may be particularly advantageous in identifying an animal based on weight. The disclosure may be beneficial in tracking behavior, trends, or both of a specific animal based on weight.BACKGROUND

[0003] Automated pet health devices targeted to filling the needs of domestic animals and their owners often include a number of onboard sensors. These sensors are advantageous in monitoring performance of the device itself; monitoring usage of the device by an animal; and aiding in determining generally precise usage or consumption by an animal. For example, the automated litter device disclosed in WO 2020 / 219849A1. incorporated herein by reference in its entirety’ for all purposes, makes use of one or more sensors near the entry opening to determine the presence of an animal entering and / or exiting the chamber and a level of litter within the chamber. An automated litter device may also make use of one or more mass sensors, such as disclosed in US Patent No. 11.399.502. incorporated herein by reference in its entirety for all purposes.

[0004] These automated pet health devices via their sensors collect a vast amount of data regarding use by an animal. One of these sensed values may include presence, weight, and / or mass by one or more mass sensors of a device, ft would be advantageous to determine an identity’ of an animal based on sensed presence and weight and / or mass. It would be advantageous to distinguish between multiple animals using a device based on their sensed weight and / or mass, ft would be advantageous to collect data and / or determine trends and associate with a specific animal when a device is used by multiple animals. It would be useful to display such data, including individualized by animal, to a user via one or more user interfaces.SUMMARY

[0005] The present teachings relate to a method for identify ing an animal using one or more pet health devices comprising: a) monitoring for a presence of the animal at the one or more pet health devices by one or more sensing devices; b) detecting the presence of the animal at the one or more pet health devices by the one or more sensing devices; c) recording a weight of the animal as detected by the one or more sensing devices, wherein the one or more sensing devices include one or more mass sensors, and the weight once recorded is a recorded weight; d) detecting a departure of the animal from the one or more pet health devices by the one or more sensing devices; e) automatically identifying the animal by automatically associatingthe recorded weight with an identity of the animal by matching the recorded weight with a substantially similar weight associated with an animal profile.

[0006] The present teachings relate to a method for identifying an animal using one or more pet health devices comprising: a) monitoring for a presence of the animal at the one or more pet health devices by one or more mass sensors; b) detecting the presence of the animal at the one or more pet health devices by the one or more mass sensors when the one or more mass sensors detect a weight over a detection threshold and the weight is detected over an initial threshold time period; c) recording a weight of the animal as detected by the one or more mass sensors, wherein the weight once recorded is a recorded weight, and wherein the recorded weight is a peak detected weight; d) detecting a departure of the animal from the one or more pet health devices by the one or more mass sensors when the one or more mass sensors detect the weight below at or below a hysteresis threshold; and e) automatically identifying the animal by automatically associating the recorded weight with an identity of the animal by matching the recorded weight with a substantially similar weight associated with an animal profile.

[0007] The disclosure may be beneficial in multi-pet households. Weight may be used to identify an animal entering, exiting, and / or using a device. If weights are sufficiently distinct, weight may provide a substantially accurate identifier. In doing so, the behavior of a specific animal can be monitored and segregated from the behavior of other animals using the same devices. This can aid in providing an accurate history per individual pet, identifying trends of a specific pet, and potentially even identifying potential health concerns or changes in behavior for a specific pet.BRIEF DESCRIPTION OF DRAWINGS

[0008] FIG. 1 illustrates animal profiles displayed in an application on a computing device.

[0009] FIG. 2 illustrates an animal profile displayed in an application on a computing device.

[0010] FIG. 3 illustrates an animal profile database.

[0011] FIG. 4 illustrates an animal weight database.

[0012] FIG. 5 illustrates an animal weight profile displayed in an application.

[0013] FIG. 6 illustrates a system.

[0014] FIG. 7 illustrates a system.

[0015] FIG. 8 is a perspective view of a litter device.

[0016] FIG. 9 is a cross-section view of a litter device.

[0017] FIG. 10 is a perspective view of a water dispenser.

[0018] FIG. 11 is a perspective view of a feeder.

[0019] FIG. 12 is a jitter plot with recorded weight values and resulting threshold values from a clustering algorithm.

[0020] FIG. 13 illustrates a weight recording indicating presence of an animal at a pet health device.

[0021] FIG. 14 illustrates a method of identifying an animal based on weight.DETAILED DESCRIPTION

[0022] The explanations and illustrations presented herein are intended to acquaint others skilled in the art with the present teachings, its principles, and its practical application. The specific embodiments of thepresent teachings as set forth are not intended as being exhaustive or limiting of the present teachings. The scope of the present teachings should be detennined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. The disclosures of all articles and references, including patent applications and publications, are incorporated by reference for all purposes. Other combinations are also possible as will be gleaned from the following claims, which are also hereby incorporated by reference into this written description.

[0023] Pet Health Devices and System

[0024] The system of the present teachings may cooperate with and / or be integrated into one or more pet health devices. The one or more pet health devices may function to serve an animal with one or more needs necessary for their health. The needs may include water consumption, food consumption, waste elimination, rest, and / or the like. The one or more pet health devices may include one or more litter devices, feeders, water dispensers, weight scales, resting devices (e.g., pet bed, crate), the like, or any combination thereof. The one or more pet health devices may meet the needs of one or more domesticated animals. One or more domesticated animals may include one or more cats, rabbits, ferrets, pigs, dogs, ducks, goats, foxes, the like, or any combination thereof.

[0025] The one or more pet health devices may include one or more litter devices. The teachings may be particularly relevant to a litter device which is an automated litter device. An automated litter device may be any type of litter device which automates cleaning of the device after elimination of waste by an animal. A litter device may include the kind in which a chamber rotates to cause rotation of a sifting portion therein, which then segregates waste from litter. A litter device may be the kind in which a sifting portion rotates within a chamber to pass through the litter and segregate waste from the litter. A litter device may be the kind in which an automated sifting scoop passes through litter retained within a fairly rectangular litter box to sift and segregate waste from litter.

[0026] The litter device may include a bezel, a chamber, a box, a septum, a sifting scoop, a bonnet, a base, a waste receptacle, a track, a hub. an entry' barrier, the like, or any combination thereof. The chamber may include an entry opening. The chamber may be configured to hold litter. The chamber may be configured to allow an animal to enter and / or exit. The chamber may be configured to allow an animal to excrete waste within the interior. The chamber may include a septum. The septum may include a sifting portion. The sifting portion may be configured for sifting through litter and separating waste from litter. The litter device may include a waste receptacle. A waste receptacle may be in communication with the chamber. A waste receptacle may be configured to receive waste. A waste receptacle may receive waste from the chamber. The waste receptacle may be configured as a waste drawer.

[0027] The present teachings may be useful for use with an automated litter device having a chamber supported by a base, having a waste drawer, or both. The teachings may also be useful for an automated litter device having an entry barrier which is able to block and allow access into a chamber. The chamber may be a portion of the device configured to hold litter, where an animal may enter and excrete waste, or both. The chamber may be supported by and / or rest above a base. The chamber may be rotatably supported by the base. The chamber may rotate through one or more cleaning cycles to allow for funneling anddisposal of waste. The chamber may have an axis of rotation. The axis of rotation may extend through the entry opening of the chamber. The axis of rotation may be concentric or off-center with the entry opening. The axis of rotation may be a tilted axis of rotation. The tilted axis of rotation may promote funneling and disposal of waste, increased line of sight of one or more sensors, or both. The chamber may include a septum such that rotation of the chamber may result in rotation of a septum which sifts through the litter. The septum may filter clean litter from clumps of waste and guide funneling and / or disposal of the waste. Waste from the chamber may be disposed into a waste drawer. A waste drawer may be located in a support base of the device, below a chamber, adjacent to a chamber, or any combination thereof. A litter dispenser may be affixed to the litter device to replenish litter disposed during cleaning cycles. A bonnet may be located at least partially over a chamber to cover one or more components of the litter device, prevent access to one or more pinch points, or both. A chamber, bezel, cleaning cycle of the chamber, rotational capability, axis of rotation (e.g., tilted rotational axis) base (e.g.. support base), bonnet, waste drawer, litter dispenser, and other components of the litter device may be configured such as those disclosed in US Patent Nos. 8,757,094; and 9,433,185; US Publication No: 2019 / 0364840; and PCT Patent Application No.: PCT / US2020 / 029776 (Published as PCT Publication No. WO 2020 / 219849A1), which are incorporated herein by reference in their entirety for all purposes.

[0028] The one or more pet health devices may include one or more feeders. The teachings may be particularly relevant to a feeder which is an automated feeder. The feeder may be any device that stores and dispenses food for consumption by an animal. Food may include any type of food suitable for consumption by an animal. Food may include solid food, semi-solid food, liquid, the like, or a combination thereof. Solid food may be in the form of granular material. Semi-solid food may be in the form of ground and / or shredded protein (e.g.. meat) and / or vegetables and may be stored or served in a liquid (e.g., gravy). Liquid may refer to a water, broth, gravy, or other liquid. An automated feeder may dispense food into a serving bowl, present a container holding stored food therein, or both.

[0029] The present teachings may be useful with a feeder which stores food in granular form and dispenses a serving of the food into a feeding dish. The present teachings may be useful with a feeder including one or more of the following features: a housing, base portion, chamber portion, hopper, intermediate portion, feeding cavity, serving area, feeding dish, a chute, a cover, one or more handles, a control panel, a dispenser, one or more sensors, a sensing tower, drive source, a power source, or any combination thereof. The feeder may include a base portion, chamber portion supported by the base portion, and a dispenser. The chamber portion may include a hopper. The hopper may store the food therein. A sensing tower may extend through the hopper and housing one or more sensing devices. The sensing tower may extend from the bottom to the top of the hopper. One or more sensing devices may be located at and / or toward a top and / or upper portion of the sensing tower. The sensing device(s) may have a line of sight down into the interior of the hopper. The sensing device(s) may be able to sense a presence, distance, and / or amount of food stored in the hopper. The feeder may have a front opposing a rear. The front of the feeder may be the side of the feeder in which a feeding cavity is exposed. The feeder may have a top opposing a bottom. The bottom of the feeder may be the portion of the feeder which rests on a surface during normal use of the feeder. A feeder may be anautomated food dispenser such as disclosed in PCT Patent Publication No. WO 2020 / 061307. which is incorporated herein by reference in its entirety for all purposes. Another exemplary feeder may be the automated food dispenser such as disclosed in US Patent No. 9,161,514. which is incorporated herein by reference in its entirety for all purposes.

[0030] The present teachings may be useful with a feeder which stores food in semi-solid and / or liquid form within individual serving containers and presents an open container with the food therein. The feeder may include a container storage subassembly, container handling subassembly, container transport subassembly, container opening subassembly, a waste collection subassembly, a container disposal subassembly, the like, or a combination thereof. A container storage subassembly may allow for a plurality of food containers to be stored therein. The containers may be sealed to preserve the food therein. For example, the container storage subassembly may store one or more stacks of sealed containers. The container storage subassembly may include a hopper, magazine, or both. The container storage subassembly may substantially columnar. A container handling subassembly may function to retain a container while moving from a container storage subassembly toward a feeding area. A container handling subassembly may cooperate with a container transport subassembly. A container transport subassembly may function to move a container and / or container handling subassembly in one or more linear directions, away from a container storage subassembly, to a container opening position, to a feeding area, toward a waste collection subassembly, and / or the like. A transport subassembly may be coupled to the container handling subassembly such that one drive shaft (e.g., lead screw) is in rotatable communication with the container handling subassembly. Rotation of the drive shaft in a first direction may cause the container handling subassembly to move toward a front of the feeding assembly, a feeding area, or both. Rotation of the drive shaft in a second direction may cause the container handling subassembly to move toward a rear of the feeding assembly, toward a loading position, or both. The container handling subassembly may move past a container opening subassembly. The container opening subassembly may be located above the container handling subassembly and / or container transport subassembly The container opening subassembly may include one or more jaws, hooks, and / or the like which engage with a lid of the container as the container passes. For example, a pair of jaws may grasp and pinch a leading edge of the lid. As the container continues to move forward on the container handling subassembly and moved by the container transport subassembly, the lid may be peeled away from the container base. The container transport subassembly continues to move the container handling subassembly and open container base to a feeding area (e.g.. front of the feeder). The lid when removed, may fall into the waste collection subassembly. For example, a waste bin may be located below the container opening subassembly, container handling subassembly, and / or container transport subassembly. The open container may then be presented in a container display opening, allowing for an animal to consume the food stored therein. Once complete, the container and container handling subassembly may be retracted from the feeding area by the container transport subassembly. As the container handling subassembly is moved back toward the container storage subassembly, a container disposal subassembly may eject the container base into the waste collection subassembly. For example, a container disposal subassembly may apply a force onto the container base such that the container base ispushed off of the container handling subassembly and falls into the waste collection subassembly. Exemplary automated feeders may be the autonomous feeders as disclosed in US Provisional Patent Application Nos. 63 / 341.962 and 63 / 599,131, and PCT Patent Publication No. WO 2023 / 220751 incorporated herein by reference in their entirety for all purposes.

[0031] The one or more pet health devices may include one or more water dispensers. The teachings may be relevant to a water dispenser which is an automated water dispenser. An automated water dispenser may be any type of dispenser which automated dispensing of water, or any other liquid, for consumption by an animal. An automated water dispenser may rely on any type of actuation mechanism for creating flow of water from a fresh water holding area toward a serving area. One or more actuation mechanisms may include one or more pumps, valves, carousels, drive emits, the like, or any combination thereof.

[0032] The present disclosure may be useful with an automated liquid dispenser. The device may function to provide liquid suitable for consumption by an animal. Liquid may include water, semi-liquid food, and / or the like. The device may function in one or more modes. One or more modes may include a filling mode, circulating mode, emptying mode, or a combination thereof. The device may include a carousel, cap assembly, valve assembly, actuator assembly, one or more tanks (e.g., fresh tank, used tank), one or more housing portions (e.g., bottom, intermediate, and top), one or more serving bowls, one or more filters, the like, or a combmation thereof. In general, a carousel may function like a water wheel to transfer liquid to one or more other areas of the device. The carousel may rotate to receive, circulate, and / or dispense fresh liquid; receive and / or dispense used liquid; or any combination thereof. Fresh water may be dispensed from a tank via one or more actuator assemblies, valve assemblies, or both. The one or more actuator assemblies may be engaged by rotation of the carousel in one or more directions. A direction of rotation of the carousel may be determined by the mode in which in the device is operating. A water dispenser may be an automated liquid dispensing device as disclosed in US Provisional Patent Application No. 63 / 339.763 and PCT Patent Publication No. WO 2023 / 192540. which are incorporated herein by reference in their entirety for all purposes.

[0033] The one or more pet health devices may include one or more controllers. The one or more controllers may function to receive one or more signals, transmit one or more signals, control operations of one or more components of the devices, or a combination thereof. The one or more controllers may be in communication with and / or include one or more sensing devices, communication modules, networks, other controllers, other electrical components, or any combination thereof. The one or more controllers may be adapted to control operation of one or more electrical components of a pet health device. For example, signaling one or more drive sources (e.g.. motors) to power on and causing rotation of a dispenser in a feeder to dispense food, causing rotation of chamber of a litter device to generate a cleaning cycle, causing rotation of a carousel in a water dispenser to dispenser water, and / or causing opening and / or closing of a lid to display and / or conceal food. The one or more controllers may automatically receive, interpret, and / or transmit one or more signals. The one or more controllers may be adapted to receive one or more signals from the one or more sensing devices. The one or more controllers may be in electrical communication with one or more sensing devices. The one or more controllers may interpret one or more signals from oneor more sensing devices as one or more status signals. The controller may relay the one or more status signals to one or more other controllers, processors, storage mediums, computing devices, and / or the like. The one or more controllers may be adapted to receive one or more signals from one or more computing devices. The one or more signals may include one or more instruction signals related to one or more instructions. The one or more instructions may be input by a user into a user interface, stored instructions on a computer readable medium (e.g., software) in one or more computing devices, and / or the like. The one or more controllers may automatically control one or more operations of one or more components upon receipt of one or more signals or instructions. The one or more controllers may reside within or be in communication with the one or more pet health devices. For example, in a litter device, the one or more controllers may be located within or affixed to a bezel, bonnet, base (e.g., support base), chamber, near an entry opening, the like, or any combination thereof. For example, in a feeder, the one or more controllers may be located within a base portion, intermediate portion, chamber portion, near a user interface, in a housing, in a container storage subassembly area, in proximity to a container opening subassembly, the like, or any combination thereof. For example, in a water dispenser, the one or more controllers may be located within the housing, above a feeding dish, in a base portion, near a drive source, the like, or any combination thereof. The one or more controllers may include one or more controllers, microcontrollers, microprocessors, processors, storage mediums, or a combination thereof. One or more suitable controllers may include one or more controllers, microprocessors, or both as described in US Patent No. 8,757,094; 9,433,185; 11,399,502, all of which are incorporated herein by reference in their entirety for all purposes. The one or more controllers may be in communication with and / or include one or more communication modules, processors, storage mediums, circuit boards (e.g.. printed circuit board “PCB ’), input and / or output peripherals, analog to digital convertors, the like, or any combination thereof.

[0034] The pet health devices may include one or more communication modules. The one or more communication modules may allow for the pet health device to receive and / or transmit one or more signals from one or more controllers and / or computing devices, be integrated into a network, or both. The one or more communication modules may have any configuration which may allow for one or more data signals from one or more controllers to be relayed to one or more other controllers, communication modules, communication hubs, networks, computing devices, processors, the like, or any combination thereof located external of the pet health device. The one or more communication modules may include one or more wired communication modules, wireless communication modules, or both. A wired communication module may be any module capable of transmitting and / or receiving one or more data signals via a wired connection. One or more wired communication modules may communicate via one or more networks via a direct, wired connection. A wired connection may include a local area network wired connection by an ethernet port. A wired communication module may include a PC Card. PCMCIA card. PCI card, the like, or any combination thereof. A wireless communication module may include any module capable of transmitting and / or receiving one or more data signals via a wireless connection. One or more wireless communication modules may communicate via one or more networks via a wireless connection. One or more wireless communication modules may include a Wi-Fi transmitter, a Bluetooth transmitter, an infrared transmitter,a radio frequency transmiter, an IEEE 802.15.4 compliant transmiter, cellular radio signal transmiter, Narrowband-Internet of Things (NB-IoT) transmiter, the like, or any combination thereof. A Wi-Fi transmiter may be any transmiter complaint with IEEE 802.11. A communication module may be single band, multi-band (e.g.. dual band), or both. A communication module may operate at 2.4 Ghz. 5 Ghz, the like, or a combination thereof. A cellular radio signal transmiter may be any transceiver compatible with any cellular frequency band (e.g., 500. 900, 1,800, 1,900 MHz) and / or network (3G, LTE, LTE Catl, LTE M. 4G. 5G). A communication module may communicate with one or more other communication modules, computing devices, processors, or any combination thereof directly; via one or more communication hubs, networks, or both; via one or more interaction interfaces; or any combination thereof.

[0035] The pet health devices may have or be in communication with one or more sensing devices. The one or more sensing devices may function to sense the presence of an animal, a behavior of an animal, one or more traits of an animal, identify the animal, one or more conditions and / or operations of a pet health device, the like, or any combination thereof. The one or more sensing devices may receive one or more signals, transmit one or more signals, or a combination thereof. The one or more signals may be related to one or more conditions detected by the sensing device. The one or more conditions may be related to one or more operations of one or more components. The one or more sensing devices may cooperate with one or more other sensing devices w hich detect one or more conditions of one or more pet health devices, data related to an animal, or both. The one or more sensing devices may be located in any suitable location of a pet health device, affixed to the pet health device, in communication with a pet health device, distanced from a pet health device, the like, or any combination thereof. Based on the one or more conditions sensed, one or more sensing devices may transmit one or more signals to one or more controllers, processors, communication modules, computing devices, the like, or any combination thereof. One or more signals from one or more sensing devices may be converted into one or more signals (e.g.. analog to digital, signal to a status signal), data entries, or both by one or more controllers, processors, communication modules, computing devices, or any combination thereof. One or more sensing devices may be configured to detect one or more conditions related to: mass of an animal, presence of an animal, or both.

[0036] The one or more sensing devices may include one or more mass sensors. The one or more mass sensors may function to monitor a mass of a device or a portion of a device, monitor a mass of an animal, identify a presence of an animal within or near a device, measure a mass of an animal, or any combination thereof. A mass sensor may continuously, intermitently, or both monitor for mass and / or changes thereof. The mass sensor may be located at any location in or near a pet health device so that any change in mass of the device, presence of an animal within or near the deGee, or any combination thereof may be detected. The mass sensor may include one or more load cells, resistors, force sensors, switches, controllers, microprocessors, the like, or a combination thereof. The one or more mass sensors may be located anywhere within, on. and / or near a pet health device suitable for detecting mass of an animal, the device or portions thereof, or both; detecting a presence of an animal; or any combination thereof. The one or more mass sensors may be located within one or more feet and / or legs of one or more pet health devices, as a scale plate integrated into a botom of a pet health device, within an interior of one or more pet health devices,on a mat or scale below and / or near (e.g., in front of) one or more pet health devices, the like, or any combination thereof. Exemplary integration into a litter device may include within one or more feet, between a chamber and a support base, below and / or integrated into a waste drawer, a scale / mat below the litter device, the like, or any combination thereof. Exemplary integration with a feeder may include below a serving bowl, one or more feet / legs / scale plates of the feeder, a scale / mat below the feeder, a scale / mat located in front of a serving bowl, the like, or any combination thereof. Exemplary integration with a liquid dispenser may include below a serving bowl, in one or more feet / legs / scale plate of the dispenser, a scale / at below the dispenser, a scale / mat located in front of a serving bowl, the like, or any combination thereof. Exemplary integration with a resting device may include one or more feet / legs / scale plate below or integrated into the bottom of the resting device. The one or more mass sensors may be in communication with one or more controllers, computing devices, processors, communication modules, the like, or any combination thereof. The one or more mass sensors may be directly and / or indirectly connected to one or more controllers, computing devices, processors, communication modules, or any combination thereof. The one or more mass sensors may relay one or more signals relating to a monitored mass to one or more controllers, computing devices, processors, communication modules, or any combination thereof. The one or more mass sensors may relay a presence of mass above a predetermined mass (e.g., detection threshold), a real-time mass, a change in mass, or a combination thereof to one or more controllers, computing devices, processors, communication modules, or any combination thereof. The one or more controllers or other computing devices may receive a substantially continuous and / or intermittent signal from one or more mass sensors and recognize a mass above a predetermined mass, a real-time mass, a change in mass, or a combination thereof. A signal from one or more mass sensors relayed to one or more controllers, computing devices, processors, communication modules, or any combination thereof related to the detected mass maybe referred to as a mass signal. The mass signal may be included as a status signal. Exemplary mass sensors and configurations may be as described in US Patent Nos. 8.757,094, 9,422,185, 11.399.502. and 11,523,586; PCT Publication No. W02020 / 219849; and US Provisional Patent Application No. 63 / 325,480, all of which are incorporated herein by reference in their entirety.

[0037] The one or more sensing devices may include one or more emitting sensors. The one or more emitting sensors may detect a presence of an animal at. in, and / or near a pet health device; movement of an animal relative to a device; size of an animal; distance to an animal; a presence, amount, and / or distance of litter, food, water, and / or the like in a pet health device; the like; or any combination thereof. The one or more emitting sensors may be located anywhere on, within, or near a pet health device. One or more emitting sensors may include one or more laser sensors (e.g.. time-of-flight sensors), infrared sensors, ultrasonic sensors, radio frequency (RF) admittance sensors, optical interface sensors, microwave sensors, the like, or combination thereof. The one or more emitting sensors may be located anywhere within, on, and / or near a pet health device suitable for detecting presence, distance, or other physical traits of an animal. The one or more emitting sensors may be located within an interior and / or exterior of one or more pet health devices. Exemplary integration into a litter device may include affixed to a bezel, within a chamber, inside of a waste receptacle, affixed to a bonnet, the like, or any combination thereof. Exemplary- integration to afeeder or liquid dispenser may include at or near a serving dish, inside of a hopper and / or tank, part of a sensing tower, a front face of the device, or any combination thereof. The one or more emitting sensors may be in communication with one or more controllers, computing devices, processors, communication modules, or any combination thereof. The one or more emitting sensors may be directly and / or indirectly connected to one or more controllers, computing devices, processors, communication modules, or any combination thereof. The one or more emitting sensors may relay one or more signals related to a monitored physical condition to one or more controllers, computing devices, processors, communication modules, or any combination thereof. The one or more emitting sensors may relay a presence of an animal, an absence of an animal, a distance to an animal, one or more positions or behavior of an animal, the like, or a combination thereof to one or more controllers, computing devices, processors, communication modules, or any combination thereof. One or more emitting sensors may cooperate together to determine and / or track one or more positions or physical behaviors of an animal. A signal from one or more emitting sensors relayed to one or more controllers, computing devices, processors, communication modules, or any combination thereof related to the detected object may be referred to as an emitting signal. The emitting signal may be included as a status signal. Exemplary emitting sensors, such as laser sensors, and configurations are disclosed in US Patent Nos. 11,399,502, and 11,523,586, which are incorporated herein by reference in their entirety.

[0038] The one or more pet health devices may be in communication with a communication hub. A communication hub may function to receive one or more signals, transfer one or more signals, or both from one or more other computing devices. The communication hub may be any type of communication hub capable of sending and transmitting data signals over a network to one or a plurality of computing devices. The communication hub may include a wired router, a wireless router, an antenna, a satellite, or any combination thereof. For example, an antenna may include a cellular tower. The communication hub may be connected to the one or more pet health devices, one or more computing devices, or both a via wired connection, wireless connection, or a combination of both. For example, the communication hub may be in wireless connection with the pet health devices via the communication module. The communication hub may allow for communication of a computing device with the pet health devices when the computing device is directly connected to the communication hub, indirectly connected to the communication hub, or both. A direct connection to the communication hub may mean that the computing device is directly connected to the communication hub via a wired and / or wireless connection and communicates with the litter device through the communication hub. An indirect connection to the communication hub may mean that a computing device first communicates with one or more other computing devices via a network before transmitting and / or receive one or more signals to and / or from the communication hub and then to the litter device.

[0039] The one or more pet health devices may be integrated into one or more netw orks. The pet health devices may be in removable communication with one or more networks. The one or more networks may be formed by placing the pet health devices in communication with one or more other computing devices. One or more netw orks may include one or more communication hubs, communication modules, computingdevices, or a combination thereof as part of the network. One or more networks may be free of one or more communication hubs. One or more computing devices of the system may be directly comrected to one another without the use of a communication hub. For example, a communication module of a pet health device may be placed in direct communication with a communication module of a mobile communication device (e.g., mobile phone) without having a communication hub therebetween. The pet health devices connected together without a communication hub may form a network, and / or be connected to another network. As another alternative, one or more pet health devices may include a communication hub integrated therein. One or more pet health devices form a network by connecting to the same communication hub of one of the pet health devices and / or be connected to another network. One or more networks may be connected to one or more other networks. One or more networks may include one or more local area networks (LAN), wide area networks (WAN), intranet, Internet, Internet of Things (loT), the like, or any combination thereof. The netw ork may allow for the pet health devices to be in communication with one or more user interfaces remote from the device via the Internet, such as through one or more managed cloud services. An exemplary’ managed cloud sendee may include AWS loT Core by Amazon Web Services®. The network may be temporarily, semi-permanently, or permanently connected to one or more computing devices, pet health devices, or both. A netw ork may allow' for one or more computing devices to be temporarily and / or permanently connected to the pet health devices to transmit one or more data signals to the pet health devices, receive one or more data signals from the devices, or both. The network may allow for one or more signals from one or more controllers to be relayed through the system to one or more other computing devices, processors, storage mediums, the like, or any combination thereof. The network may allow for one or more computing devices to receive one or more data entries from and / or transmit one or more data entries to one or more storage mediums. The network may allow for transmission of one or more signals, status signals, data entries, instruction signals, or any combination thereof for processing by one or more processors.

[0040] Devices on the network may communicate via one or more protocols. The one or more protocols may allow for two or more devices part of the network or system to communicate with one another either while in direct or indirect communication, wireless or wired communication, via one or more communication hubs, or any combination thereof. The one or more protocols may be any protocol suitable for use in telecommunications. The one or more protocols may be suitable for wired, wireless, or both communication styles between devices within the network or system. The one or more protocols may allow the devices of the system to be connected to and communication with one another through the Internet. The network and protocols may allow for the devices to be an “Internet of Things” (loT). The one or more protocols may be those compatible with cloud computing sen ices. Exemplary cloud computing services may include Amazon Web Sendees®, Microsoft Azure®, Google Cloud®, IBM®, Oracle Cloud®, the like, or any combination thereof. One or more cloud computing services may be managed by one or more managed cloud services. Exemplary’ protocols may include simple object access protocol (SOAP), hypertext transfer protocol (HTTP), user datagram protocol (UDP), message queuing telemetry’ transport (MQTT), Bluetooth low’ energy’ (BLE) protocol, IEEE 802 family of standards, the like, or any combinationthereof. For example, the automated litter device may connect wirelessly to a computing device using one or more protocols. Exemplary protocols may include UDP, BLE, and the like which allow for direct communication between devices. UDP and BLE may even be useful for allowing direct communication with devices without using the Internet as part of the network. As another example, an automated litter device may connect with a dispatch interface, interaction interface, or both via one or more protocols using the Internet. Exemplary protocols for commrmication from the litter device to a dispatch interface, interaction interface, or both may include UDP. MQTT, REST, and the like. As another example, a dispatch interface, interaction interface, or both may communicate with an authentication portal using one or more protocols either directly or indirectly through the Internet. Exemplary protocols for communication between a dispatch interface or interaction interface and an authentical portal may include REST, SOAP, MQTT, the like, or any combination thereof. Suitable protocols useful as loT protocols may be those provided by “loT Standards and Protocols” by Postscapes™ available at https: / / www.postscapes.com / internet-of-things- protocols / , incorporated herein in its entirety for all purposes.

[0041] The one or more pet health devices may be integrated into a system. The system may allow for monitoring signals from, receiving signals from, and / or sending signals to one or more of the pet health devices. The system may allow' for sending one or more instruction signals to a pet health device. The system may allow for transmitting one or more signals, status signals, or both from the pet health device. The system may allow for storing one or more data entries related to one or more signals. The system may allow for one or more algorithms to be executed locally and / or remote from the pet health device(s). The system may allow for controlling of one or more operations of the pet health devices while remote from the device. The system may include one or more communication hubs, computing devices, processors, storage mediums, databases, the like, or any combination thereof. The system may allow for one or more pet health devices to communicate with, be controlled by, or both one or more computing devices remote therefrom. The system may allow for one or more pet health devices to cooperate with an application. The system may allow for one or more pet health devices to interact with one or more other pet health devices.

[0042] The pet health devices may include and / or be in communication with one or more computing devices. The one or more computing devices may function to receive and / or transmit one or more signals; convert one or more signals to data entries; to send one or more data entries to a storage medium; to store one or more data entries; to retrieve one or more data entries from a storage medium; to access and / or execute one or more methods, algorithms, and / or processes; apply one or more rules; control operations of one or more pet health devices; execute an application; the like; or any combination thereof. One or more computing devices may include or be in communication with one or more other computing devices, processors, storage mediums, databases, interaction devices, pet health device(s). or any combination thereof. One or more computing devices may communicate with one or more computing devices, processors, storage mediums, databases, or any combination thereof through an interaction interface, dispatch interface, or both. Communication between computing devices may be controlled or managed via a managed cloud service. The one or more computing devices may include one or more non-transient storage mediums, processors, other computing components, or a combination thereof. One or morecomputing devices may include one or more servers. One or more servers may include one or more physical servers, virtual servers, or a combination of both. One or more servers may include one or more local servers, remote servers, or both. One or more computing devices may include one or more processors of pet health device(s), personal computers (e.g., laptop, desktop, etc.), mobile computing devices (e.g., tablet, mobile phone, etc.), or a combination thereof.

[0043] One or more computing devices may include one or more processors. The one or more processors may function to analyze one or more signals from the pet health device(s), one or more storage mediums, databases, communication modules, applications, user interfaces, or any combination thereof. The one or more processors may be located within or in communication with one or more computing devices, servers, storage mediums, or any combination thereof. One or more processors may be in communication with one or more other processors. The one or more processors may automatically process data; execute one or more methods, algorithms, and / or processes; apply one or more rules; evaluate data; control operations of one or more pet health devices or components thereof; control operations of an application; or a combination thereof; may wait for an instruction or signal such as from a user; or any combination thereof. Processing data may include receiving, transforming, outputting, executing, the like, or any combination thereof. One or more processors may be part of one or more hardware, software, systems, or any combination thereof. One or more hardware processors may include one or more central processing units, multi-core processors, front-end processors, the like, or any combination thereof. One or more software processors may include one or more word processors, document processors, the like, or any combination thereof. One or more system processors may include one or more information processors, the like, or a combination thereof. One or more processors suitable for use within the pet health device(s) as part of the one or more controllers may include a microcontroller, such as Part No. PIC18F45K22 and / or Part No. PIC18F46J50 produced by Microchip Technology Inc., incorporated herein by reference in their entirety for all purposes. The one or more processors may be located within a same non-transient medium as one or more storage mediums, other processors, communication modules, communication hubs, or any combination thereof. The one or more processors may be an ARM-based processor. Exemplary ARM-based processors may include one or more of the Cortex-M Family, versions ARM to ARMv6 (ARM 32-bit), version ARMv6-M to ARMv9-R (ARM 32-bit Cortex), versions ARMv8-A to ARMv-9 (ARM 64 / 32-bit). the like, or any combination thereof. The one or more processors may include one or more local and / or cloud-based processors. Local may mean the processor is located onboard a same device it is controlling. A cloud-based processor may be part of or in communication with a dispatch interface, an interaction interface, an authentication portal, or a combination thereof. A cloud-based processor may be located remote from a pet health device, a computing device, one or more other processors, one or more databases, or any combination thereof. Cloudbased may mean that the one or more processors may reside in a non-transient storage medium located remote from the pet health device, computing device, processor, databases, or any combination thereof. One or more cloud-based processors may be accessible via one or more networks. A suitable cloud-based processor may be Amazon Elastic Compute Cloud™ (EC2™) may be provided by Amazon Web Sendees®, incorporated herein by reference in its entirety for all purposes. Another suitable platform for a cloud-basedprocessor may include Lambda™ provided by Amazon Web Services®, incorporated herein in its entirety by reference for all purposes. The one or more processors may convert data signals to data entries to be saved within one or more storage mediums. The one or more processors may access one or more methods, algorithms, and / or processes to analyze one or more data entries and / or data signals, execute one or more functions of a pet health device, execute one or more functions of an application, the like, or a combination thereof. The one or more processors may access one or more methods, algorithms, and / or processes saved within one or more memory storage mediums. The one or more methods, algorithms, and / or processes being accessed by one or more processors may be located in the same or different computing device (e.g.. storage medium, server) as the processor(s). The one or more methods, algorithms, and / or processes may include a method for identifying an animal based on weight, a monitoring algorithm, a use algorithm, a weighing algorithm, a departure algorithm, a weight storage algorithm, a weight identification algorithm, a notification algorithm, a trend algorithm, an updating algorithm, an onboarding algorithm, initial weight algorithm, a disabling algorithm, the like, or a combination thereof.

[0044] One or more computing devices may include one or more memory storage mediums (e.g., storage medium). The one or more memory storage mediums may include one or more hard drives (e.g., hard drive memory), chips (e.g., Random Access Memory “RAM)”), discs, flash drives, memory’ cards, the like, or any combination thereof. The one or more memory storage mediums include one or more non-transient storage mediums. The one or more storage mediums may include one or more local and / or cloud-based storage mediums. Local may mean the storage medium is onboard the device having its data stored therein. A cloud-based storage medium may be located remote from a pet health device(s), a computing device, one or more processors, one or more databases, or any combination thereof. Cloud-based may mean that the one or more storage mediums may reside remote from the pet health device(s), computing device, processor, other databases, or any combination thereof. One or more cloud-based storage mediums may be accessible via one or more networks. A suitable cloud-based storage medium may be Amazon S3TM provided by Amazon Web Services®, incorporated herein by reference in its entirety for all purposes. One or more memory storage mediums may store one or more data entries in a native format, foreign format, or both. One or more memory storage mediums may store data entries as objects, files, blocks, or a combination thereof. The one or more memory storage mediums may include one or more algorithms, rules, databases, data entries, the like, or any combination therefore stored therein. The one or more memory storage mediums may store data in the form of one or more databases.

[0045] One or more computing devices may include one or more databases. The one or more databases may function to receive, store, and / or allow for retrieval of one or more data entries. The one or more databases may be located within one or more memory storage mediums. The one or more databases may include any type of database able to store digital information. The digital information may be stored within one or more databases in any suitable form using any suitable database management system (DBMS). Exemplary storage forms include relational databases (e.g., SQL database, row-oriented, column-oriented), non-relational databases (e.g., NoSQL database), correlation databases, ordered / unordered flat files, structured files, the like, or any combination thereof. The one or more databases may store one or moreclassifications of data models. The one or more classifications may include column (e.g.. wide column), document, key-value (e.g., key-value cache, key-value store), object, graph, multi-model, or any combination thereof. One or more databases may be located within or be part of hardware, software, or both. One or more databases may be stored on the same or different hardware and / or software as one or more other databases. The databases may be located within one or more non-transient storage mediums. One or more databases may be located in the same or different non-transient storage medium as one or more other databases. The one or more databases may be accessible by one or more processors to retrieve data entries for analysis via one or more algorithms. The one or more databases may be one or more local and / or cloud-based databases. Cloud-based may mean that the one or more databases may reside in a non- transient storage medium located remote from the pet health device(s). One or more cloud-based databases may be accessible via one or more netw orks. One suitable database service may be Amazon DynamoDB® offered through Amazon Web Services®, incorporated herein in its entirety by reference for all purposes.

[0046] One or more databases may include one or more databases capable of storing one or more conditions of pet health device(s), one or more status signals related to pet health device(s). one or more instruction signals sent to pet health device(s), one or more users, one or more user accounts, one or more registered pet health device(s), one or more traits and / or characteristics of one or more animals (e.g., weight), one or more identifications of one or more animals, the like, or any combination thereof. One or more databases may include one or more animal profile databases, weight databases, registered device databases, account databases, the like, or a combination thereof. One or more animal profile databases may store data associated with one or more animals. One or more animal profile databases may include the following data per animal entry': data key, animal image, identifier, name, species, breed, gender, weight (e.g., input by owner and / or derived), date of birth, age, account and / or owner, location, pet health device(s) associated with the pet, the like, or a combination thereof. One or more weight databases may store each weight recorded by one or more pet health devices. One or more weight databases may include the following data per weight recorded: data key, timestamp (e.g., time weight was detected), account / owner, pet health device (e.g., where weight detected), weight value, the like, or a combination thereof. There may be one or more intermediate weight databases which store one or more derived w eight values, such as from one or more weight identification algorithms (e.g., clustering). One or more registered device databases may store each pet health device recorded into the system. One or more registered device databases may include the following data per registered pet health device: data key, type of device (e.g., litter device, feeder, water dispenser, scale, etc.), serial number, manufacturing date, purchase date, registration date, owner / account. location, the like, or a combination thereof. One or more account databases may store information related to each account, owner, and / or user part of the system. One or more account databases may store the following per individual account: data key; name of account owmer; names of other users; contact information, including emails, phone numbers, mailing addresses; birthdays; age; gender; race; ethnicity'; location; the like; or a combination thereof.

[0047] One or more computing devices may include one or more interaction interfaces. One or more interaction devices may function to transmit and / or relay one or more data signals, data entries, or bothfrom one or more computing devices, processors, storage mediums, databases, or a combination thereof to one or more other computing devices, processors, storage mediums, databases, or a combination thereof. One or more interaction interfaces may include one or more application programming interfaces (API). The one or more interaction interfaces may utilize one or more architectures. The one or more architectures of an interaction interface may be one or more web service architectures useful for requesting, receiving, and / or transmitting one or more data signals, data entries, or both from one or more other remotely located computing devices connected via one or more networks (e.g.. web-based resources). One or more web sendee architectures may include Representation State Transfer (REST). gRPC. the like, or any combination thereof. One suitable interaction interface which is a REST API may be Amazon API Gateway™ provided by Amazon Web Sen ices®, incorporated herein by reference in its entirety for all purposes. The one or more interaction interfaces may utilize one or more protocols for transmitting and / or receiving one or more data signals, data entries, or both. One or more protocols may include simple object access protocol (SOAP), hypertext transfer protocol (HTTP), user datagram protocol (UDP), message queuing telemetry transport (MQTT), the like, or any combination thereof.

[0048] The system in which the pet health device(s) may be integrated into may include and / or be connected to one or more authentication controls. One or more authentication controls may function to control access of a user to one or more pet health devices, computing devices, processors, storage mediums, databases, interaction interfaces, e-commerce platforms, the like, or any combination thereof. The one or more authentication controls may be in communication with one or more components of tire system via one or more networks. The one or more authentication controls may communicate with one or more other components of die system via one or more interaction interfaces. The one or more authentication controls may receive one or more user credentials via one or more user interfaces of one or more computing devices. One or more user credentials may include one or more data entries related to one or more user accounts. One or more user credentials may include one or more user login identifications (e g., "user ID”), passwords, die like, or a combination thereof. One or more authentication controls may include one or more authentication algorithms. The one or more authentication algorithms may compare the one or more user credentials provided via a user interface with one or more data entries residing within one or more databases, such as a User Database and / or User Settings Database. If the one or more user credentials match one or more data entries, the one or more authentication algorithms may instruct one or more computing devices, processors, or both to allow a user to access one or more data entries, receive one or more data signals, transmit one or more instruction signals, or any combination thereof. A suitable authentication control may include Amazon Cognito™ available through Amazon Web Services®, incorporated herein by reference in its entirety for all purposes. One or more authentication controls may cooperate with one or more e-commerce platforms. One or more authentication controls may authenticate one or more users based on one or more user credentials received from one or more e-commerce platforms, stored within one or more databases of one or more e-commerce platforms, or both.

[0049] One or more computing devices may include one or more user interfaces. The one or more user interfaces may function to display information related to one or more pet health devices, display one ormore notifications related to one or more animals, receive user inputs related to the pet health devices, transmit information related to the pet health devices, the like, or any combination thereof. The one or more user interfaces may be located on the pet health device, a separate computing device, or both. One or more user interfaces may be part of one or more computing devices. One or more user interfaces may include one or more interfaces capable of relaying information (e.g., data entries) to a user, receiving information (e.g.. data signals) from a user, or both. One or more user interfaces may display information related to the pet health device. One or more user interfaces may display information from one or more algorithms. The user interface may allow for inputting of information related to a pet health device, an owner, an animal, the like, or a combination thereof. Information may include a username, password, one or more instruction signals, uploaded documents (e.g., veterinary documents), animal profile information, owner / user information, the like, or any combination thereof. The one or more user interfaces may include one or more graphic user interfaces. The one or more graphic interfaces may include one or more screens. The one or more screens may be a screen located directly on the litter device, another computing device, or both. The one or more screens may be a screen on a mobile computing device, non-mobile computing device, or both. The one or more graphic interfaces may include and / or be in communication with one or more user input devices. The one or more user input devices may allow for receiving one or more inputs (e.g., instruction signals) from a user. The one or more input devices may include one or more buttons, wheels, keyboards, switches, touchscreens, the like, or any combination thereof. The one or more input devices may be integrated with a graphic interface. The one or more input devices may include one or more touch-sensitive monitor screens.

[0050] The one or more pet health devices, system, or both may include or be in communication with one or more applications. The application (i.e., “computer program”) may function to access data, upload data, receive data, receive instructions, transmit instructions, display information, transmit notifications, the like, or a combination thereof relative to a pet health device, an animal, a computing device, the like, or any combination thereof. The application may be stored on one or more storage mediums. The application may be stored on one or more personal computing devices, remote computing devices, or both. The application may be accessible by one or more personal computing devices while being at least partially executed from one or more remote computing devices. The application may comprise and / or access one or more computerexecutable instructions, algorithms, rules, models, processes, methods, user interfaces, menus, databases, the like, or any combination thereof. The computer-executable instructions, when executed by a computing device, may cause the computing device to perform one or more methods described herein. The application may be downloaded, accessible without downloading, or both. The application may be downloadable onto one or more computing devices. The application may be downloadable from an application store (i.e., “app store”). An application store may include, but is not limited to, Apple® App Store®, Google Play®, Amazon Appstore®, Skills Shop for Amazon’s® Alexa®, the like, or any combination thereof. The application may be accessible without downloading onto one or more computing devices. The application may be accessible via one or more web browsers. The application may be accessible as a website. The application may interact and / or communicate through one or more user interfaces. The application may beutilized by and / or on one or more computing devices. The application may also be referred to as a dedicated application. The application may be referred to as a pet health application. The application may automatically generate one or more displays and / or menus on a user interface of a computing device.

[0051] Method of Identifying an Animal Based on Weight

[0052] The present teachings relate to one or more methods for identifying an animal. The one or more methods may be particularly useful with one or more pet health devices and / or the system of pet health devices as disclosed in the present teachings. Identification may occur based on use of one or more pet health devices by the animal. One or more traits of the animal may be sensed and used to determine the identity of the animal. One or more traits of the animal may be the weight of the animal. In other words, the present teachings may relate to one or more methods of identifying an animal based on weight.

[0053] The method may be understood as a computer-implemented method. The method may be referred to as an animal identification method, animal identification by weight method, weight-based identification method, the like, or any combination thereof. The method may be stored in one or more storage mediums. The one or more storage mediums may be local and / or remote from one or more pet health devices. The method may be accessible by one or more processors. The method may be automatically executed. Each step, or only some steps, may be automatically executed. Automatic execution may be by the one or more processors. The method may be executed locally, remotely, or both. The method may be executed by one or more controllers of a pet health device, by edge-computing, cloud-computing, or a combination thereof. It is possible one or more local processors may execute a portion of the method while one or more remote processors may execute another portion of the method, the method may be entirely remotely executed, or the method may be entirely locally executed.

[0054] Although the terms house, home, dwelling, and household may be used, they are not limited to the specific definitions. These terms may also refer to a general building, shared residence, shared property, and / or the like. For example, a farm, a shelter, an animal boarding building, an office building, an animal sanctuary, a veterinary hospital, the like, or a combination thereof.

[0055] The method for identifying an animal using one or more pet health devices may comprise: a) monitoring for a presence of the animal at the one or more pet health devices by one or more sensing devices; b) detecting the presence of the animal at the one or more pet health devices by the one or more sensing devices; c) recording a weight of the animal as detected by the one or more sensing devices, wherein the one or more sensing devices include one or more mass sensors, and the weight once recorded is a recorded weight; d) detecting a departure of the animal from the one or more pet health devices by the one or more sensing devices; e) automatically identifying the animal by automatically associating the recorded weight with an identify of the animal by matching the recorded weight with a substantially similar weight associated with an animal profile.

[0056] The method for identifying an animal using one or more pet health devices may comprise: a) monitoring for a presence of the animal at the one or more pet health devices by one or more mass sensors; b) detecting the presence of the animal at the one or more pet health devices by the one or more mass sensors when the one or more mass sensors detect a weight over a detection threshold and the weight isdetected over an initial threshold time period; c) recording a weight of the animal as detected by the one or more mass sensors, wherein the weight once recorded is a recorded weight, and wherein the recorded weight is a peak detected weight; d) detecting a departure of the animal from the one or more pet health devices by the one or more mass sensors when the one or more mass sensors detect the weight below at or below a hysteresis threshold; and e) automatically identifying the animal by automatically associating the recorded weight with an identify of the animal by matching the recorded weight with a substantially similar weight associated with an animal profile.

[0057] The method for identifying an animal using one or more pet health devices may comprise one or more of the following in any suitable combination or sequence: a) onboarding one or more animal profiles; b) monitoring for a presence of the animal at the one or more pet health devices by one or more sensing devices; c) detecting the presence of the animal at the one or more pet health devices by the one or more sensing devices; d) detecting use of a pet health device by an animal, such as by detecting the presence of an animal over an initial threshold time period, e) recording a weight of the annual as detected by the one or more sensing devices, wherein the one or more sensing devices include one or more mass sensors, and the weight once recorded is a recorded weight; f) detecting a departure of the animal from the one or more pet health devices by the one or more sensing devices; g) automatically associating the recorded weight of the animal with an activity of the animal, h) automatically identifying the animal by automatically associating the recorded weight with an identity of the animal by matching the recorded weight with a substantially similar weight associated with an animal profile, i) notifying one or more users of an identify, weight, and / or activity of the animal, j) updating one or more trends associated with the animal, k) inquiring as to a new animal if a new weight is detected which goes unmatched with an existing animal profile, 1) automatically disabling die association of weights with specific animals and animal identification based on weight, and m) updating one or more threshold weights of one or more animals.

[0058] The method for identifying an animal based on weight may comprise one or more of the following in any suitable combination or sequence: a) executing an onboarding algorithm by one or more processors such as to associate an initial threshold weight with an animal profile, b) executing a monitoring algorithm by one or more processors part of a pet health device to monitor for the presence of the animal at the pet health device, c) detecting the presence of an animal at a pet health device by one or more sensing devices (e.g., mass sensors and / or emitting sensors), d) detecting use of a pet health device by the animal during execution of a use algorithm by one or more processors, e) weighing and recording the weight of the animal as detected by one or more mass sensors during execution of a weighing algorithm by one or more processors, f) monitoring for and detecting the departure of the animal from the one or more pet health devices during execution of a departure algorithm by one or more processors, g) associating the weight with an activity of the animal during execution of a weight storage algorithm by one or more processors, f) determining an identity of the animal based on the recorded weight during execution of a weight identification algorithm by one or more processors, h) notifying a user, passively and / or actively, via an application on a user interface of a personal computing device during execution of a notification algorithm, i) updating one or more trends associated with a specific animal, such as their weight and / or use of one ormore pet health devices, during execution of a trend algorithm executed by one or more processors, and j) updating one or more weight threshold values associated with one or more animal profiles during execution of an updating algorithm by one or more processors. The one or more processors may be the same or different for each step of the method.

[0059] The method may include onboarding one or more animal profiles. Onboarding may refer to one or more users creating and / or editing one or more animal profiles via a user interface of a computing device and the one or more animal profiles being stored in one or more animal profile databases. Onboarding may allow for a user to create one or more animal profiles, edit one or more animal profiles, store one or more animal profiles into one or more databases, associate a weight with one or more animal profiles, store a weight in one or more databases, and / or the like. Onboarding may allow for a user to manually input data, allow a user to control initial gathering of data, allow for partial or full automation of gathering data, or a collection thereof related to one or more animals. Onboarding may allow for a user to create one or multiple animal profiles. A single animal profile may be useful in a home, or other dwelling, with a single pet. Multiple animal profiles may be useful in a home, or other dwelling, with multiple pets.

[0060] Onboarding may include one or more users initiating (e.g., opening) an application on a computing device. The application may be a pet health application. The application may be able to control one or more operations of one or more pet health devices. The application may be the application as disclosed earlier in these teachings. The computing device may be a personal computing device (e.g., mobile phone, mobile device, tablet, personal computer). Some of the basic teachings and principles relative to computing device, pet health application, and control of a pet health device may be as disclosed in US Patent No. 11,399,502, incorporated herein by reference in its entirety for all purposes.

[0061] Onboarding may include the application executing one or more onboarding algorithms. The onboarding algorithm may be stored locally and / or remotely from the computing device. In other words, the onboarding algorithm may be accessible via local and / or cloud-based computing such as to at least be partially executed on the computing device. The onboarding algorithm may include one or more onboarding displays and / or menus being opened on the user interface of the computing device. The onboarding algorithm may automatically prompt the user(s) to input one or more inputs via the displays and / or menus.

[0062] The onboarding algorithm may automatically prompt the user(s) to input one or more animal quantity inputs. An animal quantity input may allow for a user to input how many animals may share one or more pet health devices, share a household, and / or the like. An animal quantity may allow for a user to input how many new animals may be being added into their user account. Upon the quantity being entered by the user, the onboarding algorithm may automatically generate a matching number of new individual animal profiles. Each animal profile may be associated with an animal profile record in an animal profile database. Each newly created animal profile may add a new animal profile record to an animal profile database. The onboarding algorithm may automatically associate the one or more animal records in an animal profile database with one or more records in one or more other databases. The one or more other databases may include a registered device database, account database, weight database, the like, or any combination thereof. The animal profiles (e.g., animal profile records) may be automatically associatedwith one or more users (e.g., owner), accounts, pet health devices, household, devices, locations, and / or the like.

[0063] The onboarding algorithm may automatically prompt the user(s) to create one or more newly created animal profiles, edit one or more existing animal profiles, or both. The onboarding algorithm may execute one or more animal profile displays in editing mode on an interface of a computing device, in the application, or both. Creating and / or editing one or more individual animal profiles may include adding and / or editing data associated with one or more animal profile records. Creating and / or editing one or more individual animal profiles may include one or more users uploading and / or changing information (e.g.. data) about one or more animals, associating the one or more animals with their user account, household, pet health devices, location, the like, or a combination thereof. The animal profile may include a plurality of data associated with the identity of the animal. Each animal profile record may be associated with a single animal. The information may include a plurality' of photos and / or video of the animal. The information may include the animal’s name, age, gender, weight (known, estimated), breed, known health issues, medications, known eating habits, household, user account, address (city, state, country), language preference for understanding verbal commands, and / or the like. The animal profile data may be stored in one or more databases within the system. The animal profile data may be stored in one or more databases within the system. The animal profile data may be automatically stored in one or more animal profile databases. Each animal profile may be automatically converted into one or more data records, data strings (e.g., by one or more processors), and / or the like (e.g., such as upon the user saving the input information).

[0064] The method may include associating one or more initial weights with one or more animal profiles. Each animal profde may be associated with a single, initial weight. Associating a single, initial weight to a specific animal profile may allow for identifying an animal based on weight, starting to create a history of specific animal’s weight change, starting to create a history of a specific animal’s behaviors, and / or allowing for trends in a specific animal’s weight and / or behavior to be determined. The initial weight associated with an animal and / or animal profile may be referred to as the animal weight. This animal weight may also be referred to as the initial weight, baseline weight, anchor weight, identifying weight, comparison weight, the like, or a combination thereof.

[0065] Associating an initial weight with an animal profile may include the application executing one or more initial weight algorithms. The initial weight algorithm may be part of the onboarding algorithm or separate therefrom. Initially, the weight of an animal may be inputted into the system during onboarding or thereafter. Onboarding may take place in a single instance or over multiple instances (e.g., populating an animal profile over different periods). The initial weight algorithm may be stored locally and / or remotely from the computing device. In other words, the initial weight algorithm may be accessible via local and / or cloud-based computing such as to at least be partially executed on a computing device. The initial weight algorithm may include one or more weight entry displays and / or menus being opened on the user interface of the computing device. The initial weight algorithm may automatically prompt the user(s) to input and / or confirm an initial weight of an animal associated with an animal profile. Inputting of the weight may be manual, partially automated, automated, or a combination thereof.

[0066] Manual inputting of an animal weight may include the weight of an animal input by a user into the application. The user may input the weight into a display and / or menu of the application as displayed on an interface of a computing device. An animal profde onboarding display and / or menu may ask a user if they know the weight of a specific animal and / or to input a weight of a specific animal if the weight is known. This weight may then be stored as the animal weight. The animal weight may be stored in one or more databases. The one or more databases may include one or more animal profile databases, weight databases, the like, or a combination thereof.

[0067] Partially automated inputting of an animal weight may include a user placing an animal in and / or on a pet health device (e.g., litter device) having one or more mass sensors and recording the weight. A pet health device may be in communication, such as via a network, with one or more databases. A recorded weight may be automatically transmitted from the pet health device to the database and stored with the animal profile. The application may prompt confirmation by the user of the detected weight on the designated pet health device. For example, a user may select in the application which pet health device they will set the pet on and / or inside of. The one or more mass sensors of the pet health device may detect the additional weight of the animal. The pet health device may transmit the additional weight to one or more processors. One or more same or other processors may generate one or more confirmation notifications to the user via their application. The one or more users may confirm the recognized weight detected by the pet health device is that of the animal placed in and / or on to the pet health device. The detected weight of the animal may be automatically stored in one or more databases. The one or more databases may include one or more animal profile databases, weight databases, the like, or a combmation thereof.

[0068] Automated inputting of an animal weight may include a user confinning a recorded weight is that of a specific animal, specific pet health device, or both and the weight then being automatically associated with the specific animal and / or pet health device. For example, during regular use of a pet health device (e.g., litter device), weight may be detected. An onboarding and / or weight confirmation display in the application may be automatically generated. The confirmation display may be automatically prompted to ask a user to confirm a detected and recorded weight matches a specific animal’s profile. Upon confirmation by the user, the recorded weight may be automatically associated with a specific animal profile. For example, after an animal is detected by one or more sensing devices (e.g.. mass sensors, litter device), a notification may be sent to a user device requesting confirmation of the recorded weight matching to a specific animal or animal profile. The detected weight of the animal may be automatically stored in one or more databases. The one or more databases may include one or more animal profile databases, weight databases, the like, or a combination thereof.

[0069] The method may include one or more sensing devices monitoring for a presence of an animal at a pet health device. The method may include one or more pet health devices being in an idle state. During an idle state, a monitoring algorithm may be executed. The monitoring algorithm may be executed by one or more processors onboard one or more pet health devices (e.g., part of a controller), remote from a pet health device. Onboard may mean the monitoring algorithm is programmed into an individual pet health device. Onboard may allow for the pet health device to retain most or even all of its functionality evenwhen disconnected from a network and / or system. In an idle state, one or more sensing devices detect and / or maintain one or more idle settings of a pet health device. In the idle state, one or more sensing devices may continuously and / or intermittently monitor for presence of an animal at a pet health device. Presence of an animal at a pet health device may include entry of an animal into a litter device, the animal approaching a feeder and / or water, the animal located adjacent to a feeding dish and / or serving bowl, the animal entering a bed and / or crate, the animal be located on a weight scale, the animal located on top of one or more mass sensors (e.g., in a pet health device, part of weight sensing base), and / or the like. One or more sensing devices may include one or more mass sensors, emitting sensors, or both. One or more sensing devices may cooperate together to monitor for the presence of an animal.

[0070] The monitoring algorithm may include one or more sensing devices detecting the presence of an animal at a pet health device. One or more sensing devices and / or processors (e.g., controller) may detect a change in a monitored condition indicating the presence of the animal. The monitoring algorithm may automatically prompt one or more sensing devices to transmit a signal relative to the changed condition to one or more processors, may prompt one or more processors to detect a changed condition in a signal from one or more sensing devices, or both. The one or more processors may determine the presence of the animal. The one or more sensing devices may include one or more mass sensors, emitting sensors, or both. The one or more sensing devices may be configmed to differentiate between an animal approaching the pet health device, stepping on to the pet health device, and an animal actually entering and / or using a pet health device.

[0071] One or more sensing devices detecting the presence of an animal at a pet health device may include one or more emitting sensors detecting the presence of an animal. One or more emitting sensors may monitor for an emitting beam to be interrupted or otherwise changed. One or more emitting sensors may have an emitting beam interrupted, projecting distance shortened, and / or the like, indicating the presence of an animal. The one or more emitting sensors may detect the presence of an animal similar to how the one or more laser sensors detect the presence as disclosed in PCT Publication No.: W02020 / 219849, incorporated herein by reference in its entirety for all purposes.

[0072] One or more sensing devices detecting the presence of an animal at a pet health device may include one or more mass sensors detecting the presence of the animal. One or more mass sensors may monitor for a weight change and / or weight. One or more mass sensors may detect an increased weight as detecting the presence of an animal. The mass sensors may monitor for a weight change, such as if not tared to zero during idle. The mass sensors may monitor for a weight, such as if tared to zero during idle. If tared to zero, the weight would be indicative of the weight change. Whether looking for a weight change or a weight, this value may be referred to as a monitored weight, animal weight, and / or detected weight. The monitoring algorithm may automatically prompt the one or more mass sensors to transmit the mass signal to one or more computing devices (e.g., local controller, remote server processor), may detect the changed signal at the computing device, or both to determine the presence of an animal by the monitored weight. The one or more mass sensors may detect the presence of the animal at a pet health device similar to the mass sensor(s) in US Patent Nos. 8,757,094, 9,422,185, 11,399,502, and 11,523,586, and PCT Publication No. WO2020 / 219849: all of which are incorporated herein by reference in their entirety.

[0073] One or more sensing devices detecting the presence of an animal at a pet health device may include one or more sensing devices cooperating with one or more other sensing devices to detennine the presence of the animal. One sensing device(s) may function to confirm detection by the other sensing device(s). For example, one or more emitting sensors may detect entry and / or presence of an animal to a pet health device and one or more mass sensors may detect an increased mass during entry and / or presence of the animal. The increased weight detected by the mass sensor(s) may function to confirm the detected presence by the emitting sensor(s) and / or vice-versa, the detected presence by the emitting sensor(s) may function to confirm the detected presence by the mass sensor(s) sensed by the weight change.

[0074] The monitoring algorithm may include an animal detection threshold. A detection threshold is a weight indicative of an animal being present at a pet health device. The animal detection threshold may be part of a detection threshold rule part of the monitoring algorithm. The detected weight is compared to the detection threshold. If the detected weight is greater than the detection threshold, it is determined that an animal is present at the pet health device. If the detected weight is not greater than the detection threshold, it is determined that an animal is not located at the pet health device.

[0075] One or more sensing devices may detect use of a pet health device by an animal by detecting the presence of animal over an initial threshold time period. Detecting use of a pet health device may be achieved by execution of a use algorithm. The use algorithm may be executed by one or more processors onboard one or more pet health devices (e.g., part of a controller), remote from one or more pet health devices (e.g., cloud computing), or both. In other words, the use algorithm may be programmed into an individual pet health device, remote from a pet health device, or both. Detection of an animal by one or more sensing devices over an initial threshold time period may indicate the animal is using the pet health device in a manner intended. Time may be measured and associated with a mass signal via a controller of a pet health device. Detection of an animal for greater than an initial threshold time period by one or more sensing devices at a litter device, feeder, water dispenser, resting device, and / or the like may indicate the animal using the pet health device for its intended purpose as opposed to approaching and / or stepping into the pet health device out of curiosity. Intended purpose may mean waste elimination, eating, drinking, resting, and / or the like. The animal may be detected by the one or more sensing devices substantially continuously and / or intermittently. The initial threshold time period may be a time which is suitable for differentiating between approaching a pet health device as opposed to using the pet health device as intended. The initial threshold time period may be about 3 seconds or greater, about 5 seconds or greater about 8 seconds or greater, or even about 10 seconds or greater. The initial threshold time period may be about 30 seconds or less, about 25 seconds or less, about 20 seconds or less, or even about 15 seconds or less, or even about 12 seconds or less. For example, an initial threshold time period may be about 5 seconds to about 15 seconds, about 8 seconds to about 12 seconds, or even about 9 seconds to 11 seconds. For example, an initial threshold time period may be set at 10 seconds.

[0076] The method may include recording a weight of the animal. Recording of the weight of the animal may be achieved by execution of a weighing algorithm. The weighing algorithm may be executed by one or more processors onboard one or more pet health devices (e.g., part of a controller). While the weight ofan animal is detected by one or more mass sensors, a plurality of intermittent readings may be temporarily stored. Storage may be on or more local and / or remote storage mediums. One or more detected weight readings may be transmitted to one or more databases. The one or more databases may include one or more animal weight databases. The transmission may include a timestamp of when the weight reading was detected, when the animal’s presence was detected, and / or when the animal’s departure was detected. The transmission may include an identity of the pet health device from which the weight reading was detected (e.g.. the pet health device used by the animal). The one or more detected weight readings may include a single weight or a plurality of weights related to the use instance of a pet health device and the animal. The single weight may be a detected weight and / or a derived weight. The single weight may be a maximum weight value (e.g., peak weight), a minimum weight value, a central tendency weight value (e.g.. mean, mode, median), and / or the like. The single weight may be a weight value that is recorded after the initial threshold time period. The single weight may be a weight value recorded prior to departure of the animal from the pet health device.

[0077] One or more sensing devices may detect the departure of an animal from a pet health device. Detecting departure of an animal may be achieved by execution of a departure algorithm. The departure algorithm may be executed by one or more processors onboard one or more pet health devices (e.g., part of a controller). The departure algorithm may commence once the monitoring algorithm detects presence of an animal, the use algorithm detects presence over an initial threshold time period, or both. One or more sensing devices may detect a change in a monitored condition indicating departure of the animal. One or more sensing devices may transmit a signal relative to a change condition to one or more processors which determine the departure of the animal. One or more mass sensors may detect a decreased weight. One or more emitting sensors may have their emitting beam no longer broken. Once the departure of the animal is determined, a weight may be recorded.

[0078] The departure algorithm may include an animal detection hysteresis threshold. The hysteresis threshold may be a weight indicative that an animal is no longer present at a pet health device. The hysteresis threshold may be part of a hysteresis threshold rule part of the departure algorithm. Once the animal is detected, the one or more mass sensors may monitor for the detected animal weight to drop below the hysteresis threshold. Once the detected animal weight drops below the hysteresis threshold, it is determined the animal has departed the pet health device. The departure algorithm may instruct the one or more mass sensors and / or controllers to monitor for the animal weight to drop below the hysteresis threshold continuously or intermittently after an animal’s presence is detected (e.g., animal weight exceeds detection threshold).

[0079] The method may include automatically associating (e.g., pairing) the recorded weight of the animal with an activity of the animal. Associating the weight with an activity7may be achieved by execution of a weight storage algorithm. The weight storage algorithm may be part of or separate from the weighing algorithm. The weight storage algorithm may be executed by one or more processors onboard one or more pet health devices (e.g.. part of a controller), remote from one or more pet health devices (e.g., cloud computing), or both. In other words, the weight storage algorithm may be programmed into anindividual pet health device, remote from a pet health device, or both. The recorded weight may be associated with a pet health device and timestamp. Based on the pet health device associated with the recorded weight, an activity of the animal may be determined. For example, if die recorded weight is associated with a litter device, the activity may be determined as waste elimination. For example, if the recorded weight is associated with a feeder, the activity may be determined as eating food. For example, if the recorded weight is associated with a water dispenser, the activity may be determined as drinking water. For example, if the recorded weight is associated with a resting device, the activity may be determined as resting and / or sleeping. The activity of the animal may also be recorded in one or more databases and associated with the recorded weight entry. The activity of the animal may be stored in one or more animal weight databases or other similar databases.

[0080] The method may include automatically determining and associating an identity of the animal with the weight of the animal, and optionally, the activity of the animal. Determining the identity based on weight may be achieved by execution of a weight identification algorithm. The weight identification algorithm may be part of or separate from the weighing algorithm. The weight identification algorithm may be executed by one or more processors onboard one or more pet health devices (e.g., part of a controller), remote from one or more pet health devices (e.g., cloud computing), or both. In other words, the weight identification algorithm may be programmed into an individual pet health device, remote from a pet health device, or both. Associating a weight of animal and / or activity with an identity of an animal may be useful to keep track of an animal’s weight, an animal’s behaviors across one or more pet health devices, or a combination thereof. A recorded weight may be compared to one or more threshold weight values. One or more threshold weight values may be associated with one or more animal identities. For example, one or more animal profile databases, animal weight databases, or both may have a threshold weight value associated with each animal profile. Each animal profile may be associated with a specific animal and their identity. A recorded weight value may be substantially equal to a threshold weight value which corresponds to a specific animal profile and thus correlates to a specific animal identity. The recorded weight may be compared to all threshold weight values part of the system, threshold weight values associated with a specific region (e.g.. same city), threshold weight values associated with a specific owner, account, and / or home address, threshold weight values associated with a specific pet health device, the like, or any combination thereof. To determine a same region, owner, account, and / or home address of the recorded weight value to the threshold weight values, the recorded weight value is part of a data entry also including registration information about the pet health device from which the recorded weight value is derived. The region, owner, account, home address, specific identifier, and / or the like of the pet health device may be matched with a region, owner, account, home address, specific pet health device identifier, and / or the like of a weight threshold value and / or animal profile. It is also possible that each pet health device and its onboard controller (e.g., processors, storage medium, databases), compares the recorded weight value to all locally onboard threshold weight values. Identifying an animal based on weight may also include searching within an acceptable tolerance level. A tolerance level may account for natural weight fluctuations which occur throughout the day in an animal, accuracy of a mass sensor(s), or both. A tolerance level may beabout 0.1 lbs. or greater, 0.2 lbs. or greater, or even 0.5 lbs. or greater. A tolerance level may be about 1 lb. or less, about 0.8 lbs. or less, or even about 0.7 lbs. or less. For example, a tolerance level may be about + / - 0.5 lbs.

[0081] An example of the weight identification algorithm may be as follows. A detected weight of 12.4 lbs. is recorded and may be used as a search to look for an animal profile with a substantially matching weight of 12.4 lbs. The animal profile which includes or is associated with a substantially matching weight is determined as the identity of the animal associated with the weight. One or more filters may be applied to a database (e.g., animal profile database, animal weight database) prior to searching for the substantially similar 12.4 lbs. For example, a filter for user profiles, user accounts, device profiles, location, region, etc. For example, each device may have its own profile (e.g., name, serial number, unique identifier). Such a filter may aid in only searching for animal profiles applicable to a user, home, animal, pet health device and / or the like. It is also possible that as opposed to searching an overall database, more local databases may be provided. It is even possible a locally stored database (e.g., on the pet health database) is used. In other words, a global database may exist which collects all data (e.g., all animal profdes), while a plurality of local databases may exist with respect to each user, device, home, etc. Data from one database may be fed to the other.

[0082] The identity of the animal may refer to any identifying data useful for an owner to ascertain the identity of their animal and part of an animal profile. The identify may include a name, image, species, breed, age, and / or the like of the specific animal.

[0083] The method may include notifying one or more users of an identity, weight, and / or activity of the animal. The user interface of a computing device may be a useful means of keeping a user informed of the habits and / or weight of a specific animal, and even more so distinguishing between the habits and / or weight of multiple animals in a single household. Notifying may be achieved by execution of a notification algorithm. The notification algorithm may be executed by one or more processors onboard one or more pet health devices (e.g.. part of a controller), remote from one or more pet health devices (e.g., cloud computing), or both. In other words, the notification algorithm may be programmed into an individual pet health device, remote from a pet health device, or both. Executing the notification algorithm may include updating the display of an animal profile in application on a user interface. The display of the animal profile may be updated to include the most recent weight of an animal, an updated central tendency value of the weight of the animal, a timestamp associated with when the presence of the animal was last detected, update a history of the animal’s use of one or more pet health devices, the like, or a combination thereof. The notification may be passive, active, or both. A passive notification may include automatically notifying upon a user opening the application (e.g., pet health application). An active notification may include automatically notifying via a push-notification.

[0084] The method may include updating one or more trends associated with an animal. The one or more trends may be updated by execution of one or more trend algorithms. One or more trend algorithms may be executed by one or more processors onboard one or more pet health devices (e.g., part of a controller), remote from one or more pet health devices (e.g., cloud computing), or both. In other words,the one or more trend algorithms may be programmed into an individual pet health device, remote from a pet health device, or both. One or more trend algorithms may include determining one or more trends relative to an animal’s weight, waste elimination, eating, drinking, and / or the like. One or more trend algorithms may determine one or more central tendency values relative to an animal’s weight, waste elimination, eating, drinking, resting, and / or the like. One or more trend algorithms may include determining rates of change and comparing to threshold rates of change, such as disclosed in PCT Application No.: PCT / US2024 / 021340 file don March 25. 2024. incorporated herein by reference in its entirety for all purposes. The newly recorded weight, detected activity associated with the weight, and / or animal’s identity may be used to update one or more trends. One or more trends may be displayed over a period of time on a user interface. The one or more trends may be displayed as one or more numerical values, as a chart, the like, or a combination thereof. Numerical values may include central tendency values, rates of change, the like, or a combination thereof. A chart may include a scatter plot, line graph, bar chart, pie chart, bubble chart, histogram, the like, or any combination thereof. A chart may include a trendline therein. A period of time may be 1 day or greater, 3 days or greater, 5 days or greater, or even 7 days or greater. Aperiod of time may be about 14 days or less, 12 days or less, or even 10 days or less. For example, the period of time may be 1 week (e.g., 7 days). One or more central tendency values may include how often an animal eliminates waste over a period of time, how often and / or how much an animal consumes food over a period of time, how often and / or how much an animal drinks water over a period of time, and / or the like.

[0085] Data may be stored for a period greater than what is displayed. For example, weight recordings, usage, and / or other detection of an animal at one or more health devices may be stored for 1 month or greater, 1 year or greater, or even 3 years or greater.

[0086] The method may include inquiring as to a new animal if a new weight is detected. In an instance where a user does not onboard an animal profile for a new pet in the household before the new pet uses a pet health device, a notification may be generated on a screen. This inquiry may be executed as part of the weight identification algorithm. If a new weight which is substantially distinct from any weights associated with any known animal profiles is detected, the notification may be a new pet detected notification. Substantially distinct may mean not equal to a weight of existing animal profiles associated with a user, outside of tolerance levels of the known weight of existing animal profiles, or both. If a user confirms a new' animal is present, the user may be prompted to an onboarding screen to create the new' animal profile.

[0087] The method may include automatically disabling the association of weights with specific animals, animal identification based on weight, or both. If a user has multiple animal profiles within their account but weight recordings are too similar to discern the animal by weight, association and / or identification may be automatically disabled. Disabling may result from execution of a similarity algorithm. Too similar may mean that the weights are equal to one another, have overlapping tolerances, are within a certain weight from one another, or any combination thereof. Overlapping tolerances may mean the weights are within + / - 0.01 to 0.5 lbs. of one another. Within a certain weight may mean up to 0.2 lbs. or greater, 0.5 lbs. or greater, 1 lb. or greater. Within a certain weight may mean 3 lbs. or less. 2 lbs. or less, or even 1lb. or less. In the case weight association and / or identification are disabled, weight may still be recorded. The weight may then be associated with a generic health device profde. In other words, a litter device may have its own profile as compared to each animal having their own profile. Upon disabling, one or more pop-up notifications may be generated and displayed on a user interface. The pop-up notification may alert a user that weight association and / or identification has been disabled, a health device profile is being used, or both.

[0088] The method may include automatically disabling weight recording, associating, and / or identifying. The disabling may result from execution of a sensor issue algorithm. If a recording weight varies greatly from any expected weight over a single occurrence or multiple occurrences, weight recording, associating, and / or identify ing may be disabled. A pop-up screen may be generated alerting a user that weight recording, associating, and / or identifying is disabled. The pop-up screen may provide information to a user as to why disabling has occurred. For example, the pet health device with one or more mass sensors therein may not be on a flat surface (e.g.. located on carpet instead of solid floor), the pet health device may be crooked (e.g., tilted by another animal or child), or both. If weight recording is disabled, usage history may remain enabled and / or also disabled. Usage may be based on any one or more sensing devices detecting the presence of an animal, one or more cleaning cycles, and / or the like.

[0089] The method may include updating one or more threshold weights of one or more animals. The weight of an animal may fluctuate, decrease, and / or increase over tune. For example, the weight of an animal may increase if the animal is adopted by an owner in its youth. As another example, the weight of an animal may decrease as the animal becomes elderly. And as a further example, the weight may fluctuate naturally due to eating and / or waste elimination habits, changing weather seasons (e g., heavier in winter), medications, and / or the like. One or more updating algorithms may be executed to update one or more threshold weights. One or more updating algorithms may include one or more machine learning algorithms. One or more updating algorithms may include one or more automated algorithms, teclmiques, and / or methods which function to organize and group comparable values with one another, create clusters, identify centroid values, convert centroid values to threshold weight values, assign threshold weight values to specific animal profiles, the like, or any combination thereof. The one or more updating algorithms may include one or more clustering algorithms. The one or more clustering algorithms may include one or more centroid-based clustering algorithms. The one or more clustering algorithms may determine a centroid of a cluster of recorded w eight values. A centroid weight value may be recognized as a threshold weight value. A threshold weight value may be replaced with a newly determined threshold weight value. The one or more updating algorithms may be executed on a recurring frequency. The recurring frequency may be at least every single day or less often, every two days or less often, or eveiy- three days or less often. The recurring frequency may be at least every month or more often, every twenty days or more often, every ten days or more often, every seven days or more often, or even every five days or more often. For example, the recurring frequency may be about every two days to about every seven days. Updating the threshold values too infrequently may result in the threshold value lagging too far behind a change in the actual weightof an animal and then being unable to accurately identify an animal. This may most often occur during periods of quick growth or decline.

[0090] Each step of the method which is not an input by a user may be automatically executed. Automatic execution may be by one or more processors. Automatic execution may occur based on one or more prior sensed conditions, determined conditions, results from an algorithm, and / or the like. Any suitable processor may execute a part of or all of a method, algorithm, and / or process.

[0091] The teachings herein may expand upon and / or be combined with those in US Provisional Application Nos. 63 / 4911,751, filed on March 23. 2023. and 63 / 490.990. filed on March 17, 2023; and PCT Application Nos.: PCT / US2024 / 021340, filed on March 25, 2024 and PCT / US2024 / 020406, filed on March 18, 2024, all of which are incorporated herein by reference in their entirety for all purposes.

[0092] Illustrative Examples

[0093] FIG. 1 illustrates a computing device 1. The computing device 1 is a personal computing device 3. The computing device 1 is a mobile phone 5. The computing device 1 includes a screen 7 which displays a user interface 9 (e.g., graphical user interface, GUI). The computing device 1 executes an application 10. The application 10 is a pet health application 12. The pet health application 12 is able to display a plurality7of animal profiles 14 or summaries 16 thereof. Each animal profile summary 16 illustrates an image 18, name 20, breed 22, gender 24, and age 26 associated with an animal 28. Also displayed with the animal profile summary 16 is a weight 30 associated with the animal 28. The weight 30 may be the most recent weight 32 (as shown), or any other derived value, such as an average weight, daily weight, weekly weight, max weight, and / or the like. The weight 30 may be associated with a weight of tire animal 28 measured by one or more mass sensors (not shown) of one or more pet health devices (not shown) and / or derived therefrom.

[0094] FIG. 2 illustrates a pet health application 12 executed by a computing device 1. The pet health application 12 is able to display an animal profile 14. The animal profile 14 includes an image 18, name 20, breed 22, gender 24, age 26. The animal profile 14 may illustrate a time 34 when an animal 28 was last identified at one or more pet health devices (not shown). This time may be determined by when the animal 28 was last identified, such as by their presence and measured weight at a pet health device (not shown). The animal profile 14 may illustrate a weight 30. The weight 30 as illustrated is an average weekly weight 36, but may be any other weight value, recorded or derived. Based on the identify of the animal, such as weight, tendencies of the animal 28 may be able to be derived. For example, waste elimination frequency vahie(s) 38 and / or consumption (e.g., eating and / or drinking) frequency values 40.

[0095] FIG. 3 illustrates an animal profile database 200. An animal profile database 200 may be a local database (e.g., local computing), semi-local (e.g.. edge computing) and / or global database (e.g.. cloud computing). A local database may be a database for animals specific to a location or subset of locations (e.g., pets in a home or shelter). A semi-local database may7be a database of a number of animals stored on a remote computing device but limited to a specific region or other determining factor. A global database may be a database of all or a variety of animals available stored on a remote computing device.

[0096] The animal profile database 200 may be a single database or a plurality of databases. Data across multiple databases may be linked to an animal and / or the animal profile via a data key 206 or similar. For example, a weight database (not shown) may be separate from the animal profile database 200.

[0097] The animal profile database 200 may include a plurality of data entries 204 associated with each animal 28 stored therein and related to an identify of the animal 1. The data entries 204 per animal may include one or more data keys 206. The data key 206 may be useful for correlating data from one database to data in another database. The data entries 204 may include one or more of the following: images of the animal 18. identifiers or data associated with an identifier 210. respective given names of the animal 20. species of the animal 214, breed of the animal 22, gender of the animal 24, weight of the animal 30, date of birth of the animal 222, age of the animal 26, an account and / or owner of the animal 226, a location of the animal 228, and / or the like.

[0098] FIG. 4 illustrates an exemplary’ animal weight database 78. The animal weight database 78 may store a plurality of weights 30. Each weight 30 may be a recorded or derived weight value 76. Each weight 30 may be associated with a timestamp 58, account / owner 226. pet health device 102, and even a location 228 (not shown). The account / owner 226 and / or location 228 may be derived by the identity’ of the specific health device 102, such as in a device registration database (e.g., database which stores registration data for each pet health device 102 part of the system 100). Although the animal weight database 78 illustrates data associated with a single account 226 (e.g., “Bob"), the database 78 may store data across a number of accounts, even all of the accounts part of a system 100.

[0099] FIG. 5 illustrates one of the displays 11 of an application 10. The application 10 may be a pet health application 12. The display 11 illustrates an animal weight profile 42. The animal weight profile 42 is for a specific, individual animal 28. The identity of the animal 28 is illustrated by the name 20 but can also be illustrated by their image 18 or other identifying information.

[0100] The animal weight profile 42 provides for a chart 44. The chart 44 illustrates different measured weight 30 or trends of an animal 28 at diflerent times or over periods of measurement. The chart 44 is illustrated as a scatter plot 46. As illustrated, the values on the scatter plot 46 are daily weight 48. The daily weight 48 are trend values over a daily period (e.g., 12 am - 11:59 pm). As an alternative, each value illustrated may be each individual recorded weight. The chart 44 also includes a trend line 50.

[0101] The display 11 of the animal weight profile 42 illustrates a weight 30. The weight 30 as shown is a central tendency value 52.

[0102] The display 11 of the animal weight profile 42 displays a weight history 54. The weight history 54 provides for a weight recording 56 at each individual point in time an animal has been detected and had their weight measured by a sensing device (e.g., mass sensors, scale). Each weight recording 56 is also associated with a timestamp 58.

[0103] FIGS. 6 and 7 illustrate a system 100. The system 100 includes a plurality7of pet health devices 102. The pet health devices 20 include one or more litter devices 500, water dispensers 600. feeders 700. The system 100 also includes one or more computing devices 1. The computing device(s) 12 may be personal computing devices 3. Personal computing devices 14 may include mobile phones 5, tablets 6,laptops (not shown), and / or the like. The pet health device(s) 102 and / or personal computing devices 3 may all be in communication (e.g., two-way) with another computing device 1, such as a remote computing device 104. Communication may be via one or more communication hubs 106 (e.g., router, antenna). The system 100 may be set up as a cloud-computing system 108 or an edge-computing system 110. It is also possible that edge-computing may do most of the computing on onboard controllers 112 of the pet health devices 20. then transmit to a cloud-computing system 108.

[0104] FIGS. 8 and 9 illustrate a litter device 500 as an exemplary pet health device 102. The litter device 500 is an automated litter device. The litter device 500 includes a chamber 502. The chamber 502 defines an entry opening 518. The chamber 502 is partially covered by a bonnet 522. The chamber 502 is rotatably supported on a base 504. Inside the chamber 502 is a septum 506 which includes a sifting portion 508. During a cleaning cycle, the chamber 502 rotates about its rotational axis AR and the sifting portion 508 sifts through litter 510 to segregate waste for disposal. The base 504 includes a waste receptacle 512. The waste receptacle 512 is shown as a waste drawer 514. The segregated waste exists the chamber 502 and is stored in the waste receptacle 512 for later disposal. The litter device 500 includes a bezel 516. The bezel 516 is located about the entry opening 518. The bezel 516 is statically affixed such that it remains fixed while the chamber 502 rotates. For example, by being affixed to the boimet 522 and base 504.

[0105] The bezel 516 supports one or more sensing devices 60. The sensing device(s) 60 may include one or more laser sensors 62. The sensing device(s) 60 have a line of sight 524 into at least the interior of the chamber 502. The sensing device(s) 60 may also have a line of sight 526 into the waste receptacle 512, such as when a waste opening 528 is rotated during a cleaning cycle and aligns with the waste receptacle 512. The axis of rotation AR is tilted compared to a horizontal plane HP (e.g., ground, plane parallel to ground). This tilting allows for the entry opening 18 and bezel 516 to also be tilted. This angle allows for the sensing device(s) 60 to have line of sight into the interior of the chamber 502 as opposed to solely across the entry opening 518.

[0106] The one or more sensing devices 60 includes one or more mass sensors 64. The one or more mass sensors 64 may be located anywhere below the chamber 502 such as to detect the weight of the animal within the chamber 502. The one or more mass sensors 64 may be located at the base 504.

[0107] FIG. 10 illustrates a pet health device 102, a water dispenser 600. The water dispenser 600 is an automated water dispenser. The water dispenser 600 includes a serving bowl 602. The water dispenser 602 includes a fresh water tank 604 and a used water tank 606. Water is then able to exit via a spout 608 into the serving bowl 602. The water dispenser 600 rests atop a sensing device 60. The sensing device 60 is a weight sensing base 66. The weight sensing base 66 may include one or more mass sensors 64 therein or at its bottom. The weight sensing base 66 may be configured similar to a weight scale. The weight sensing base 66 is located such that a portion extends beyond the front of the water dispenser 600. Specifically, the weight sensing base 66 is located in front of the serving bowl 602. The weight sensing base 66 is located where an animal would typically stand or sit while consuming water from the serving bowl 602.

[0108] FIG. 11 illustrates a pet health device 102, a feeder 700. The feeder 700 is an automated feeder. The feeder may be beneficial in presenting dry (e.g., granular) food to an animal. But the concept may beuseful with a feeder beneficial in presenting wet food to an animal. The feeder 700 includes a housing 702. Inside of the housing 702 is a hopper 704. The hopper 704 stores the food for future dispensing. The feeder 700 includes a feeding dish 706. The feeder 700 may or may not include a lid 708. The feeding dish 706 may then be able to be covered by a lid 708. Located in front of the feeder 700 is a sensing device 60. The sensing device 60 is a weight sensing base 66. The weight sensing base 66 may include one or more mass sensors 64 therein or at its bottom. The weight sensing base 66 may be configured similar to a weight scale. The weight sensing base 66 is located in front of the feeding dish 706. The weight sensing base 66 is located where an animal would typically stand or sit while consuming food from the feeding dish 706.

[0109] The sensing device 60. as illustrated in FIGS. 9 and 10, may either include its own controller, including a communication module, or be in electrical communication with the pet health device 102.

[0110] FIG. 12 illustrates an exemplary plot 70. The plot 70 is shown as a jitter plot 72. The jitter plot 72 is used to better visual the distribution of weight values 74. In the jitter plot 72, weight values 74 are onedimensional and plotted along the x-axis. The weight values 74 are randomly shifted vertically along the y - axis. This random shifting has no meaning, other than aiding in separating out the weight values 74 for easier visualization and minimizing overlap of the weight values 74 on the plot 70.[oni] In the plot 70, there are a plurality of weight values 74. The weight values 74 are derived from the weighing of five animals via mass sensors 64 (not shown). The weight values 74 may be derived from a single pet health device 102 (not shown) or a plurality. For example, a single automated litter device in a home or two automated litter devices in a home. As another example, two automated litter devices, two automated feeders, and one automated water dispenser, all associated with their own mass sensors, in a home. The weight values 74 may be derived from a single location (a single home), a region, or all data collected into the system.

[0112] A clustering algorithm is automatically executed on the weight values 74. The clustering algorithm may be a centroid-based clustering algorithm. The clustering algorithm may determine a centroid of a cluster of weight values 74. The centroid may be an arithmetic mean. The clustering algorithm may determine individual identifying weight values 76. Each identifying weight value 76 may be associated with an individual animal 28 (not shown). As an example, the clustering algorithm determines there are five centroids from the weight values 74 and thus five separate animals 28 (not shown) and five, associated individual identifying weight values 76.

[0113] FIG. 13 illustrates a weight recording chart. The chart illustrates intermittent or continuous weight values 74 detected by one or more mass sensors 64 (not shown) of a pet health device 102 (not shown). The y-axis represents the weight value while the x-axis represents time. Once the presence of an animal 28 (not shown) is detected by one or more sensing devices 60 (not shown) continuously’ for a first time period Tl. the one or more mass sensors 64 may begin to record the detected mass over a second time period T2. The second time period T2 ends when the animal 28 (not shown) departs the pet health device 102 (not shown) and is no longer detected by one or more sensing devices 60 (not shown). A weight value 74, either recorded or derived from the recorded weight values, may be the weight value 74 associated with that particular visit to a pet health device 102 and the animal 28. The weight value 74 may be a peak (e.g., maximum) weightvalue, miniminn weight value, a central tendency value (mean, mode, median), and / or the like. This weight value 74 may then be transmitted from the one or more mass sensors and / or controllers to one or more animal weight databases 78 (not shown).

[0114] FIG. 14 illustrates the process of onboarding one or more animal profiles via an onboarding algorithm 250. The onboarding algorithm may be executed upon a user opening an application, such as a pet health application. The user may be prompted to enter a new animal quantity input. The user may then create and / or edit one or more animal profiles. A display and / or menu similar to at least a portion of the display shown in FIGS. 1 and 2 may be similar to at least part of a creation and / or editing display for an animal profile. The fields may be blank as opposed to being filled out, prior to the user entering the information. The onboarding algorithm includes associating an animal weight with an animal profile. The weight may be associated with the animal profile via manual input, partially automated input, and / or automated input. This weight may be considered an initial threshold weight. This may conclude the onboarding of one or more animal profiles.

[0115] FIG. 15 illustrates a method of identifying an animal based on weight 300. Steps of the sequence, although shown in consecutive order, may occur in parallel or in a different sequence as feasible. The method of identifying an animal based on weight 300 starts with execution of a monitoring algorithm. During the monitoring algorithm, one or more sensing devices monitor for the presence of an animal at a pet health device. The monitoring algorithm may look for a detection threshold rule to be met to determine the animal is present. Once the animal arrives and is present at the pet health device, the monitoring algorithm detects and determines the presence of the animal at the pet health device. Once detected, a use algorithm is executed. The use algorithm determines that the animal is using the pet health device as intended. Once presence is detected and / or use is detected, a weighing algorithm is executed. During the weighing algorithm, a weight of the animal using the pet health device is determined and stored (e.g., recorded). Once presence and / or use is detected, a departure algorithm is also executed. During the departure algorithm, one or more sensing devices monitor for the departure of the animal from the pet health device. The departure algorithm may look for a hysteresis rule to be met to determine the animal has departed. Once the animal departs the pet health device, a weight storage algorithm and / or a weight identification algorithm may be executed. The weight storage algorithm and weight identification algorithm may be executed in any sequence relative to the other, including in parallel. The weight storage algorithm may associate (e.g.. pair) a weight with an activity of the animal. The weight identification algorithm may identify an animal based on weight. Once an activity and / or identification is determined, a notification algorithm may be executed. The notification algorithm may be executed promptly upon an identification and / or activity being determined, upon a user opening a pet health application, or both. The notification algorithm may generate a passive and / or active notification. One an activity and / or identification is determined, a trend algorithm, updating algorithm, or both may be executed. On the other hand, these may be executed on a pre-determined frequency. A trend algorithm may function to update one or more trends associated with a specific animal. One or more of these trends may be updated on an application and viewable via a user interface. An updating algorithm may update one or more weight threshold values. Theupdated weight threshold value may be useful for future executions of the method for identifying an animal based on weight.

[0116] Unless otherwise stated, any numerical values recited herein include all values from the lower value to the upper value in increments of one unit provided that there is a separation of at least 2 units between any lower value and any higher value. As an example, if it is stated that the amount of a component, a property, or a value of a process variable such as. for example, temperature, pressure, time and the like is. for example, from 1 to 90, preferably from 20 to 80, more preferably from 30 to 70. it is intended that intermediate range values such as (for example, 15 to 85, 22 to 68, 43 to 51, 30 to 32 etc.) are within the teachings of this specification. Likewise, individual intermediate values are also within the present teachings. For values which are less than one. one unit is considered to be 0.0001, 0.001. 0.01 or 0.1 as appropriate. These are only examples of what is specifically intended and all possible combinations of numerical values between the lowest value and the highest value enumerated are to be considered to be expressly stated in this application in a similar manner.

[0117] Unless otherwise stated, all ranges include both endpoints and all numbers between the endpoints. The use of “about’’ or “approximately” in connection with a range applies to both ends of the range. Thus, “about 20 to 30” is intended to cover “about 20 to about 30”, inclusive of at least the specified endpoints.

[0118] The terms “generally” or “substantially” to describe angular measurements may mean about + / - 10° or less, about + / - 5° or less, or even about + / - 1° or less. The terms “generally” or “substantially” to describe angular measurements may mean about + / - 0.01° or greater, about + / - 0.1° or greater, or even about + / - 0.5° or greater. The terms “generally” or “substantially” to describe linear measurements, percentages, or ratios may mean about + / - 10% or less, about + / - 5% or less, or even about + / - 1% or less. The terms “generally” or “substantially” to describe linear measurements, percentages, or ratios may mean about + / - 0.01% or greater, about + / - 0.1% or greater, or even about + / - 0.5% or greater.

[0119] The disclosures of all articles and references, including patent applications and publications, are incorporated by reference for all purposes. The term “consisting essentially of’ to describe a combination shall include the elements, ingredients, components, or steps identified, and such other elements ingredients, components or steps that do not materially affect the basic and novel characteristics of the combination. The use of the terms “comprising” or “including” to describe combinations of elements, ingredients, components, or steps herein also contemplates embodiments that consist essentially of, or even consist of the elements, ingredients, components or steps. Plural elements, ingredients, components, or steps can be provided by a single integrated element, ingredient, component, or step. Alternatively, a single integrated element, ingredient, component, or step might be divided into separate plural elements, ingredients, components, or steps. The disclosure of “a” or “one” to describe an element, ingredient, component, or step is not intended to foreclose additional elements, ingredients, components, or steps.

[0120] It is understood that the above description is intended to be illustrative and not restrictive. Many embodiments as well as many applications besides the examples provided will be apparent to those of skill in the art upon reading the above description. The scope of the invention should, therefore, be determined not with reference to the above description, but should instead be determined with reference to the appendedclaims, along with the full scope of equivalents to which such claims are entitled. The disclosures of all articles and references, including patent applications and publications, are incorporated by reference for all purposes. The omission in the following claims of any aspect of subject matter that is disclosed herein is not a disclaimer of such subject matter, nor should it be regarded that the inventors did not consider such subject matter to be part of the disclosed inventive subject matter.

Claims

CLAIMSWhat is claimed is:Claim 1. A method for identifying an animal using one or more pet health devices comprising: a) monitoring for a presence of the animal at the one or more pet health devices by one or more sensing devices; b) detecting the presence of the animal at the one or more pet health devices by the one or more sensing devices; c) recording a weight of the animal as detected by the one or more sensing devices, wherein the one or more sensing devices include one or more mass sensors, and the weight once recorded is a recorded weight; d) detecting a departure of the animal from the one or more pet health devices by the one or more sensing devices; e) automatically identifying the animal by automatically associating the recorded weight with an identify of the animal by matching the recorded weight with a substantially similar weight associated with an animal profile.Claim 2. The method of Claim 1, wherein the one or more sensing devices include one or more emitting sensors.Claim 3. The method of Claim 2, wherein both the one or more emitting sensors and the one or more mass sensors monitor for and detect the presence of the animal at the one or more pet health devices.Claim 4. The method of Claim 1, wherein the one or more mass sensors monitor for the presence and detect the presence of the animal at the one or more pet health devices.Claim 5. The method of Claim 1, wherein the one or more pet health devices include one or more litter devices, feeders, water dispensers, resting devices, weight scales, the like, or a combination thereof.Claim 6. The method of Claim 1. wherein the one or more pet health devices include one or more litter devices, feeders, water dispensers, resting devices, the like, or a combination thereof.Claim 7. The method of Claim 1. wherein the one or more pet health devices include and / or are in communication with one or more non-transitory storage mediums which include one or more animal profile databases stored therein.Claim 8. The method of Claim 7, wherein the one or more animal profile databases include one or more animal profile records; and wherein each of the animal profile records includes information related to a specific animal, including: a name, an image, an age. a gender, a weight, a species, a breed, a date of birth, health issues, medications, known eating habits, a household, a user account, an address, a language preference for understanding verbal commands, or a combination thereof.Claim 9. The method of Claim 8, wherein the each of the animal profile records includes the image, the name, the species, the breed, the age and / or the date of birth, the gender and the weight of the specific animal.Claim 10. The method of Claim 1, wherein the one or more pet health devices include and / or are in communication with one or more non-transitory storage mediums which include one or more animal weight databases stored therein.Claim 11. The method of Claim 10, wherein the one or more animal weight databases store a history' of weight records for recorded weights of one or more animals.Claim 12. The method of Claim 11, wherein the one or more animal weight databases include one or more weight records; and wherein each of the weight records includes a recorded weight, a timestamp from when the recorded weight was detected, and a pet health device where the recorded weight was detected.Claim 13. The method of Claim 1. wherein the detecting the presence of the animal is also determined by one or more controllers in conjunction with the one or more sensing devices.Claim 14. The method of Claim 13. wherein the one or more mass sensors detect the weight of the animal which is greater than a detection threshold; and wherein the one or more processors determine that the animal is present based on the weight being greater than the detection threshold.Claim 15. The method of Claim 1. wherein the method includes detecting use of a pet health device by an animal by detecting the presence of the animal over an initial threshold time period.Claim 16. The method of Claim 15, wherein the one or more sensing devices detect the presence of the animal greater for a duration longer than an initial threshold time; and wherein the one or more processors determine that the animal is using the pet health device as intended for use based on the duration being longer than the initial threshold time.Claim 17. The method of Claim 16, wherein the initial threshold time is about 3 seconds or greater to about 30 seconds or less.Claim 18. The method of Claim 17, wherein the initial threshold time is about 5 seconds or greater to about 15 seconds or less.Claim 19. The method of Claim 16, wherein the intended use refers to eliminating waste at a litter device, eating food from a feeder, drinking water from a water dispenser, resting at a resting device, or a combination thereof.Claim 20. The method of Claim 1. wherein the recording of the weight includes the recorded weight being stored in one or more non-transitory storage mediums; and wherein the one or more non-transitory storage mediums are part of the pet health device, remote from the pet health device, or both.Claim 21. The method of Claim 20, wherein the recorded weight is stored in one or more animal weight databases stored in the one or more non-transitory storage mediums.Claim 22. The method of Claim 20, wherein the recorded weight is a single weight related to a use instance of the animal at the pet health device.Claim 23. The method of Claim 20, wherein the recorded weight is a detected weight and / or a derived weight.Claim 24. The method of Claim 23, wherein the recorded weight is a maximum weight value, a minimum weight value, a central tendency value, or a combination thereof associated with a single use instance of the animal at the pet health device.Claim 25. The method of Claim 24, wherein the recorded weight is the maximum weight value associated with the single use instance of the animal at the pet health device.Claim 26. The method of Claim 24, wherein the recorded weight is determined after an initial threshold time period to ascertain the presence of the animal at the pet health device.Claim 27. The method of Claim 1, wherein the departure of the animal is detected by the one or more mass sensors.Claim 28. The method of Claim 27, wherein the departure is determined by the detected weight dropping below a hysteresis threshold which indicates the animal is no longer present at the pet health device.Claim 29. The method of Claim 1, wherein the recorded weight is automatically associated with an activity of the animal by the one or more processors based on the pet health device in which the animal was detected.Claim 30. The method of Claim 29, wherein the activity of the animal includes eliminating waste, eating, drinking, resting, or a combination thereof.Claim 31. The method of Claim 30, wherein the recorded weight is associated with the activity within one or more databases.Claim 32. The method of Claim 31 , wherein the recorded weight is associated with the activity in one or more animal weight databases.Claim 33. The method of Claim 1 , wherein one or more processors may associate the recorded weight with the identity.Claim 34. The method of Claim 33, wherein the one or more processors are part of the pet health device, remote from the pet health device, or both.Claim 35. The method of Claim 33, wherein the recorded weight is compared to one or more threshold weights associated with one or more animal profiles.Claim 36. The method of Claim 35, wherein the recorded weight is matched with a substantially similar threshold weight such as to determine the animal profile which corresponds thereto.Claim 37. The method of Claim 35, wherein the one or more animal profiles are stored in one or more animal profile databases.Claim 38. The method of Claim 37, wherein the automatically identifying includes first automatically filtering the one or more animal profile databases such as to share data with the pet health device from which the recorded weight originated.Claim 39. The method of Claim 38, wherein the data includes an account, owner, user, location, region, or a combination thereof.Claim 40. The method of Claim 1, wherein substantially similar means within an acceptable tolerance.Claim 41. The method of Claim 40, wherein the acceptable tolerance is about 0.1 lbs. or greater to about 1 lb. or less.Claim 42. The method of Claim 41, wherein the acceptable tolerance is about 0.1 lbs. or greater to about 0.5 lbs. or less.Claim 43. The method of Claim 1, wherein the method includes notifying one or more users of an identity, weight, and / or activity of the animal based on the automatic identification.Claim 44. The method of Claim 43, wherein the notifying is via a user interface of a computing device.Claim 45. The method of Claim 44, wherein the notifying includes automatically updating a display of the animal profile shown on a user interface of a computing device.Claim 46. The method of Claim 44, wherein the notifying includes updating the animal profile to include a most recent weight of the animal as the recorded weight, an updated central tendency value of the weight of the animal derived using the recorded weight, a timestamp associated with when the presence of the animal was detected at the pet health device, an updated history of using one or more pet health devices based on the presence being detected and the weight being recorded, or a combination thereof.Claim 47. The method of Claim 1, wherein the method includes automatically updating one or more trends associated with the animal.Claim 48. The method of Claim 47, wherein the one or more trends include one or more trends associated with the weight of the animal, use of the one or more pet health devices by the animal, or both.Claim 49. The method of Claim 48, wherein the one or more trends include one or more trends relative to a weight of the animal, waste elimination by the animal, eating by the animal, drinking by the animal, resting by the animal, or a combination thereof.Claim 50. The method of Claim 47, wherein the method includes automatically displaying the one or more trends via a user interface of a computing device.Claim 51. The method of Claim 50, wherein the one or more trends are shown as one or more numerical values and / or charts.Claim 52. The method of Claim 1, wherein the substantially similar weight is a threshold weight.Claim 53. The method of Claim 52, wherein the method includes automatically updating one or more threshold weights of one or more animals.Claim 54. The method of Claim 53, wherein the updating occurs after one or more recorded weights are obtained.Claim 55. The method of Claim 54, wherein the updating is executed on a recurring frequency.Claim 56. The method of Claim 55, wherein the recurring frequency is about every single day to about every seven days.Claim 57. The method of Claim 54, wherein one or more updating algorithms are executed to update the one or more threshold weights.Claim 58. The method of Claim 57, wherein the updating algorithm is a machine learning algorithm.Claim 59. The method of Claim 58, wherein the updating algorithm is a clustering algorithm.Claim 60. The method of Claim 59. wherein the clustering algorithm is a centroid-based clustering algorithm.Claim 61. The method of Claim 1, wherein the method includes onboarding of one or more animal profiles.Claim 62. The method of Claim 61, wherein the onboarding includes creating and / or editing the one or more animal profiles.Claim 63. The method of Claim 62, wherein the onboarding includes associating one or more initial weights with the one or more animal profiles.Claim 64. The method of Claim 63, wherein inputting of the initial weight is manual, partially automated, or automated.Claim 65. A method for identifying an animal using one or more pet health devices comprising: a) monitoring for a presence of the animal at the one or more pet health devices by one or more mass sensors; b) detecting the presence of the animal at the one or more pet health devices by the one or more mass sensors when the one or more mass sensors detect a weight over a detection threshold and the weight is detected over an initial threshold time period; c) recording a weight of the animal as detected by the one or more mass sensors, wherein the weight once recorded is a recorded weight, and wherein the recorded weight is a peak detected weight; d) detecting a departure of the animal from the one or more pet health devices by the one or more mass sensors when the one or more mass sensors detect the weight below at or below a hysteresis threshold; e) automatically identifying the animal by automatically associating the recorded weight with an identity of the animal by matching the recorded weight with a substantially similar weight associated with an animal profile.Claim 66. A system for execution the method of Claim 1, the system comprising: a) the one or more pet health devices comprising the one or more sensing devices; b) one or more processors part of and / or separate from the pet health devices and configured to execute the method; c) one or more non-transitory storage mediums including the method stored therein and accessible by the one or more processors.Claim 67. A method for identifying an animal using one or more pet health devices comprising: a) monitoring for a presence of the animal at the one or more pet health devices by one or more sensing devices; b) detecting the presence of the animal at the one or more pet health devices by the one or more sensing devices; c) recording a weight of the animal as detected by the one or more sensing devices, wherein the one or more sensing devices include one or more mass sensors, and the weight once recorded is a recorded weight; d) detecting a departure of the animal from the one or more pet health devices by the one or more sensing devices; e) automatically identifying the animal by automatically associating the recorded weight with an identity of the animal by matching the recorded weight with a substantially similar weight associated with an animal profile.Claim 68. The method of Claim 67, wherein the one or more sensing devices include one or more emitting sensors.Claim 69. The method of Claim 68. wherein both the one or more emitting sensors and the one or more mass sensors monitor for and detect the presence of the animal at the one or more pet health devices.Claim 70. The method of Claim 67. wherein the one or more mass sensors monitor for tire presence and detect the presence of the animal at the one or more pet health devices.Claim 71. The method of any of the preceding claims, wherein the one or more pet health devices include one or more litter devices, feeders, water dispensers, resting devices, weight scales, the like, or a combination thereof.Claim 72. The method of any of the preceding claims, wherein the one or more pet health devices include one or more litter devices, feeders, water dispensers, resting devices, the like, or a combination thereof.Claim 73. The method of any of the preceding claims, wherein the one or more pet health devices include and / or are in communication with one or more non-transitory storage mediums which include one or more animal profile databases stored therein.Claim 74. The method of any of the preceding claims, wherein the one or more animal profile databases include one or more animal profile records; and wherein each of the animal profile records includes information related to a specific animal, including: a name, an image, an age, a gender, a weight, a species, a breed, a date of birth, health issues, medications, known eating habits, a household, a user account, an address, a language preference for understanding verbal commands, or a combination thereof.Claim 75. The method of Claim 74, wherein the each of the animal profile records includes the image, the name, the species, the breed, the age and / or the date of birth, the gender and the weight of the specific animal.Claim 76. The method of any of the preceding claims, wherein the one or more pet health devices include and / or are in communication with one or more non-transitory storage mediums which include one or more animal weight databases stored therein.Claim 77. The method of any of the preceding claims, wherein one or more animal weight databases store a history of weight records for recorded weights of one or more animals.Claim 78. The method of Claim 77 or 78, wherein the one or more animal weight databases include one or more weight records; and wherein each of the weight records includes a recorded weight, a timestamp from when the recorded weight was detected, and a pet health device where the recorded weight was detected.Claim 79. The method of any of the preceding claims, wherein the detecting the presence of the animal is also determined by one or more controllers in conjunction with the one or more sensing devices.Claim 80. The method of any of the preceding claims, wherein the one or more mass sensors detect the weight of the animal which is greater than a detection threshold; and wherein the one or more processors determine that the animal is present based on the weight being greater than the detection threshold.Claim 81. The method of any of tire preceding claims, wherein the method includes detecting use of a pet health device by an animal by detecting the presence of the animal over an initial threshold time period.Claim 82. The method of Claim 81, wherein the one or more sensing devices detect the presence of the animal greater for a duration longer than an initial threshold time; and wherein the one or more processors determine that the animal is using the pet health device as intended for use based on the duration being longer than the initial threshold time.Claim 83. The method of Claim 82, wherein the initial threshold time is about 3 seconds or greater to about 30 seconds or less.Claim 84. The method of Claim 83, wherein the initial threshold time is about 5 seconds or greater to about 15 seconds or less.Claim 85. The method of any of claims 82 to 84, wherein the intended use refers to eliminating waste at a litter device, eating food from a feeder, drinking water from a water dispenser, resting at a resting device, or a combination thereof.Claim 86. The method of any of the preceding claims, wherein the recording of the weight includes the recorded weight being stored in one or more non-transitory storage mediums; and wherein the one or more non-transitory storage mediums are part of the pet health device, remote from the pet health device, or both.Claim 87. The method of any of the preceding claims, wherein the recorded weight is stored in one or more animal weight databases stored in the one or more non-transitory storage mediums.Claim 88. The method of any of the preceding claims, wherein the recorded weight is a single weight related to a use instance of the animal at the pet health device.Claim 89. The method of any of the preceding claims, wherein the recorded weight is a detected weight and / or a derived weight.Claim 90. The method of any of the preceding claims, wherein the recorded weight is a maximum weight value, a minimum weight value, a central tendency value, or a combination thereof associated with a single use instance of the animal at the pet health device.Claim 91. The method of Claim 90, wherein the recorded weight is the maxim um weight value associated with the single use instance of the animal at the pet health device.Claim 92. The method of Claim 90 or 91, wherein the recorded weight is determined after an initial threshold time period to ascertain the presence of the animal at the pet health device.Claim 93. The method of any of the preceding claims, wherein the departure of the animal is detected by the one or more mass sensors, emitting sensors, or both.Claim 94. The method of any of the preceding claims, wherein the departure is determined by one or more mass sensors and determined by the detected weight dropping below a hysteresis threshold which indicates the animal is no longer present at the pet health device.Claim 95. The method of any of the preceding claims, wherein the recorded weight is automatically associated with an activity of the animal by the one or more processors based on the pet health device in which the animal was detected.Claim 96. The method of Claim 95, wherein the activity of the animal includes eliminating waste, eating, drinking, resting, or a combination thereof.Claim 97. The method of any of the preceding claims, wherein the recorded weight is associated with the activity within one or more databases.Claim 98. The method of Claim 97, wherein the recorded weight is associated with the activity in one or more animal weight databases.Claim 99. The method of any of the preceding claims, wherein one or more processors may associate the recorded weight with the identity.Claim 100. The method of any of the preceding claims, wherein the one or more processors are part of the pet health device, remote from the pet health device, or both.Claim 101. The method of any of the preceding claims, wherein the recorded weight is compared to one or more threshold weights associated with one or more animal profdes.Claim 102. The method of any of the preceding claims, wherein the recorded weight is matched with a substantially similar threshold weight such as to determine the animal profile which corresponds thereto.Claim 103. The method of any of the preceding claims, wherein the one or more animal profiles are stored in one or more animal profile databases.Claim 104. The method of any of the preceding claims, wherein the automatically identifying includes first automatically filtering the one or more animal profile databases such as to share data with the pet health device from which the recorded weight originated.Claim 105. The method of Claim 104, wherein the data includes an account, owner, user, location, region, or a combination thereof.Claim 106. The method of any of the preceding claims, wherein substantially similar means within an acceptable tolerance.Claim 107. The method of Claim 106, wherein the acceptable tolerance is about 0.1 lbs. or greater to about 1 lb. or less.Claim 108. The method of Claim 107, wherein the acceptable tolerance is about 0.1 lbs. or greater to about 0.5 lbs. or less.Claim 109. The method of any of the preceding claims, wherein the method includes notifying one or more users of an identity, weight, and / or activity of the animal based on the automatic identification.Claim 110. The method of Claim 109, wherein the notify ing is via a user interface of a computing device.Claim 111. The method of Claim 109 or 110, wherein the notifying includes automatically updating a display of the animal profile shown on a user interface of a computing device.Claim 112. The method of any of Claims 109 to 111, wherein the notifying includes updating the animal profile to include a most recent weight of the animal as the recorded weight, an updated central tendency value of the weight of the animal derived using the recorded weight, a timestamp associated with when the presence of the animal was detected at the pet health device, an updated history of using one or more pet health devices based on the presence being detected and the weight being recorded, or a combination thereof.Claim 113. The method of any of the preceding claims, wherein the method includes automatically updating one or more trends associated with the animal.Claim 114. The method of Claim 113, wherein the one or more trends include one or more trends associated with the weight of the animal, use of the one or more pet health devices by the animal, or both.Claim 115. The method of Claim 113 or 114, wherein the one or more trends include one or more trends relative to a weight of the animal, waste elimination by the animal, eating by the animal, drinking by the animal, resting by the animal, or a combination thereof.Claim 116. The method of any of the preceding claims, wherein the method includes automatically displaying the one or more trends via a user interface of a computing device.Claim 117. The method of Claim 116. wherein the one or more trends are shown as one or more numerical values and / or charts.Claim 118. The method of any of the preceding claims, wherein the substantially similar weight is a threshold weight.Claim 119. The method of any of the preceding claims wherein the method includes automatically updating one or more threshold weights of one or more animals.Claim 120. The method of Claim 119. wherein the updating occurs after one or more recorded weights are obtained.Claim 121. The method of Claim 119 or 120, wherein the updating is executed on a recurring frequency.Claim 122. The method of Claim 121, wherein the recurring frequency is about every single day to about every seven days.Claim 123. The method of Claim 120 to 122. wherein one or more updating algorithms are executed to update the one or more threshold weights.Claim 124. The method of Claim 123, wherein the updating algorithm is a machine learning algorithm.Claim 125. The method of Claim 123 or 124, wherein the updating algorithm is a clustering algorithm.Claim 126. The method of Claim 125, wherein the clustering algorithm is a centroid-based clustering algorithm.Claim 127. The method of any of the preceding claims, wherein the method includes onboarding of one or more animal profiles.Claim 128. The method of Claim 127, wherein the onboarding includes creating and / or editing the one or more animal profiles.Claim 129. The method of Claim 127 or 128, wherein the onboarding includes associating one or more initial weights with the one or more animal profiles.Claim 130. The method of Claim 129. wherein inputting of the initial weight is manual, partially automated, or automated.Claim 131. A method for identifying an animal using one or more pet health devices comprising: a) monitoring for a presence of the animal at the one or more pet health devices by one or more mass sensors; b) detecting the presence of the animal at the one or more pet health devices by the one or more mass sensors when the one or more mass sensors detect a weight over a detection threshold and the weight is detected over an initial threshold time period; c) recording a weight of the animal as detected by the one or more mass sensors, wherein the weight once recorded is a recorded weight, and wherein the recorded weight is a peak detected weight; d) detecting a departure of the animal from the one or more pet health devices by the one or more mass sensors when the one or more mass sensors detect the weight below at or below a hysteresis threshold;e) automatically identifying the animal by automatically associating the recorded weight with an identity of the animal by matching the recorded weight with a substantially similar weight associated with an animal profile.Claim 132. A method for identifying an animal using one or more pet health devices comprising: a) onboarding one or more animal profiles; b) monitoring for a presence of the animal at the one or more pet health devices by one or more sensing devices; c) detecting the presence of the animal at the one or more pet health devices by the one or more sensing devices; d) detecting use of a pet health device by an animal, such as by detecting the presence of an animal over an initial threshold time period; e) recording a weight of the animal as detected by the one or more sensing devices, wherein the one or more sensing devices include one or more mass sensors, and the weight once recorded is a recorded weight; f) detecting a departure of the animal from the one or more pet health devices by the one or more sensing devices; g) automatically associating the recorded weight of the animal with an activity of the animal; h) automatically identifying the animal by automatically associating the recorded weight with an identity of the animal by matching the recorded weight with a substantially similar weight associated with an animal profile; i) notifying one or more users of an identity, weight, and / or activity of the animal; j) updating one or more trends associated with the animal; k) optionally, automatically inquiring as to a new animal if a new weight is detected which goes unmatched with an existing animal profile; l) optionally, automatically disabling the association of weights with specific animals and animal identification based on weight if there are animal weights in too close proximity to one another or if there is an unsuitable condition detected in the pet health device and / or one or more mass sensors; and m) updating one or more threshold weights of one or more animals.Claim 133. A method for identifying an animal based on weight comprising: a) executing an onboarding algorithm by one or more processors such as to associate an initial threshold weight with an animal profile; b) executing a monitoring algorithm by one or more processors part of a pet health device to monitor for the presence of the animal at the pet health device; c) detecting the presence of an animal at a pet health device by one or more sensing devices (e.g., mass sensors and / or emitting sensors); d) detecting use of a pet health device by the animal during execution of a use algorithm by one or more processors;e) weighing and recording the weight of the animal as detected by one or more mass sensors during execution of a weighing algorithm by one or more processors; f) monitoring for and detecting the departure of the animal from the one or more pet health devices during execution of a departure algorithm by one or more processors; g) associating the weight with an activity of the animal during execution of a weight storage algorithm by one or more processors; f) determining an identity of the animal based on the recorded weight during execution of a weight identification algorithm by one or more processors; h) notify ing a user, passively and / or actively7, via an application on a user interface of a personal computing device during execution of a notification algorithm; i) updating one or more trends associated with a specific animal, such as their weight and / or use of one or more pet health devices, during execution of a trend algorithm executed by one or more processors; and j) updating one or more weight threshold values associated with one or more animal profiles during execution of an updating algorithm by one or more processors; and wherein the one or more processors may be the same or different for each step of the method.Claim 134. The method of Claims 132 or 133, wherein the method includes any of the features of Claims 1 to 131 in any combination.Claim 135. A system for execution the method of any of Claims 67 to 134, the system comprising; a) the one or more pet health devices comprising the one or more sensing devices; b) one or more processors part of and / or separate from the pet health devices and configured to execute the method; and c) one or more non-transitory storage mediums including the method stored therein and accessible by the one or more processors.Claim 136. One or more non-transitory' computer readable mediums storing therein all or part of a computer program for executing the method according to any of the previous claims.Claim 137. A method, pet health device(s), system, and / or non-transitory computer readable medium according to any of the teachings herein, comprising any of the teachings the present disclosure in any combination.

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