Method and system for determining animal behavior and health

Abstract

A method for monitoring behavior and health of an animal, including: a) receiving one or more initial data from a start time related to the animal and / or one or more pet health devices; b) receiving one or more later data from an end time related to the animal and / or one or more pet health devices; c) automatically determining one or more trend values associated with the one or more initial data and the one or more later data; d) automatically comparing the one or more trend values to one or more threshold values and determining if the one or more trend values is below, meets, or exceeds the one or more threshold values; and d) based on the comparison of the one or more trend values to the one or more threshold values, one or more processors automatically executing one or more actions.

Description

METHOD AND SYSTEM FOR DETERMINING ANIMAL BEHAVIOR AND HEALTHCROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims priority from U.S. Provisional Application No. 63 / 491,751. filed on March 23, 2023, and which is incorporated herein by reference in their entirety for all purposes.FIELD

[0002] The disclosure relates to a method and system for determining trends related to animal consumption and usage of different pet health devices. The disclosure may be advantageous in determining trends related to litter devices, feeders, and waterers. The disclosure may be beneficial in determining abnormal behavior based on deviation from one or more trends. The disclosure may be advantageous in determining one or more trend values associated with the one or more trends and comparing to one or more threshold values. One or more threshold values may function to identify anticipated health and / or healthy behavior and a significant difference from a threshold value may identify the potential presence of a health and / or behavior problem.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. As another example, the automated feeder disclosed in WO 2020 / 061307, incorporated herein by reference in its entirety for all purposes, makes use of a sensing tower to determine the volume of food available and one or more chute sensors to determine the level of food available for consumption. And, as a further example, a liquid dispensing device may make use of one or more sensors to determine volume of water consumed or available, such as disclosed in US Provisional Application No. 63 / 325,480, incorporated herein by reference in its entirety.

[0004] These automated pet health devices via their sensors collect a vast amount of data regarding use by an animal. It would be advantageous to determine behavior and health of an animal based on the collected data, trends from the data, and deviations from those trends. It would be advantageous to provide pet owners with potential causes of such deviations, recommend actions to pet owners (e.g., taking pet to veterinarian, adjusting food consumption), trigger updated or new automated operations of a health device (e.g., reducing / increasing food dispensed or frequency ), and / or the like.

[0005] It would be advantageous to decipher between the occasional anomaly or outlier from a trend, which may typically not be indicative of a behavior or health issue of an animal, as opposed to a trend, which may indicate the presence of a potential behavior or health issue. For example, a detected weight byone or more mass sensors of a liter device may obtain an unusually high reading, but this may be due to two cats entering into the liter device. As another example, a detected weight by one or more mass sensors of a liter device may obtain an unusually low reading, but this may be due to a cat only partially stepping onto the liter device (e.g.. onto a step) out of curiosity before walking away. As another example, a dog after going for a long run with their owner on an unusually hot day may drink a significantly higher amount of water as compared to usual and then go back to their typical drinking volume.

[0006] It would also be advantageous to compare observed trends to expected or desired trends when an animal is expected to undergo significant changes in their behavior and / or health and determine if the animal is tracking to the expected trend or may be experiencing a behavior and / or health issue. Examples include the rapid growth from birth to adulthood (e.g., kiten to adult cat), weight gain associated with pregnancy of an animal, weight loss for an overw eight animal under a controlled diet, a slow and continuous food volume reduction intentionally provided to an overweight animal, and the like. Medical professionals may know or provide safe rates of growth or loss, but it can be difficult for pet owners to collect the data (e.g., weight) and determine if their pet is gaining and / or losing weight safely.

[0007] It would also be advantageous to identify health and / or behavior issues in an animal which are slow' to present themselves. Some animals may experience slow weight loss, w eight gain, changes in eating habits, and / or changes in drinking habits which when looking at short periods of time are either not observable or do not cause alarm to their caregiver. But observing their trend over longer periods of time and / or compared to established threshold values for the longer time periods, may identify a trend which may be problematic.SUMMARY

[0008] The present disclosure relates to a method for monitoring behavior of an animal relative to one or more pet health devices, the method including: a) one or more processors automatically receiving one or more initial data from a start time related to the animal and / or the one or more pet health devices, wherein the one or more initial data are related to a measured trait and / or a sensed condition of the animal and / or the one or more pet health devices; b) the one or more processors automatically receiving one or more later data from an end time related to the animal and / or the one or more pet health devices, wherein the one or more later data are related to the measured trait and / or the sensed condition of the animal and / or the one or more pet health devices; c) the one or more processors automatically determining one or more trend values associated w ith the one or more initial data and the one or more later data; d) the one or more processors automatically comparing the one or more trend values to one or more threshold values and determining if the one or more trend values is below, meets, or exceeds the one or more threshold values; e) based on the comparison of the one or more trend values to the one or more threshold values, the one or more processors automatically: i) adjusting one or more operations of the one or more pet health devices; ii) notifying a user via a user interface on a computing device of one or more results from the comparing the one or more trend values to the one or more threshold values; iii) notifying the user via the user interface of the computing device of one or more potential health conditions of the animal; iv) notifying the user via the user interfaceof the computing device of one or more recommended lifestyle changes for the animal; v) the like; or vi) any combination thereof.

[0009] The present disclosure relates to a method for monitoring behavior of an animal relative to one or more pet health devices, the method including: a) receiving a plurality of initial data signals over a first time period related to the animal and / or the one or more pet health devices; b) receiving one or more later data signals from a later time or a later time period related to the animal and / or the one or more pet health devices, c) determining one or more trends associated with the initial data entries, the further data, the one or more later data entries, the additional data and related to the animal and / or the one or more pet health devices; d) comparing the one or more later data signals and / or the additional data to the one or more trends and determining if the one or more later data signals are within the trend or deviate from the trend and / or comparing a trend inclusive of the one or more later data signals and / or the additional data to a threshold trend and determining if the trend is below, meets, or exceeds the threshold trend.

[0010] The present disclosure relates to a method for monitoring behavior of an animal relative to one or more pet health devices, the method including: a) receiving a plurality of initial data signals over a first time period related to the animal and / or the one or more pet health devices; b) receiving one or more later data signals from a later time or a later time period related to the animal and / or the one or more pet health devices, c) determining one or more trends associated with the initial data entries, the further data, the one or more later data entries, the additional data and related to the animal and / or the one or more pet health devices; d) comparing the one or more later data signals and / or the additional data to the one or more trends and determining if the one or more later data signals are within the trend or deviate from the trend and / or comparing a trend inclusive of the one or more later data signals and / or the additional data to a threshold trend and determining if the trend is below, meets, or exceeds the threshold trend; and e) based on the comparison, one or more of: i) adjusting one or more operations of the one or more pet health devices based on the trend, the deviation from the trend, and / or trend comparison to the threshold trend; ii) notifying a user via a user interface on a computing device of the trend, and / or trend comparison to threshold trend ; iii) notifying the user via the user interface of the computing device of one or more potential health conditions of the animal; iv) notifying the user via the user interface of the computing device of one or more recommended lifestyle changes for the animal (e.g.. diet, activity, environment); v) the like; or vi) any combination thereof.

[0011] The present teachings may provide for one or more methods which determine one or more trends associated with measured traits and / or sensed conditions of an animal and / or pet health device. The one or more trends may be one or more trendlines, central tendency values, or both. One or more methods may provide for one or more trendlines which smooth out the data such as to reduce sensitivity to data associated with one or more anomalies or outliers. One or more methods may provide for one or more trendlines which may be sufficiently sensitive to detect long term trends which may typically be slow to present themselves. The present teachings may provide for determining one or more regression lines as the one or more trendlines associated with the measured traits and / or sensed conditions.

[0012] The presenting teachings provide for a beneficial regression line which may be a least squares regression line. A least squares regression line may be determined using a linear least squares regression method. The linear least squares regression method may be useful in avoiding the use of mean, median, and mode values while still determining one or more trends of the data. The linear least squares regression line may provide for adjusted starting and ending points of a trend line which intermediate data points into consideration as opposed to a simple trendline from a starting point to an ending point based on observed values. The regression line may provide for one or more trend values useful for comparing to one or more threshold values. The one or more trend values may include a slope value, a percentage difference value, an adjusted starting point, an adjusted ending point, the like, or a combination thereof. One or more trend values being less than, equal to, or greater than one or more trend values may signify the presence of a potential animal behavior and / or health problem.BRIEF DESCRIPTION OF DRAWINGS

[0013] FIG. 1 illustrates a system.

[0014] FIG. 2 illustrates a system.

[0015] FIG. 3 illustrates an application and various displays for a user interface.

[0016] FIG. 4 illustrates an application displayed on a user interface.

[0017] FIG. 5 illustrates an application displayed on a user interface.

[0018] FIG. 6 illustrates a plot chart with differing trend lines and regression lines.

[0019] FIG. 7 illustrates collected data and analysis for a plot chart and trend / regression lines.

[0020] FIG. 8 illustrates calculated data for differing trend and regression lines.

[0021] FIG. 9 illustrates notifications delivered from an application.

[0022] FIG. 10 is a perspective view of a litter device.

[0023] FIG. 11 is a cross-section view of a litter device.

[0024] FIG. 12 is a perspective view of a water dispenser.

[0025] FIG. 13 is a perspective view of a water dispenser.

[0026] FIG. 14 is a cross-section view of a water dispenser.

[0027] FIG. 15 is a perspective view of a feeder.

[0028] FIG. 16 is a perspective view of a feeder.

[0029] FIG. 17 is a perspective view of a feeder.

[0030] FIG. 18 is a cross-section view of a feeder.

[0031] FIG. 19 is a perspective view of a feeder.DETAILED DESCRIPTION

[0032] 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 the present teachings as set forth are not intended as being exhaustive or limiting of the present teachings. The scope of the present teachings should be determined 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. Othercombinations are also possible as will be gleaned from the following claims, which are also hereby incorporated by reference into this written description.

[0001] Pet Health Devices and System

[0002] 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, movement, vital sign(s) monitoring, 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. crat). wearables, embedded trackers, vital sign and / or biomarker detection devices, 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.

[0003] 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.

[0004] 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.

[0005] 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 and disposal 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 anddisposal 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 capability7, 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 entirety7for all purposes.

[0006] 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 ty pe 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.

[0007] 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 a bottom to a top of the hopper. One or more sensing devices may 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 an automated 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 theautomated food dispenser such as disclosed in US Patent No. 9,161,514. which is incorporated herein by reference in its entirety for all purposes.

[0008] 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 is pushed 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 PatentApplication 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.

[0009] 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 units, the like, or any combination thereof.

[0010] 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 fdters, 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.

[0011] 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 one or 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, tire like, or any combination thereof.

[0012] 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 transmitter, an IEEE 802.15.4 compliant transmitter, cellular radio signal transmitter, Narrowband-Internet of Things (NB-IoT) transmitter, the like, or any combination thereof. A Wi-Fitransmitter may be any transmitter 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 transmitter 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.

[0013] 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 which 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; visual traits of an animal; mass of an animal; touch, vibrations, capacitance, resistance, or the like related to physical contact by or proximity with an animal; identification of an animal (specifically or more generically); presence of an animal; biomarker(s) of an animal; vital sign(s) of an animal; the like; or any combination thereof.

[0014] The one or more sensing devices may include one or more cameras. The one or more cameras may be suitable for capturing one or more videos, images, frames, the like, or any combination thereof. The one or more cameras may be positioned within a setting to have a line of sight on one or more pet health devices, animals, or both. Line of sight may mean the camera is in view of at least part of or all of a front of a pet health device, a bowl (e.g., feeding dish, serving bowl) of a pet health device, through an entry opening, into the interior chamber of a pet health device, into a hopper or other storage area of a pet health device (e.g., line of sight onto transparent surface of hopper), an animal when using a pet health device, or any combination thereof. Line of sight may mean having an animal’s body, side profile, front profile, rear profde, head, legs, eyes, nose, mouth, ears, tail or tail area, one or more bodily orifices, any combination thereof in view of the camera. The one or more cameras may have a line of sight (e.g., have in view) of a single pet health device, a portion of a device, or a plurality of pet health devices.

[0015] The one or more cameras may be suitable for capturing one or more key features of an animal for animal detection, identification, behavior, or any combination thereof. Key features are discussed hereinafter.

[0016] The one or more cameras may be suitable for capturing one or more features of one or more pet health devices for identifying the pet health device(s) in view. The one or more cameras may be suitable for capturing one or more features of a pet health device for detection, identification, condition and / or operation detection, or combination thereof. Identification may include identifying a specific t pe of pet health device (e.g.. litter device, feeder, water dispenser, etc.), an exact pet health device (e.g.. serial number), a location of a specific health device relative to another, an environment (e.g., setting) a pet health device is located in (e.g.. bedroom, bathroom, laundry room), and / or the like. The one or more cameras may be suitable for capturing one or more conditions of a pet health device. One or more conditions may include cleanliness, litter level inside a chamber, position of a chamber, progress or status of a cleaning cycle, cleanliness in proximity7to a pet health device (e.g., litter, waste, food, water on the floor), water level in a serving bowl, water level in a fresh tank, water level in a used tank, cleanliness of a serving bowl of a water dispenser and / or water in a serving bowl, level of food in a feeding dish, level of food in a hopper of a feeder, level of food in a container on display, number of containers in a container storage subassembly, cleanliness of a serving bowl and / or feeding area of a feeder and / or food in a serving bowl, the presence of pests, the presence of waste, the like, or any combination thereof. The camera may even capture an animal bringing an object to a pet health device which may then be recognized. Exemplar}7objects may include toys, other animals (e.g., mice, bird, rabbit), household goods, human wearables (e.g., socks, jewelry), and the like.

[0017] A camera may continuously, intermittently, or both capture incoming images (e.g., video stream, image stream). The camera may be continuously operational and capturing incoming images. The camera may be triggered to initiate and / or stop capturing incoming images via one or more other sensing devices. One or more sensing devices may sense a change in one or more conditions of one or more pet health devices, the presence and / or absence of an animal, the arrival of an animal, the departure of an animal, use of a pet health device by an animal, and / or the like. For example, an identification sensor may detect an identifier of an animal within a sensing range, transmit a status signal as a detection signal and / or identification signal to a controller, and the controller may then initiate the camera to begin capturing a video stream. As another example, one or more mass sensors may detect an animal incoming into a pet health device and / or approaching a pet health device, transmit the status signal as a detection signal and / or identification signal to a controller, the controller may7then initiate the camera to begin capturing a video stream. Stopping of capturing the video stream may occur in similar manner. Such as by detecting the departure of the animal by the identification sensor and / or one or more mass sensors.

[0018] The one or more cameras may include one or more lenses, image sensors, processors, storage mediums, housings, lighting elements, the like, or any combination thereof.

[0019] The one or more cameras may have a wide-angle lens (e.g., viewing angle of 150 degrees or greater). The one or more cameras may be capable of capturing static images, video recordings, or both atresolutions of about 480 pixels or greater. 640 pixels or greater, 720 pixels or greater, or even 1080 pixels or greater. The one or more cameras may be able to capture video recordings at a frame rate of about 10 frames per second. 25 frames per second or greater, about 30 frames per second or greater, about 60 frames per second or greater, or even 90 frames per second or greater.

[0020] One or more cameras may include one or more image sensors. One or more image sensors may cooperate with a lens to react with incoming light through the lens. The one or more image sensors may convert the captured analog signals to digital signals. The one or more image sensors may then transmit the digital signals to one or more processors and / or storage mediums of the camera and / or pet health device.

[0021] The one or more cameras may be suitable for capturing images under one or more lighting conditions. Lighting conditions may include natural light, supplemental illumination, or both. Illumination may be visible, infrared, or both. Illumination may be provided by a lighting element. The lighting element may be part of the camera, part of the pet health device, or both. The lighting element may include one or more light emitting diodes (LEDs). For example, the lighting element may be positioned adjacent and / or near proximity to the lens of the camera. The lighting element may be above, below, and / or beside the lens.

[0022] The one or more cameras may cooperate with one or more other sensing devices, cameras, or both to determine distance, create 3D interpretations, or both. One or more cameras cooperating with other camera(s) or sensing device(s) may be able to determine a distance to an animal, a pet health device, components within a pet health device (e.g., litter, food, water), and / or the like. One or more cameras cooperating with other camera(s) or sensing device(s) may be able to collect data to generate substantially accurate three-dimensional interpretations of an animal, a pet health device, components of a pet health device, an environment, other items within the surrounding environment, the like, or a combination thereof. Cameras may cooperate together for object detection, similarity matching, and / or depth estimation such as described in “Multi-Camera 3D Mapping with Object Detection, Similarity Matching and Depth Estimation” (2021) by Emilio Montoya. David Ramirez, and Dr. Andreas Spanias, incorporated herein by reference in its entirety.

[0023] One suitable camera for use may include the SainSmart IMX219 Camera Module with an 8MP sensor and 160-degree field of vision, the camera module and its specifications incorporated herein by reference in its entirety for all purposes.

[0024] The one or more cameras may include a camera as disclosed in US Provisional Application No. 63 / 490,910, incorporated herein by reference in its entirety.

[0025] 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, or any combination thereof. A mass sensor may continuously, intermittently, 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 device, 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. 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; and US Provisional Patent Application No. 63 / 325,480, all of which are incorporated herein by reference in their entirety. 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. 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 bottom 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, betw een 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 bowd, the like, or any combination thereof. Exemplary integration w ith 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. Exemplar}' integration with a resting device ma 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, 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. 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 may be referred to as a mass signal. The mass signal may be included as a status signal.

[0026] The one or more sensing devices may include one or more temperature sensors. The one or more temperature sensors may function to monitor a temperature of a device, monitor a temperature of an animal, identify a presence of an animal within or near a device, identify abnormal temperature of an animal or ambient environment, or any combination thereof. A temperature sensor may continuously, intermittently, or both monitor for temperature and / or changes thereof. The temperature sensor may be located at any location in or near a pet health device so that any change in temperature of the device or ambient environment, presence of an animal within or near the device, temperature of the animal, or any combination thereof may be detected. The temperature sensor may be touchless such as to detect temperature from a distance without requiring direct contact. One or more temperature sensors may include one or more infrared thermometers, thermistors (e.g., digital thermometer), the like, or any combination thereof. The one or more temperature sensors may be located anywhere within, on, and / or near a pet health device suitable for detecting temperature of an animal, the device or portions thereof, an ambientenvironment, or any combination thereof. The one or more temperature sensors may be located within an interior or exterior of one or more pet health devices. Exemplary integration into a litter device may include affixed to a bezel, within a chamber, affixed to a boimet, the like, or any combination thereof. Exemplary integration to a feeder or liquid dispenser may include at or near a feeding area (e.g.. serving bowl), a front face of the device, or both. The one or more temperature sensors may be in communication with one or more controllers, computing devices, processors, communication modules, or any combination thereof. The one or more temperature 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 temperature sensors may relay one or more signals related to a monitored temperature to one or more controllers, computing devices, processors, communication modules, or any combination thereof. The one or more temperature sensors may relay a presence of temperature above a predetermined temperature, a real-time temperature, a change in temperature, or a combination thereof to one or more controllers, computing devices, processors, communication modules, or any combination thereof. A signal from one or more temperature sensors relayed to one or more controllers, computing devices, processors, communication modules, or any combination thereof related to the detected temperature may be referred to as a temperature signal. The temperature signal may be included as a status signal.

[0027] The one or more sensing devices may include one or more laser sensors. The one or more laser 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 food in a pet health device; the like; or any combination thereof. The one or more laser sensors may be located anywhere on, within, or near a pet health device. One or more laser sensors may include one or more time- of-flight sensors, infrared sensors, ultrasonic sensors, membrane sensors, radio frequency (RF) admittance sensors, optical interface sensors, microwave sensors, the like, or combination thereof. The one or more laser 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 laser 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 a feeder 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 laser sensors may be in communication with one or more controllers, computing devices, processors, communication modules, or any combination thereof. The one or more laser 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 laser 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 laser 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 laser sensors maycooperate together to determine and / or track one or more positions or physical behaviors of an animal. Suitable exemplary 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. A signal from one or more laser 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 a laser signal. The laser signal may be included as a status signal.

[0028] The laser sensor(s) may collect sufficient data to create three-dimensional representations of an animal, identifying characteristics of an animal, or both. One or more processors may generate the three- dimensional representations based on the data received from the laser sensor(s). The three-dimensional representations may be used to determine behaviors of an animal, such as the acts of sleeping, sitting, squatting, defecating, urinating, self-grooming, the like, or any combination thereof. A signal from one or more laser sensors relayed to one or more controllers, computing devices, processors, communication modules, or any combination thereof related to the detected presence may be referred to as a presence signal.

[0029] The one or more sensing devices may include one or more identification sensors (“ID sensor”). One or more ID sensors may function to identify an animal by its identity via one or more identifiers on an animal. An identification sensor may be one or more readers configured to communicate with one or more identifiers. An identification sensor may include a radio frequency identification (RFID) reader, Bluetooth reader, a Near Field Communication (NFC) reader, the like, or any combination thereof. The one or more identification sensors may receive identification of an animal by collecting identifying data directly from the identifier, from receiving a signal related to identification data in an identification database, or both. The one or more identification sensors may be located anywhere within, on, and / or near a pet health device suitable for communicating with the identifier when an animal is near, at, or in the pet health device. The one or more identification sensors may be located within an interior or exterior of one or more pet health devices. Exemplary integration into a litter device may include affixed to a bezel, within a chamber, affixed to a bonnet, the like, or any combination thereof. Exemplary integration to a feeder or liquid dispenser may include at or near a serving dish, a front face of the device, or both. The one or more identification sensors may be in communication with one or more controllers, computing devices, processors, communication modules, or any combination thereof. The one or more identification 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 identification sensors may relay one or more signals related an identifier to one or more controllers, computing devices, processors, communication modules, or any combination thereof. The one or more identification sensors may relay identifying data of an animal, data related to a subsequent database to retrieve identifying data of an animal, or both. A signal from one or more identification sensors relayed to one or more controllers, computing devices, processors, communication modules, or any combination thereof related to the detected identifier may be referred to as an identification signal. The identification signal may be included as a status signal.

[0030] An animal may be associated with an identifier. An identifier may function to specifically identify an animal. An identifier may be worn on a collar, embedded within the flesh (e.g., microchip), or the like. Exemplary identifiers may include radio frequency identification (RFID) tags, Bluetooth tags. Near Field Communication (NFC) tags, passive IR, the like, or any combination thereof. One or more identifiers may have identification information stored therein, link to one or more databases which have identification information stored therein, or both. One or more identifiers may be active or passive. Passive may mean that the identifier is free of its own internal power source. Active may mean that the identifier is powered and / or broadcasts its own signal. An identifier may establish a signal with an identification sensor. This signal may be referred to as an identifier signal. An identifier signal may also be included as a status signal.

[0031] Suitable exemplary identification sensor and identifiers are disclosed in PCT Publication No. PCT / US2021 / 056490 and US Provisional Patent Application No. 63 / 625,515, which are incorporated herein by reference in their entirety for all purposes.

[0032] The one or more sensing devices may include one or more touch sensors. The one or more touch sensors may detect presence of an animal, consumption or use by an animal, or both. The one or more touch sensors may be located anywhere on, within, or near a pet health device. One or more touch sensors may include one or more tactile sensors (e.g., similar to fingertip force sensor), capacitive sensors (e.g., capacitive touch sensor), resistive sensors (e.g., resistive touch sensor), pressure sensors, vibration sensors (e.g., Piezo vibration sensor), the like, or any combination thereof. The one or more touch sensors may be located anywhere within, on, and / or near a pet health device suitable for detecting presence, absence, use, or consumption by an animal. The one or more touch sensors may be located within an interior or exterior of one or more pet health devices. Exemplary integration into a litter device may include affixed to a step, bezel, within a chamber, affixed to a support base, below a chamber, affixed to a bonnet, the like, or any combination thereof. Exemplary integration to a feeder or liquid dispenser may include at or near a serving dish, integrated into a mat below and / or in front of the feeder or liquid dispenser, or combination thereof. The one or more touch sensors may be in communication with one or more controllers, computing devices, processors, communication modules, or any combination thereof. The one or more touch 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 touch sensors may relay one or more signals related to sensing the physical touch of an animal on one or more components of a pet health device to one or more controllers, computing devices, processors, communication modules, or any combination thereof. The one or more touch sensors may relay the sensed touch to one or more controllers, computing devices, processors, communication modules, or any combination thereof. A signal from one or more touch sensors relayed to one or more controllers, computing devices, processors, communication modules, or any combination thereof related to the detected presence may be referred to as a touch signal. A touch signal may also be included as a status signal.

[0033] The one or more sensing devices may include one or more animal behavior sensors. The one or more animal behavior sensors may function to collect data relative to an animal’s behavior away or at one or more pet health devices, and / or in or even away from the household. An animal behavior sensor may beable to sense motion, location, sound, vital conditions, physiological conditions, the act of eating or drinking, environmental surroundings, and / or the like. An animal behavior sensor may even aid in determining habits of an animal while inside of a household as compared to when outside the household (e.g., free-roaming cat. dog allowed outdoors in a fenced in yard. etc.). An animal behavior sensor may include one or more motion sensors, location sensors, sound sensors, vital sign sensors, physiological sign sensors, the like, or any combination thereof. One or more motion sensors may be able to measure acceleration, orientation, velocity (angular velocity), magnetic fields, the like, or any combination thereof. One or more motion sensors may include one or more accelerometers, gyroscopes, magnetometers, altimeters, inertial measurement units, the like, or any combination thereof. The one or more location sensors may be able to detect a current location of an animal, past location(s) of an animal, aid in creating mapping of an animal’s movement patterns, and / or the like. A location sensor may include one or more global positioning system (GPS) sensors, other satellite navigation sensors, inertial measuring units, ultra- wideband (UWB) sensors / transceivers the like, or any combination thereof. A sound sensing device may function to pick up sound emitted from an animal, an ambient environment, or both. A sound sensing device may include one or more microphones. A vital sign sensor may be able to detect vital signs including heart rate, blood oxygen level, body temperature, respiratory’ rate, being awake or asleep, the like, or any combination thereof. The one or more vital sign sensors may include one or more optical heart rate sensors, pulse oximeters, blood oxygen (SpO2) sensors, bioimpedance sensors, electrocardiogram (ECG) sensors, skin temperature sensors, piezoelectric sensor (i.e., for sensing heart rate), the like, or any combination thereof. The one or more animal behavior sensors may be worn by the animal, embedded into the animal under the skin (e.g., similar to a microchip), part of a mat or other surface in proximity to an animal, into a pet health device, or any combination thereof. The one or more animal behavior sensors may be integrated into a collar, or other animal wearable. The one or more animal behavior sensors may be used for determining the location of waste expelled from an animal (e.g., finding fecal matter in a yard for subsequent removal). The one or more animal behavior sensors may even be used to mapping property based on the motion of the animal.

[0034] The one or more sensing devices may include one or more air sensors. The one or more air sensors may function to detect if waste has been eliminated by an animal, a type of waste eliminated by an animal, or both. The one or more air sensors may sense one or more gasses or compounds emitted from animal waste. The one or more air sensors may sense one or more gasses compounds, or both associated with urine, fecal matter, or both. The one or more air sensors may be integrated into a pet health device, onto an animal wearable, or both. The one or more air sensors may include one or more volatile organic compound (VOC) sensors. Exemplary air sensors may include: Bosch Sensortec BME680 gas sensor. Figaro USA, Inc. TGS2600 air quality sensor. Winsen semiconductor combustible gas sensor MQ-4B, and Winsen Meu-H2S hydrogen sulfide gas sensor, all of which are incorporated herein by reference in their entirety for all purposes. For example, one or more air sensors may be integrated onto a bezel, a bonnet, into a chamber, or combination thereof of a litter device. For example, one or more air sensors may be located with one or more other sensors on an upper portion of a bezel.

[0033] 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 comrection and communicates with the litter device through the communication hub. An indirect comrection 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.

[0034] The one or more pet health devices may be integrated into one or more networks. 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, computing devices, 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 connected 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 netw orks (LAN), wide area networks (WAN), intranet, Internet. Internet of Things (loT). the like, or any combination thereof. The network 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-pennanently. 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 totransmit 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.

[0035] 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 netw ork 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 services. Exemplary cloud computing services may include Amazon Web Services®, 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 combination thereof. 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 coimect with a dispatch interface, interaction interface, or both via one or more protocols using the Internet. Exemplary protocols for communication from tire 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 PostscapesTM available at https: / / www.postscapes.com / intemet-of-things-protocols / , incorporated herein in its entirety for all purposes.

[0036] The 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 tire pet health devices. The system may allow for sending one or more instruction signals to a pet health device. The system may allowfor transmitting one or more signals, status signals, or both from the 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 remote from the pet health devices. 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.

[0037] 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 compute one or more algorithms, apply one or more rules, 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. A nontransient storage medium 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. One or more computing devices may use one or more processors.

[0038] 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, 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 function to process data, execute one or more algorithms to analyze data, apply one or more rules, evaluate data against one or more rules, or any combination thereof. The one or more processors may automatically process data, execute one or more algorithms, apply one or more rules, evaluate data, 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) aspart 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 or different non-transient storage 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 cloud-based processors. 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. Cloud-based 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 CloudTM (EC2TM) may be provided by Amazon Web Services®, incorporated herein by reference in its entirety for all purposes. Another suitable platform for a cloud-based processor may include LambdaTM 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 algorithms to analyze one or more data entries and / or data signals. The one or more processors may access one or more algorithms saved within one or more memory storage mediums. The one or more algorithms being accessed by one or more processors may be located in a same or different storage medium or server as the processor(s).

[0039] One or more computing devices may include one or more memory storage mediums. 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 storage mediums may include one or more cloud-based storage mediums. 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 in a non-transient storage medium located remote from the pet health devices, computing device, processor, other databases, or any combination thereof. One or more cloudbased 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 memory7storage mediums may include one or more algorithms, rules, databases, data entries, the like, or any combination therefore stored therein. The one or more memory7storage mediums may store data in the form of one or more databases.

[0040] 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 more classifications 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 a same or different hardware and / or softw are 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 a 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 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 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, one or more identifications of one or more animals, the like, or any combination thereof. One suitable database service may be Amazon DynamoDB® offered through Amazon Web Services®, incorporated herein in its entirety by reference for all purposes.

[0041] 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 both from 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 TM provided by Amazon Web Services®, 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 / orreceiving 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.

[0042] 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 the system via one or more networks. The one or more authentication controls may communicate with one or more other components of the 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, the 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 CognitoTM 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.

[0043] 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 or more notifications related to one or more animals, receive user inputs related to the pet health devices, transmit information related to the pet health devices, 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. Information may include a user name, password, one or more instruction signals, uploaded documents (e.g., veterinary documents), 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 ormore 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.

[0044] Method for Monitoring Behavior of an Animal

[0045] The present disclosure may relate to a method for monitoring behavior of an animal. The method may be useful in identifying one or more potential trends that may be problematic, signal a health concern to the owner, or both. The method may be useful in automatically adjusting one or more operations of a pet health device based on the observed trends. The method may be useful at observing trends and smoothing out data related to the animal such as avoid or reduce the impact of detected anomalies causing unnecessary concern. The method may employ one or more pet health devices, sensing devices of or separate from the pet health devices, and computing devices as described herein. 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), wearables (e.g., collar, chip), the like, or any combination thereof. Any of the steps may be conducted automatically by one or more processors. The one or more processors may be located locally on the one or more pet health devices (e g., local computing), remotely from the one or more pet health devices (e g., cloud computing), or a combination of both (e.g., edge computing).

[0046] The method for monitoring behavior of an animal relative to one or more pet health devices, the method may include: a) receiving a plurality of initial data signals over a first time period related to the animal and / or the one or more pet health devices, wherein the plurality of initial data signals are related to a measured trait and / or a sensed condition of the animal and / or the one or more pet health devices; b) optionally, converting and storing the plurality of initial data signals as one or more initial data entries in one or more storage mediums; c) optionally, calculating further data from the one or more initial data entries and storing the further data in the one or more storage mediums; d) receiving one or more later data signals from a later time or a later time period related to the animal and / or the one or more pet health devices, wherein the one or more later data signals are related to the measured trait and / or the sensed condition of the animal and / or the one or more pet health devices; e) optionally, converting and storing the one or more later data signals as one or more later data entries in the one or more storage mediums; f) optionally, calculating additional data from the one or more later data entries and storing the additional data in the one or more storage mediums; g) determining one or more trends associated with the initial data entries, the further data, the one or more later data entries, the additional data and related to the animal and / or the one or more pet health devices; h) comparing the one or more later data signals and / or the additional data to the one or more trends and determining if the one or more later data signals are within the trend or deviate from the trend and / or determining a trend inclusive of the one or more later data signals and / or the additionaldata and comparing to a threshold trend; i) based on the comparison, one or more of: i) adjusting one or more operations of the one or more pet health devices based on the trend or the deviation from the trend; ii) notifying a user via a user interface on a computing device of the trend or the deviation from the trend; iii) notifying the user via the user interface of the computing device of one or more potential health conditions of the animal; iv) notifying the user via the user interface of the computing device of one or more recommended lifestyle changes for the animal (e.g., diet, activity, environment); v) the like; or vi) any combination thereof.

[0047] The method for monitoring behavior of an animal relative to one or more pet health devices, the method may include: a) one or more processors automatically receiving one or more initial data from a start time related to the animal and / or the one or more pet health devices, wherein the one or more initial data are related to a measured trait and / or a sensed condition of the animal and / or the one or more pet health devices; b) the one or more processors automatically receiving one or more later data from an end time related to the animal and / or the one or more pet health devices, wherein the one or more later data are related to the measured trait and / or the sensed condition of the animal and / or the one or more pet health devices; c) the one or more processors automatically determining one or more trend values associated with the one or more initial data and the one or more later data; d) the one or more processors automatically comparing the one or more trend values to one or more threshold values and determining if the one or more trend values is below, meets, or exceeds the one or more threshold values; e) based on the comparison of the one or more trend values to the one or more threshold values, the one or more processors automatically: i) adjusting one or more operations of the one or more pet health devices; ii) notifying a user via a user interface on a computing device of one or more results from the comparing the one or more trend values to the one or more threshold values; iii) notifying the user via the user interface of the computing device of one or more potential health conditions of the animal; iv) notifying the user via the user interface of the computing device of one or more recommended lifestyle changes for the animal; v) the like, or vi) any combination thereof.

[0048] The method may include one or more processors automatically receiving one or more initial data from a start time, a plurality of initial data signals over a first time period, or both related to the animal and / or the one or more pet health devices. The one or more initial data, the plurality of initial data signals, or both may be related to a measured trait, a sensed condition, or both of one or more animals, one or more pet health devices, or both. The one or more initial data, the plurality of initial data signals, or both may be related to one or more status signals of one or more sensing devices. The one or more measured traits, the sensed conditions, or both may be measured, determined, and / or sensed by one or more sensing devices, controllers, or both. The one or more sensing devices may be associated with one or more pet health devices and / or standalone separate from one or more pet health devices. One or more controllers may be one or more controllers of one or more pet health devices and / or sensing devices.

[0049] The method may include one or more processors automatically receiving one or more later data from an end time, one or more later data signals from a later time or a later time period, or both related to the animal and / or the one or more pet health devices. The one or more later data, later data signals, or bothmay be related to a measured trait, a sensed condition, or both of the animal, one or more pet health devices, or both. The one or more later data, the one or more later signals, or both may be related to one or more status signals of one or more sensing devices. The one or more measured traits, the sensed conditions, or both may be measured, determined, and / or sensed by one or more sensing devices, controllers, or both. The one or more sensing devices may be associated with one or more pet health devices and / or standalone separate from one or more pet health devices. One or more controllers may be one or more controllers of one or more pet health devices and / or sensing devices.

[0050] The method may include one or more processors automatically receiving one or more intermediate data from an intermediate time and / or intermediate time period, one or more intermediate data signals from an intermediate time or an intermediate time period, or both related to the animal and / or the one or more pet health devices. The one or more intermediate data, intermediate data signals, or both may be related to a measured trait, a sensed condition, or both of the animal, one or more pet health devices, or both. The one or more intermediate data, the one or more intervening signals, or both may be related to one or more status signals of one or more sensing devices. The one or more measured traits, the sensed conditions, or both may be measured, determined, and / or sensed by one or more sensing devices, controllers, or both. The one or more sensing devices may be associated with one or more pet health devices and / or standalone separate from one or more pet health devices. One or more controllers may be one or more controllers of one or more pet health devices and / or sensing devices.

[0051] The one or more initial data, intermediate data, later data, initial data signals, intermediate data signals, later data signals may include or be automatically associated with one or more of tire following, which may be referred to as one or more sensed conditions and / or measured traits: entry of the animal into the pet health device; exit of the animal into the pet health device; detection of an object by a laser sensor; the animal within detecting proximity to the pet health device: mass of an animal; mass of an overall pet health device or a specific portion of the pet health device; mass of a pet health device prior to use by the animal; mass of a pet health device during use by the animal; mass of a pet health device after use by the animal; mass of waste disposed by the animal; mass of the pet health device at a predetermined time or time interval; mass and / or volume of food present within a pet health device; mass and / or volume of food consumed by the animal; mass and / or volume of liquid present within a pet health device; mass and / or volume of liquid consumed by the animal; body temperature of the animal; temperature of one or more components of the pet health device; temperature of an ambient environment in which the animal or the pet health device is located; one or more videos, frames, and / or images of an animal, an exterior of a health device, an interior of a health device, and / or an ambient environment: one or more videos, frames, and / or images of waste excreted into a litter device; recording of one or more sounds; electromagnetic field(s) associated with an animal (e.g., EEG, ECG): biomarkers or vitals including heart rate, blood oxygen level, body temperature, and / or respiratory rate of an animal; position and / or location of an animal: change in status of a touch sensor; acceleration and / or velocity associated with an animal; identification data from an identifier; identity of an animal associated with an identifier, identity of an animal from visual recognition.The one or more sensed conditions and / or measured traits may originate as one or more status signals from one or more sensing devices.

[0052] The method may include correlating any of the data to a specific type of animal, a specific animal and their associated pet identity, and / or to generic use of one or more pet health devices regardless of animal type or specific pet identity. If pet identity is determined, any of the measured traits and / or sensed conditions related to that animal may be correlated to that specific animal. Identification of an animal may be achieved such as disclosed in U.S. Provisional Application Nos. 63 / 490.990 and 63 / 490.910. both filed on March17, 2023, and PCT Application Nos. PCT / US2024 / 020406 and PCT / US2024 / 020390, both filed on March18, 2024, all of which are incorporated herein by reference in their entireties for all purposes.

[0053] The method may include converting and storing the one or more initial data, intermediate data, later data, initial data signals, intermediate data signals, and / or later data signals as one or more initial data entries, intermediate data entries, and / or later data entries in one or more storage mediums. The converting and storing may be automatically executed by one or more processors.

[0054] The method may include the one or more initial data, intermediate data, later data, initial data signals, intermediate data signals, later data signals, or a combination thereof being correlated with additional data. The correlation may be automatically executed by one or more processors. The correlation may occur prior to, simultaneous with, and / or after being stored in the one or more storage mediums. The additional data may include: i) an identification of a specific pet health device from which the initial data, intermediate data, later data, initial data signals, intermediate data signals, and / or later data signals originated; ii) a date and / or time stamp from when the initial data, intermediate data, later data, initial data signals, intermediate data signals, and / or later data signals were generated; iii) an identification of a specific animal associated with measured trait and / or sensed condition; and / or iv) a user account and / or household associated with the specific health device and / or the specific animal.

[0055] The method may include calculating further data from the one or more initial data, intermediate data, later data, initial data signals, intermediate data signals, later data signals, initial data entries, intermediate data entries, and / or later data entries. The calculating the further data may be automatically executed by one or more processors. The further data may be referred to as calculated data. The calculated data may include one or more of: duration of any of the initial and / or later data signals; time elapsed (e.g., time interval) between one data signal and a subsequent occurring similar data signal; duration of the animal at. in, or otherwise using the pet health device; duration of the animal in proximity to the pet health device; frequency of use of the pet health device over one or more time periods; change in mass of an animal; change in mass of the pet health device; time duration associated with an increase or decreased in monitored mass; amount of food consumed over a single visit or any other period of time (e.g., day, week); amount of food remaining in a feeder; amount of liquid consumed over a single visit or any other period time (e.g., day, week); amount of liquid remaining in a liquid dispensing device; type of waste (stool, urine) eliminated by the animal; duration of time an animal is at rest or sleeping; duration of time an animal is moving; change in temperature; time duration associated with an increase or decrease in temperature; timestamp associated with a change in status of a touch sensor; duration associated with a change in status of a touch sensor. Theduration, the frequency, the amount, or any other values of any of the calculated data may be from a single visit, a portion of a day. daily, weekly, monthly, quarterly, annually, and / or any other time period. The calculated data may be stored in one or more storage mediums. One or more processors may automatically convert and store the further data as one or more further data entries in one or more storage mediums.

[0056] The method may include automatically determining one or more trends associated with the one or more initial data, intermediate data, later data, initial data signals, intermediate data signals, later data signals, initial data entries, later data entries, and / or the further calculated data and related to the animal and / or the one or more pet health devices. The one or more trends may be automatically determined by one or more processors. The one or more trends may be automatically determined upon receipt of the later data at and / or after the end time, substantially in real time upon receipt of the later data at the end time, or both. Determining the one or more trends may be achieved via executing statistical analysis, machine learning, artificial intelligence, the like, or any combination thereof. The statistical analysis may include determining a mean, mode, median, range, maximum, minimum, standard deviation, variance, minimum variable, maximum variable, kurtosis, skewness, the like, or any combination thereof related to the initial data entries and / or further data during the first time period, data from a trailing or other time period, or all data. The machine learning may include analysis of with linear regression, logistic regression, support vector machine, hierarchal clustering, k-means clustering, self-organized mapping, the like, or a combination thereof. The determining the one or more trends may include determining one or more trendlines. One or more trendlines may include one or more regression lines. One or more trendlines may be useful for displaying on a user interface, for comparing of newly acquired data to past trends, for comparing newly acquired data or newly acquired derived data to past values or past derived values, the like, or any combination thereof. One or more trendlines may be useful for aiding in determining if there is significant deviation that may indicate an issue with an animal and / or a pet health device to a user (e.g.. pet owner, medical professional). The one or more trendlines may be linear, non-linear, or both. The one or more trendlines may include one or more linear trendlines, logarithmic trendlines, polynomial trendlines, power trendlines, exponential trendlines, and / or moving average (mean, median, mode) trendlines.

[0057] One or more linear trendlines may be utilized when data is expected to be substantially stable, change gradually, change in a substantially linear fashion, or a combination thereof (e.g.. controlled weight loss plan, pet adult stability). One or more logarithmic trendlines may be utilized when there is an expected high rate of change followed by stabilization (e.g., kitten to adult cat growth, pregnancy of an animal, intentional rapid weight loss or gain of an animal). One or more polynomial trendlines may be utilized when data is expected to fluemate (e g., intentional weight loss after weight gain of an animal).

[0058] The determining of the trendline may be free of calculating any mean, median, and / or mode values.

[0059] The method may include automatically determining one or more trend values associated with the one or more trendlines, one or more initial data, intermediate data, later data, initial data signals, intermediate data signals, later data signals, initial data entries, intermediate data entries, later data entries, or a combination thereof. One or more trend values may be one or more values and / or properties associated with the one or more trends. The one or more trend values may be advantageous in defining a trend and / ora trendline by one or more specific values. The one or more trend values may be advantageous in numerically showing stability, upward, and / or downward movement of a trend that typical central tendency values are unable to illustrate. For example, an average data point over a 7-day sequence as compared to a negative slope value or percentage change difference illustrating a downward trend in the data. The one or more trend values may be advantageous in determining a value which may be compared to one or more threshold values. The one or more trend values may include one or more percentage change values, slope values, starting point values, adjusted starting point values, ending point values, adjusted ending point values, y-intercept values, the like, or a combination thereof.

[0060] The one or more trendlines may be a simple linear trendline. The simple linear trendline may be determined over a period of time. The period of time may be a trailing time period. A trailing time period may commence at the start time. A trailing time period may end at an end time. The linear trendline may be determined using solely a first, starting point value and a second, ending data value. The linear trendline may exclude taking any intermediate values into consideration. The starting point value may be one of the initial data, initial data signals, initial data entries, and / or calculated data from the initial data at the start of the trailing time period (e.g., an observed starting point value). The ending point value may be one of the later data, later data signals, later data entries, and / or calculated data from the later data at the end of the trailing time period (e.g., an observed ending point value). A slope of the linear trendline may be automatically determined. The slope may be considered a slope value. The slope may be determined by calculating the rise over run between the starting point value and the ending point value. The percentage change value may be determined as the percentage difference between the ending point value and the starting point value. A simple linear trendline may provide a quick analysis method for determining one or more trend values. A simple linear trendline may be susceptible to being impacted by anomalies in the measured traits and / or sensed conditions by only relying on the starting point value and ending point value without taking any intermediate values into consideration.

[0061] The one or more trendlines may include a regression line. The regression line may be a curve-fit regression line. A curve-fit regression line may be determined via a linear regression, nonlinear regression, or both. The regression line may be a least squares regression line. A least squares regression line may be determined using a linear least squares regression method. A least squares regression method may allow for determining a linear equation that best fits the data over the period of time and create a trendline. The least squares regression method may be applied over a period of time (e.g.. trailing time period). The regression line may take one or more intermediate data into consideration, in addition to the initial data and later data. By taking the intermediate data into consideration, the method is able to smooth out the received data such that one or more anomalies have no or little impact in determining one or more trend values.

[0062] In applying the least squares regression method, the observed starting point value may be one of the initial data, initial data signals, initial data entries, and / or calculated data based on the initial data. In applying the least squares regression method, the observed intermediate point values may be one or more intermediate data, intermediate data signals, intermediate data entries, and / or calculated data based on theintermediate data. In applying the least squares regression method, the observed ending point value may be a later data, a later data signal, a later data entry, and / or calculated data based on the later data.

[0063] The least squares regression method may include assigning each time or instance associated with a collected data point to a sequence number. The sequence number may be the sequence number associated with the collected data point in the trailing time period. For example, the start time may be assigned to a sequence number of 1 to represent Day 1. For example, in a trailing time period of 12 days and collecting a single data point each day. the end time may be assigned to a sequence number of 12 to represent Day 12. In the least squares regression method, a square of each sequence number may be automatically calculated. This may be referred to as the squared sequence number.

[0064] In the least squares regression method, a product may be calculated. The product may be calculated for each initial data, intermediate data, and / or later data. The product may be the product of multiplying the associated sequence number with the associated initial data, intermediate data, and / or later data.

[0065] The least squares regression method may include automatically determining a linear equation which best suits the initial data, intermediate data, and / or later data. In determining the linear equation (y = mx + b), both a slope (m) and y-intercept (b) may be determined.

[0066] To determine a slope, the total of the sequence numbers in the trailing time period is calculated as a sequence aggregation value (e.g., aggregating the sequence numbers). To determine a slope, the total count of initial data, intermediate data, and later data is calculated as a count value (e.g., if there are 12 instances, the count is 12). To determine a slope, a total of the initial data, intermediate data, and later data is calculated as an aggregated data value (e.g., aggregating tire data). To determine a slope, a total of the squared sequence number is calculated as an aggregated square value (e.g., aggregating each of the squared sequence numbers in the trailing time period). To determine a slope, the total of the products is calculated as an aggregated product value (e.g., aggregating each of the products in the trailing time period).

[0067] To determine a slope, the count value may be multiplied with the aggregated product value and then subtracted therefrom is the sequence aggregation value multiplied with the aggregated data value. This visually may appear as:Count Value x Aggregated Product Value - Sequence Aggregation Value x Aggregated Data Value This calculation may be considered as determining the “rise” of the slope.

[0068] To determine a slope, the count value may be multiplied with the aggregated square value and then subtracted therefrom is the square of sequence aggregation value. This visually may appear as:Count Value x Aggregated Square Value - Sequence Aggregation ValueA2This calculation may be considered as determining the “run” of the slope.

[0069] To determine a slope, the rise may be divided by the run. This may visually appear as:Count Value x Aggregated Product Value - Sequence Aggregation Value x Aggregated Data Value Count Value x Aggregated Square Value - Sequence Aggregation ValueA2The resulting slope value may be useful in comparing to one or more threshold values, for adjusting one or more observed data into adjusted data, or both. The resulting slope value may be compared to one or more comparison slope values associated with one or more threshold values.

[0070] To determine a y-intercept, the calculated slope value may be taken into consideration. To determine the y-intercept, the aggregated data value has a product of the slope and the sequence aggregation value subtracted therefrom and is then divided by the count value. This visually may appear as:Aggregated Data Value - Slope Value x Sequence Aggregation ValueCount Value

[0071] After determining the slope and the y-intercept, the linear equation may be able to be applied to each of the sequence values, initial data, intermediate data, and later data. The initial data, intermediate data, and later data are referred to as the observed data. The linear equation is able to convert the observed data to adjusted data. The linear equation may be applied to each of the sequence numbers associated with each of the observed data to result in the adjusted data. In other words, the linear equation y = rnx + b may visually appear as:Adjusted Data = Slope Value x Sequence Number + Y-interceptUsing the linear equation, an adjusted starting point value and an adjusted ending point value over the trailing time period may be determined. An adjusted starting point value may be understood as the starting point of the regression line. An adjusted ending point value may be understood as the ending point of the regression line. The adjusted starting point value may be a result of the first sequence number at the start time of the trailing period inserted into the linear equation. The adjusted ending point value may be a result of the last sequence number at the end time of the trailing period inserted into the linear equation. The regression line may be a linear trendline over the trailing time period starting at the adjusted starting point value and ending at the adjusted ending point value. The regression line may have the slope value as calculated.

[0072] The method may include automatically determining a percentage change value between the later data and / or adjusted ending point value and the initial data and / or the adjusted starting point value. This percentage change value may be determined as the difference between the adjusted ending point value or later data and the adjusted starting point value or the initial data divided by the adjusted starting point value or the initial data and then multiplying by 100%. For the adjusted data, this visually may appear as:Adjusted Ending Point Value - Adjusted Starting Point Value x 100%Adjusted Starting Point ValueThe resulting percentage change value may be useful for comparing to one or more threshold values, such as one or more percentage change values associated with a threshold value.

[0073] The method may include automatically comparing the one or more later data signals and / or the additional data to the one or more trends and determining if the one or more later data signals are within the trend or deviate from the trend. Such a comparison may employ typical statistical analysis methods.

[0074] The method may include automatically comparing one or more trend values to one or more threshold values, comparing a trend inclusive of the one or more later data signals and / or the additional data to a threshold trend, or both. A threshold trend may be an acceptable trend for the trailing time period. One or more threshold trend values may be a threshold rate of change (e.g., a comparison slope value), a comparison percentage change value, or other value. The threshold trend and / or threshold trend value maybe specific to the duration of the trailing time period. For example, a threshold trend and / or threshold trend value for comparing to an animal’s weight or weight trend(s) may be different for a 7-day period versus a 6-month period. The threshold trend and / or threshold trend value may be specific to an animal’s age, breed, gender, health, and / or other traits.

[0075] For using a comparison percentage change value as a threshold value, a percentage change may be calculated as disclosed hereinbefore. For example, a percentage change may be calculated from starting and ending point values of a trendline, from observed starting and observed ending point values, from adjusted starting and adjusted ending point values, or any combination thereof. For example, a percentage change from an adjusted starting point value to an adjusted ending point value may be determined. Then this calculated percentage change value may be compared to a threshold trend value provided as a comparison percentage change value. If the calculated percentage change value is greater or less than the threshold percentage change, the one or more trend values may be indicative of a potential issue or an anomaly.

[0076] For using a comparison slope value as a threshold value, a slope value may be calculated as disclosed hereinbefore. For example, a slope value may be calculated using a linear regression method. The calculated slope value may be compared to a threshold trend value provided as a comparison slope value. If the calculated slope value is greater or less than the threshold comparison slope value, the one or more trend values may be indicative of a potential issue or an anomaly.

[0077] The one or more threshold trend values and / or trends may be based on a greater population database, determined by one or more medical professionals and / or animal behavior specialists, the like, or any combination thereof. A threshold trend and / or threshold trend value may be provided which takes an animal’s desired traits into account. For example, a comparison slope value and / or comparison percentage change value may be established for an animal who should maintain their weight, increase their weight (e.g., address underweight issues), or even decrease their weight (e.g.. address overweight issues). A threshold trend may even be established based on particular goals (e.g.. goal weight) over specific periods of time (e.g., goal weight by a certain date).

[0078] The method may include comparing trends and / or trend values over varying time period durations. The comparison may be to the trend values themselves over the varying time periods, threshold trend values, or both. Over the varying time period durations, the threshold trend values may be the same or different. The varying time periods may or may not be overlapping. For example, a linear regression may be determined over a 7-day period, a linear regression may be determined over a 30-day period, a linear regression may be determined over a 6-month period. Each different time period may be associated with one or more different threshold values. This may allow for understanding if any values (measured / observed data or adjusted) are anomalies or indicative of a longer-term trend that may be problematic but slow to present itself (e.g., a slow weight decline or increase). A longer-term trend that may be slow to present itself may not have a sufficient change over a short period of time, thus not exceeding the threshold trend value associated with that short period. For example, over a 7-day period, a percentage change may not exceed athreshold percentage change while over a 90-day period, the percentage change does exceed the threshold percentage change.

[0079] The method may include adjusting one or more operations of the one or more pet health devices. The adjusting may be automatically executed by one or more processors. The adjusting may be based on the comparison of the one or more trend values to threshold values, the trend, the deviation from the trend, and / or the trend comparison to a threshold trend. Adjusting of the one or more operations of tire one or more pet health devices may include: dispensing a lesser or greater amount of food; dispensing food at lesser or greater frequencies; circulating and / or refilling a liquid (e.g., water) more or less frequently; dispensing a lesser or greater amount of clean litter into a litter device; increasing or decreasing a frequency at which to alert the user for cleaning a waste receptacle of a litter device; and / or turning a light on at an expected usage time of the animal; dispensing a different food or blend of type of food; changing the accessibility to the food (e.g., opening / closing lid at a certain time based on expected arrival time of animal).

[0080] The method may include notifying a user via a user interface on a computing device. The notifying may be automatically executed by one or more processors. The notifying may be based on the comparison of one or more trend values to one or more threshold trends, trend, the deviation from the trend, and / or the trend comparison to a threshold trend. Notifying tire user may include displaying information or a notification via an application as part of the computing device; displaying information or a notification via a dashboard accessible by a browser of the computing device; sending one or more SMS messages to the computing device; sending one or more emails accessible by the computing device; generating one or more notifications via the application of tire computing device; the like: or any combination thereof. The method may include notifying one or more medical professionals (e.g., veterinarian) of the trend values as compared to the threshold trend, the trend, or the deviation from the trend. The displaying on the application or the dashboard may include: displaying one or more numerical values associated with a central tendency (e.g., median, mean, mode) of one or more traits of the animal, a pet health device, or both; displaying one or more previously occurring measurements associated with the animal, the pet health device, or both; one or more charts displaying a plurality of numerical values related to a plurality of measurements associated with the animal, the pet health device, or both; and / or one or more trendlines on the one or more charts or one or more other charts. The one or more trendlines may include the one or more trendlines as determined according to the present teachings. The displaying on the application may include displaying one or more threshold trends and / or threshold values, trendlines associated with the threshold values, or both. The displaying on the application may include both displaying one or more trendlines based on the data and based on the threshold values. The threshold trendline based on the threshold value(s) may use as a starting point, the observed starting point of the data, the adjusted starting point of the data, or both. This may aid in providing a visual comparison to a user. Displaying on the application or the dashboard may include displaying one or more predicted times the animal is expected to conduct a predicted behavior based on the one or more trends.

[0081] The method may include notifying the user via the user interface of the computing device of one or more potential health conditions of the animal. Potential health conditions may be those such as describedin U.S. Provisional Application Nos. 63 / 490,990 and 63 / 490,910, both filed on March 17, 2023 and PCT Application Nos. PCT / US2024 / 020406 and PCT / US2024 / 020390, both filed on March 18, 2024, all of which are incorporated herein by reference in their entireties for all purposes.

[0082] The method may include notifying the user via the user interface of the computing device of one or more recommended lifesty le changes for the animal (e.g., diet, activity, environment). For example, if an animal’s weight is increasing over an expected trend, the recommended lifesty le changes may include reduced food intake, different food, and / or increased physical activity. As another example, if a temperature of an ambient environment seems to be below a typically measured temperature, the recommendation may include increasing the room temperature and / or providing the animal with a layer of clothing. As another example, if waste patterns change such as to find constipation (heavier stool, less frequent stool), the recommendations may include increased water intake and / or more physical activity.

[0083] The method may be repeatedly or iteratively performed once further later data signals are obtained. The later data entries and additional data may be converted to be part of the plurality of initial data entries and further data once subsequent later data signals are received. In essence, one or more trends may be updated to capture the newly collected data with most or all of the historical data and / or may be moving trends.

[0084] Illustrative Examples

[0085] FIGS. 1 and 2 illustrate a system 10. The system 10 includes a plurality of pet health devices 20. The pet healdr devices 20 include one or more litter devices 500, water dispensers 600, feeders 700. The system 10 includes one or more visual devices 110. The visual device(s) 110 may be cameras 111. The visual device(s) 110 may be separate from the pet health devices 20 (as shown in FIG. 1) or integrated into the pet health device(s) 20 (as shown in FIG. 2) The system also includes one or more computing devices 12. The computing device(s) 12 may be personal computing devices 14. Personal computing devices 14 may include mobile phones 16. tablets 18. and / or the like. The pet health device(s) 20. camera 110. and / or personal computing devices 12 may all be in communication (e.g.. two-way) with another computing device 12, such as a remote computing device 24. Communication may be via one or more communication hubs 22 (e.g., router, antenna). The system 10 may be set up as a cloud-computing system 26 or an edgecomputing system 28. It is also possible that edge-computing may do most of the computing on onboard controllers 100 of the pet health devices 20, then transmit to a cloud-computing system 26.

[0086] FIG. 3 illustrates varying views (e.g.. user interfaces, screens) of an application 36. The application includes varying views on a user interface 38 of a computing device 12. The computing device 12 may be a personal computing device 14 (e g., mobile phone, tablet). The computing device 12 may have an application 36 running thereon. The application 36 may create and display a notification 40 on the user interface 38. The application 36 may be able to display and notify a user of various data related to an animal 1 and their use of various pet health devices and sensing devices. The application 36 may display data specific to an individual animal 1. The application 36 may display data related to any of the pet health devices 20 and / or sensing devices 102. For example, a water dispenser 600. litter device 500, mass sensor(s) 104. and the like. It can be readily apparent how the illustrative example relative to water dispenser datacould be useful for feeder data. The application 36 may display data related to trends 42 of specific pet health devices, sensing devices, or even across the system as a whole. For example, the application 36 may display one or more trendlines 43 associated with the data. The one or more trendlines 43 may be a result from a regression line analysis. The one or more trendlines 43 may aid in determining an adjusted starting point value 86 and an adjusted ending point value 88 which may then be used for determining a calculated percentage change value 92. The one or more trendlines 43 or values therefrom, such as the percentage change value 92, may be compared against one or more thresholds and / or threshold values 90. The one or more thresholds 90 may also include and / or be displayed as one or more trendlines with a comparison slope value 82. A comparison percentage change value 91 may be associated with the threshold 90. For example, a pet undergoing veterinarian recommended weight loss may have a threshold comparison percentage change value 91 established for a healthy amount of weight loss. The calculated percentage change value 92 being over or under the comparison percentage change value 91 may result in one or more notifications 40.

[0087] FIG. 4 illustrates a screen 39 of an application 36 configured to be displayed on a user interface 38. The screen 39 identifies the animal 1 the data displayed on the screen 39 refers to. The screen 39 provides for a chart 52. The chart 52 is illustrated a scatter plot chart 54. The chart 52 illustrates different measured weights 56 of an animal 1 at different times of measurement. In this example, the weight 56 of the animal 1 is measured and recorded each time the animal 1 utilizes a litter device 500 (not shown) equipped with mass sensor(s) 104 (not shown). The screen 39 displays tire most recent measurement 62 associated with a measured trait 64 of an animal 1. It is also possible the screen illustrates a statistical central tendency value (not shown) also associated with the measured weights of the animal. For example, the central tendency value may be displayed as the mean, median, or mode over a period of time (e.g., daily, weekly, monthly, etc.).

[0088] FIG. 5 illustrates a screen 39 of an application 36 configured to be displayed on a user interface 38. The screen 36 displays a plurality of statuses relative to a specific pet health device 20, such as a litter device 500. The screen 39 displays the most recent measurement 62 associated with a measured trait 64 of an animal 1. In this example, the most recent measurement 62 is the most recent weight 66 of the animal. The screen 39 also displays a recent activity log 68 relative to a health device 20.

[0089] FIG. 6 illustrates a chart 52 with varying trend lines 43. FIGS. 7 and 8 illustrate the data behind the chart 52. The chart 52 may be displayed to a user via a user interface 38 (such as in FIGS. 3-5) or solely used on the backend of the system 10 (not shown) for trend analysis. The chart 52 is a line chart 70. The line chart 70 illustrates the measured weight 64 (or any other measured trait 66 or sensed condition) of an animal over multiple days.

[0090] For example, a daily measurement 62 may be taken at a certain time each day (first litter device use after 7 am) or may be a central tendency value over the course of the day (e.g., mean, mode, median of weight).

[0091] The chart 52 also illustrates varying trend and / or regression lines 43. The chart 52 illustrates an average trendline 72. The average trendline 72 illustrates the average of the measured weights (or of other data on a line or scatter chart).

[0092] The chart 52 illustrates a median trendline 74. The median trendline 74 illustrates the median of the values.

[0093] The chart 52 illustrates a mode trendline 76. The mode trendline 76 illustrates a mode of the values.

[0094] The chart 52 illustrates a least squares regression trendline 78.

[0095] To plot the least squares regression trendline 78, the calculation may be free of employing any averages (e.g., mean), or even other similar values (e.g., median, mode). The least squares regression method may be applied to data over a defined period of time 80 (“trailing time period”). As provided in this illustrative example, the data is a daily weight of an animal provided in pounds. Via the least squares regression method, a best fit linear trendline may be applied to the data which is the least squares regression trendline 78. The least squares regression method determines a linear equation (y = mx +b) for the best fit linear trendline. A slope (m) 82 of the trendline 78 may be determined. A y-intercept value (b) 84 may also be determined. Based on the least squares regression method, an adjusted starting point value 86 and adjusted ending point value 88 over the trailing time period 80 are calculated.

[0096] The slope 82, adjusted values 86, 88, or further derived data can be compared to a threshold trend 90 (e.g., threshold trend value). In this example, the threshold trend 90 is provided as a threshold comparison percentage change value. As an example, the threshold trend 90 may be provided by a medical professional and applicable to a certain trailing time period duration. A percentage change value 92 from the adjusted starting point value 86 to the adjusted ending point value 88 is determined.Adjusted Ending Point Value 88 - Adjusted Starting Point Value 86 x 100%Adjusted Starting Point Value 86The percentage change value 92 is compared to the threshold trend value 90. In this example, the percentage change 92 exceeds the threshold trend value 90. Exceeding the threshold trend 90 may be a deviation indicative of an issue and trigger further actions. For example, exceeding the threshold trend 90 may result in one or more notifications 70 via an application 36 (such as shown in FIG. 3 or 9).

[0097] FIGS. 7-8 also illustrate varying values as disclosed herein. The “Total” of the Day column may correlate to and be an example of a “Sequence Aggregation Value.” The "Count” may correlate to and be an example of a "Count Value.” The "Total” of the Weight column may correlate to and be an example of an “Aggregated Data Value.” The “Total” of the xA2 column may correlate to and be an example of an “Aggregated Square Value.” The “Total” of the xy column may correlate to and be an example of an “Aggregated Product Value.”

[0098] FIG. 9 illustrates varying views of an application 36 on a user interface 38 of a computing device 12. The computing device 12 may be a personal computing device 14 (e.g., mobile phone, tablet). The computing device 12 may have an application 36 running thereon. The application 36 may create and display a notification 40 on the user interface 38. The application 36 may be able to display and notify a user of deviation from trends specific to an animal and / or pet health device. The application 36 may be ableto notify a user of the potential presence of one or more health issues based on one or more identified trends and / or deviations from those trends.

[0099] FIGS. 10 and 11 illustrate a litter device 500 as an exemplary pet health device 20. 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 incudes 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.

[0100] The bezel 516 supports a controller 100. The bezel 516 supports one or more sensing devices 102. The sensing device(s) 102 may include one or more laser sensors 108. The sensing device(s) 102 have a line of sight 524 into at least the interior of the chamber 502. The sensing device(s) 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 518 and bezel 516 to also be tilted. This angle allows for the sensing device(s) 102 to have line of sight into the interior of the chamber 502 as opposed to solely across the entry opening 518.

[0101] The litter device 500 also includes one or more mass sensors 104 as one or more sensing devices 102. The one or more mass sensors 104 may be located at the base 504.

[0102] The litter device 500 may include one or more temperature sensors 134 as one or more sensing devices 102. The one or more temperature sensors 134 may be affixed to the bezel 516.

[0103] The litter device 500 may include one or more touch sensors 138 as one or more sensing devices 102. For example, one or more touch sensors 138 may be integrated into a step 526 of the litter device 500.

[0104] FIGS. 12-14 illustrate a pet health device 20, 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. Inside of the water dispenser 600 is a reservoir 608. The fresh water tank 604 releases fresh water into the reservoir 608 via a valve assembly 610. The water from the reservoir 608 is transported to the serving bowl 602 via an actuation means 612. An example actuation means 612 is a carousel 614. The carousel 614 moves the water toward a spout 616. The water is then able to exit via the spout 616 into the serving bowl 602. The carousel 614 may also work to recirculate water in the reservoir, collect water for disposing into the used water tank 606. or both.

[0105] The water dispenser 600 houses a controller 100. The controller 100 may include a printed circuit board (“PCB”).

[0106] The water dispenser 600 includes one or more sensing devices 102. Sensing device(s) 102 is illustrated as one or more mass sensors 104. The mass sensors 104 are shown as a scale 106 at the base of the water dispenser 60.

[0107] A camera 110 may be located toward the front of the water dispenser 600. The camera 110 may be in electrical communication with the controller 100.

[0108] FIGS. 15 and 16 illustrate a pet health device 20. 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. The feeder 700 includes a housing 702. The housing 702 includes a base portion 704, intermediate portion 706. and a chamber portion 708. The chamber portion 708 includes a hopper 710. Located between the intermediate portion 706 and the base portion 704 is a feeding cavity 712. The base portion 704 includes a serving area 714. The serving area 714 includes a feeding dish 716. The feeder 700 may include a lid 718. The feeding dish 716 may then be able to be covered by a lid 718. The feeding dish 716 is in communication with a chute 720 such that food (not shown) can be transferred into the feeding dish 716 via the chute 720. The feeder 700 includes a controller 100.

[0109] The feeder 700 includes a sensing tower 722. The sensing tower 722 houses one or more sensing devices 102. The sensing device(s) 102 may include one or more laser sensors 108. The sensing tower 722 extends through the hopper 710, through the bottom to the top. Thus, the sensing device(s) 102 has a line of sight into the hopper 710.

[0110] The feeder 700 includes a dispenser 724. The dispenser 724 is located in a cradle 726. The dispenser 70 includes a rocker body 728 and a fin 730. The rotation of the dispenser 724 results in food stored in the hopper 710 transferring down to the feeding dish 716. For example, via the chute 720.[01U] FIGS. 17-19 illustrate a pet health device 20, a feeder 700. The feeder 700 is an automated feeder. The feeder may be beneficial in presenting single serve and / or wet food to an animal. The feeder 700 includes a housing 702. The housing 702 provides for a container display opening 742. A container base 740 (e.g., an open container 734) is able to be presented via the container display opening 742 for access and consumption of food held therein by an animal. The feeder 700 may include a lid 718. The lid 718 may close or open such as to conceal or expose the container display opening 742 and / or a container base 740 (e.g., open container 734).

[0112] The feeder 700 includes a container storage subassembly 732. The container storage subassembly 732 stores a plurality of containers 734. The housing 702 includes a base portion 704.

[0113] The feeder 700 includes a waste collection subassembly 736 located in the base portion 704. The waste collection subassembly 736 is able to receive both a lid 738 and container base 740 of a container 734.

[0114] The feeder 700 includes a container handling subassembly 744. The container handling subassembly 744 holds a container 734 after retrieval from a container storage subassembly 732. The container handling subassembly is able to move linearly from the container storage subassembly 732 toward a front, feeding area of the feeder 700. This allows for presentation of the container base 740.

[0115] The feeder 700 includes a container opening subassembly 746. The container opening subassembly 746 is configured to remove a lid 738 of a container 734.

[0116] The feeder 700 includes a controller 100. The controller 100 may be affixed in an interior of the feeder 700.

[0117] 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 rmit 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 maimer.

[0118] 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.

[0119] 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 tenns “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.

[0120] 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.

[0121] 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 skillin 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 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. 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 monitoring behavior of an animal relative to one or more pet health devices, the method including: a) one or more processors automatically receiving one or more initial data from a start time related to the animal and / or the one or more pet health devices, wherein the one or more initial data are related to a measured trait and / or a sensed condition of the animal and / or the one or more pet health devices; b) the one or more processors automatically receiving one or more later data from an end time related to the animal and / or the one or more pet health devices, wherein the one or more later data are related to the measured trait and / or the sensed condition of the animal and / or the one or more pet health devices; c) the one or more processors automatically determining one or more trend values associated with the one or more initial data and the one or more later data; d) the one or more processors automatically comparing tire one or more trend values to one or more threshold values and determining if the one or more trend values is below, meets, or exceeds the one or more threshold values; e) based on the comparison of the one or more trend values to tire one or more threshold values, the one or more processors automatically : i) adjusting one or more operations of the one or more pet health devices; ii) notifying a user via a user interface on a computing device of one or more results from the comparing the one or more trend values to the one or more threshold values; iii) notifying the user via the user interface of the computing device of one or more potential health conditions of the animal; iv) notifying the user via the user interface of the computing device of one or more recommended lifestyle changes for the animal; or v) any combmation thereof.Claim 2. The method of Claim 1. wherein the one or more threshold values includes a comparison percentage change value and / or a comparison slope value (e.g., threshold rate of change).Claim 3. The method of Claim 1, wherein the one or more threshold values is determined and / or provided by one or more medical professionals, animal behavior specialists, trend data from a larger population database, one or more earlier trendlines of data related to the animal, or any combination thereof.Claim 4. The method of Claim 3, wherein the one or more threshold values is provided by the one or more medical professionals, the one or more animal behavior specialists, or both.Claim 5. The method of Claim 2, wherein determining the one or more trend values includes determining one or more trendlines over a trailing period of time.Claim 6. The method of Claim 5, wherein determining the one or more trend values includes determining a slope value, a percentage change value, or both of the one or more trendlines.Claim 7. The method of Claim 6, wherein the one or more trendlines includes one or more regression lines.Claim 8. The method of Claim 6. wherein the comparing the one or more trend values to the one or more threshold values includes comparing the slope value, the percentage change value, or both of the one or more trendlines to the comparison slope value, the comparison percentage change value, or both of the one or more threshold values.Claim 9. The method of Claim 8, wherein the trailing time period begins at the start time and ends at the end time.Claim 10. The method of Claim 8. wherein the one or more regression lines includes a simple trendline from a starting point value associated with the initial data to an ending point value associated with the later data and excludes taking any intervening values into consideration.Claim 11. The method of Claim 8, wherein the method includes the one or more processors automatically receiving one or more intennediate data from an intermediate time period between the start time and the end time related to the animal and / or the one or more pet health devices, wherein the one or more intermediate data are related to the measured trait and / or the sensed condition of the animal and / or the one or more pet health devices.Claim 12. The method of Claim 11, wherein the one or more trend values are also associated with the one or more intermediate data.Claim 13. The method of Claim 7, wherein the determining of the one or more regression lines is free of calculating any mean values.Claim 14. The method of Claim 7, wherein the one or more regression lines includes a least squares regression line determined using a linear least squares regression method.Claim 15. The method of Claim 14. wherein values for applying the linear least squares regression method include a starting point value, one or more intervening point values, and an end point value over a trailing time period; and wherein the starting point value is associated with the initial data, the one or more intervening point values are associated with the one or more intermediate data, and the ending point value is associated with the later data.Claim 16. The method of Claim 15. wherein a slope of the least squares regression line is automatically determined based on the linear least squares regression method.Claim 17. The method of Claim 16, wherein an adjusted starting point value and an adjusted ending point value are automatically determined for the trailing time period based on the slope.Claim 18. The method of Claim 17, wherein a percentage difference between the adjusted ending point value and the adjusted starting point value is the percentage change difference value of the one or more trend values.Claim 19. The method of Claim 18, wherein die percentage change difference derived from the linear least squares regression method is compared to the comparison percentage change value.Claim 20. The method of Claim 17, wherein the slope derived from the linear least squares regression method is compared to the comparison slope value of the one or more threshold values.Claim 21. The method of Claim 1, wherein the one or more trend values being less than or greater than the one or more threshold trend values is indicative of too rapid of weight gain, excessive weight gain, too rapid of weight loss, excessive weight loss, excessive food consumption, insufficient food consumption, excessive water consumption, insufficient food consumption, or a combination thereof.Claim 22. The method of Claim 21, wherein the one or more trend values being less than or greater than the one or more threshold trend values is indicative of too rapid of weight gain, too rapid of weight loss, or both.Claim 23. The method of Claim 1, wherein the one or more pet health devices include one or more litter devices, feeders, liquid dispensers, weight scales, resting devices (e.g., pet bed, crate), wearables (e.g., collar, chip), the like, or any combination thereof.Claim 24. The method of Claim 1, wherein the one or more initial data, one or more intermediate data, and / or the one or more later data are correlated with additional data, the additional data including: an identification of a specific pet health device from which the initial, intervening and / or the later data originated; a date and / or time stamp from when the initial, intervening, and / or the later data was generated; an identification of a specific animal associated with measured trait and / or sensed condition; and / or a user account and / or household associated with the specific health device and / or the specific animal.Claim 25. The method of Claim 1, wherein the plurality of initial data, one or more intermediate data, and / or the later data include or are associated with one or more of the following: entry of the animal into the pet health device; exit of the animal into the pet health device; detection of an object by a laser sensor; the animal within detecting proximity to the pet health device; mass of an animal; mass of an overall pet health device or a specific portion of the pet health device; mass of a pet health device prior to use by the animal; mass of a pet health device during use by the animal; mass of a pet health device after use by the animal; mass of waste disposed by the animal: mass of the pet health device at a predetermined time or time interval; mass and / or volume of food present within a pet health device; mass and / or volume of food consumed by the animal; mass and / or volume of liquid present within a pet health device; mass and / or volume of liquid consumed by the animal; body temperature of the animal; temperature of one or more components of the pet health device; temperature of an ambient environment in which the animal or the pet health device is located; one or more videos, frames, and / or images of an animal, an exterior of a health device, an interior of a health device, and / or an ambient environment; one or more videos, frames, and / or images of waste excreted into a litter device; recording of one or more sounds; electromagnetic field(s) associated with an animal (e.g., EEG. ECG); biomarkers or vitals including heart rate, blood oxygen level, body temperature, and / or respiratory rate of an animal; position and / or location of an animal; change in status of a touch sensor;acceleration and / or velocity associated with an animal; identification data from an identifier; identity of an animal associated with an identifier; identity of an animal from visual recognition.Claim 26. The method of Claim 25. wherein one or more initial data signals, intermediate data signals, and / or later data signals generated from sensing the one or more measured traits and / or sensed conditions are used to derive further calculated data based on one or more measured traits and / or sensed conditions, and includes one or more of: duration of any of the initial, intervening, and / or later data signals; time elapsed (e.g., time interval) between one data signal and a subsequent occurring similar data signal; duration of the animal at, in, or otherwise using the pet health device; duration of the animal in proximity to the pet health device; frequency of use of the pet health device over one or more time periods; change in mass of an animal; change in mass of the pet health device; time duration associated with an increase or decreased in monitored mass; amount of food consumed over a single visit or any other period of time (e.g., day, week); amount of food remaining in a feeder; amount of liquid consumed over a single visit or any other period time (e.g.. day, week); amount of liquid remaining in a liquid dispensing device; type of waste (stool, urine) eliminated by the animal; duration of time an animal is at rest or sleeping; duration of time an animal is moving; change in temperature; time duration associated with an increase or decrease in temperature; timestamp associated with a change in status of a touch sensor; duration associated with a change in status of a touch sensor.Claim 1. The method of Claim 26, wherein the duration, the frequency, tire amount, or any other values of any of the calculated data can be from a single visit, a portion of a day, daily, weekly, monthly, quarterly, annually, and / or any other time period.Claim 28. The method of Claim 1, wherein the method includes the adjusting of the one or more operations of the one or more pet health devices which includes: dispensing a lesser or greater amount of food; dispensing a different food or blend of type of food;changing the accessibility to the food (e.g., opening / closing lid at a certain time based on expected arrival time of animal); dispensing food at lesser or greater frequencies; circulating and / or refilling a liquid (e.g.. water) more or less frequently; dispensing a lesser or greater amount of clean litter into a litter device; increasing or decreasing a frequency at which to alert the user for cleaning a waste receptacle of a litter device; and / or turning a light on at an expected usage time of the animal.Claim 29. The method of Claim 1, wherein the method includes the notifying the user which includes: displaying information or a notification via an application as part of the computing device; displaying information or a notification via a dashboard accessible by a browser of the computing device; sending one or more SMS messages to the computing device; sending one or more emails accessible by the computing device; generating one or more notifications via the application of the computing device; the like; or any combination thereof.Claim 30. The method of Claim 1, wherein the method further includes automatically notifying one or more medical professionals (e.g., veterinarian) of tire one or more results from comparing the one or more trend values to the one or more threshold values.Claim 31. The method of Claim 29, wherein the displaying on the application or the dashboard includes: displaying one or more numerical values associated with a central tendency (e.g.. median, mean, mode) of one or more traits of the animal, a pet health device, or both; displaying one or more previously occurring measurements associated with the animal, the pet health device, or both; one or more charts displaying a plurality of numerical values related to a plural i tx of measurements associated with the animal, the pet health device, or both; and / or one or more trendlines on the one or more charts or one or more other charts.Claim 32. The method of Claim 31, wherein the one or more trendlines include a simple trendline or a least squares regression line.Claim 33. The method of Claim 1, wherein the one or more sensing devices are associated with one or more pet health devices, the animal, or both.Claim 34. The method of Claim 1, wherein the one or more processors may be located locally on the one or more pet health devices, remotely from the one or more pet health devices (e.g., cloud computing), or a combination of both (e.g., edge computing).Claim 35. The method of Claim 1 , wherein the method is repeatedly performed once further later data is obtained.Claim 36. The method of Claim 1. wherein the one or more initial data, the one or more later data, and / or one or more intermediate data are related to one or more initial data signals, initial data entries, intermediate data signals, intermediate data entries, later data signals, later data entries, or a combination thereof.Claim 37. The method of Claim 36, wherein the one or more initial data signals, intermediate data signals, and / or later data signals are automatically generated from one or more sensing devices associated with the animal and / or the one or more pet health devices.Claim 38. The method of Claim 37, wherein the one or more initial data signals, intermediate data signals, and / or later data signals may be the same as or resulting from one or more status signals from one or more sensing devices.Claim 39. The method of Claim 38. wherein the one or more initial data signals, intermediate data signals, and / or later data signals are automatically relayed to and received by the one or more processors.Claim 40. The method of Claim 1, wherein the method includes the one or more processors automatically converting and storing a plurality of initial data signals as one or more initial data entries in one or more storage mediums.Claim 41. The method of Claim 1, wherein the method includes the one or more processors automatically calculating further initial data from the one or more initial data and storing the further initial data in the one or more storage mediums.Claim 42. The method of Claim 1 , wherein the method includes the one or more processors automatically converting and storing a plurality of later data signals as one or more later data entries in one or more storage mediums.Claim 43. The method of Claim 1, wherein the method includes the one or more processors automatically calculating further later data from the one or more later data and storing the further later data in the one or more storage mediums.Claim 44. The method of Claim 1, wherein the method includes the one or more processors automatically converting and storing a plurality of intermediate data signals as one or more intermediate data entries in one or more storage mediums.Claim 45. The method of Claim 1 , wherein the method includes the one or more processors automatically calculating further intermediate data from one or more intermediate data and storing the further intermediate data in the one or more storage mediums.Claim 46. The method of Claim 24, wherein the initial data, intermediate data, and / or later data is correlated to additional data prior to. simultaneous with, and / or after being stored in the one or more storage mediums.Claim 47. A method for monitoring behavior of an animal relative to one or more pet health devices, the method including: a) one or more processors automatically receiving one or more initial data from a start time related to the animal and / or the one or more pet health devices, wherein the one or more initial data are related to a measured trait and / or a sensed condition of the animal and / or the one or more pet health devices; b) the one or more processors automatically receiving one or more later data from an end time related to the animal and / or the one or more pet health devices, wherein the one or more later data are related to the measured trait and / or the sensed condition of the animal and / or the one or more pet health devices; c) the one or more processors automatically determining one or more trend values associated with the one or more initial data and the one or more later data; d) the one or more processors automatically comparing the one or more trend values to one or more threshold values and determining if the one or more trend values is below, meets, or exceeds the one or more threshold values; e) based on the comparison of the one or more trend values to the one or more threshold values, the one or more processors automatically: i) adjusting one or more operations of the one or more pet health devices; ii) notifying a user via a user interface on a computing device of one or more results from the comparing the one or more trend values to the one or more threshold values; iii) notifying the user via the user interface of the computing device of one or more potential health conditions of the animal;iv) notifying the user via the user interface of the computing device of one or more recommended lifestyle changes for the animal; or v) the like; or vi) any combmation thereof.Claim 48. The method of Claim 47, wherein the one or more threshold values includes a comparison percentage change value and / or a comparison slope value (e.g., threshold rate of change).Claim 49. The method of Claim 47 or 48, wherein the one or more threshold values is determined and / or provided by one or more medical professionals, animal behavior specialists, trend data from a larger population database, one or more earlier trendlines of data related to the animal, or any combination thereof.Claim 50. The method of any of Claims 47 to 49, wherein the one or more threshold values is provided by the one or more medical professionals, the one or more animal behavior specialists, or both.Claim51. The method of any of claims 47 to 50, wherein determining the one or more trend values includes determining one or more trendlines over a trailing period of time.Claim52. The method of Claim 51, wherein determining tire one or more trend values includes determining a slope value, a percentage change value, or both of the one or more trendlines.Claim53. The method of any of Claims 51 to 52, wherein the one or more trendlines includes one or more regression lines.Claim 54. The method of any of Claims 51 to 53, wherein the comparing the one or more trend values to the one or more threshold values includes comparing the slope value, the percentage change value, or both of the one or more trendlines to the comparison slope value, the comparison percentage change value, or both of the one or more threshold values.Claim 55. The method of any of Claims 47 to 54, wherein a trailing time period begins at the start time and ends at the end time.Claim 56. The method of any of Claims 53 to 55. wherein the one or more regression lines includes a simple trendline from a starting point value associated with the initial data to an ending point value associated with the later data and excludes taking any intervening values into consideration.Claim 57. The method of any of Claims 47 to 56, wherein the method includes the one or more processors automatically receiving one or more intermediate data from an intermediate time period betweenthe start time and the end time related to the animal and / or the one or more pet health devices, wherein the one or more intermediate data are related to the measured trait and / or the sensed condition of the animal and / or the one or more pet health devices.Claim 58. The method of Claim 57, wherein the one or more trend values are also associated with the one or more intermediate data.Claim 59. The method of any of Claims 47 to 58, wherein the determining of the one or more regression lines is free of calculating any mean values.Claim 60. The method of any of Claims 53 to 59, wherein the one or more regression lines includes a least squares regression line determined using a linear least squares regression method.Claim 61. The method of Claim 60, wherein values for applying the linear least squares regression method include a starting point value, one or more intervening point values, and an end point value over a trailing time period; and wherein the starting point value is associated with the initial data, the one or more intervening point values are associated with the one or more intermediate data, and the ending point value is associated with the later data.Claim 62. The method of any of Claims 60 or 61, wherein a slope of the least squares regression line is automatically determined based on the linear least squares regression method.Claim 63. The method of Claim any of Claims 47 to 62, wherein an adjusted starting point value and an adjusted ending point value are automatically determined for the trailing time period based on the slope.Claim 64. The method of Claim 63, wherein a percentage difference between the adjusted ending point value and the adjusted starting point value is the percentage change difference value of the one or more trend values.Claim 65. The method of Claim 64, wherein the percentage change difference derived from the linear least squares regression method is compared to the comparison percentage change value.Claim 66. The method of Cany of Claims 47 to 65, wherein the slope derived from the linear least squares regression method is compared to the comparison slope value of the one or more threshold values.Claim 67. The method of any of Claims 47 to 66, wherein the one or more trend values being less than or greater than the one or more threshold trend values is indicative of too rapid of weight gain,excessive weight gain, too rapid of weight loss, excessive weight loss, excessive food consumption, insufficient food consumption, excessive water consumption, insufficient food consumption, or a combination thereof.Claim 68. The method of any of Claims 47 to 67, wherein the one or more trend values being less than or greater than the one or more threshold trend values is indicative of too rapid of weight gain, too rapid of weight loss, or both.Claim 69. The method of any of Claims 47 to 68 wherein the one or more pet health devices include one or more litter devices, feeders, liquid dispensers, weight scales, resting devices (e.g., pet bed, crate), wearables (e.g., collar, chip), the like, or any combination thereof.Claim 70. The method of any of Claims 47 to 69, wherein the one or more initial data, one or more intermediate data, and / or the one or more later data are correlated with additional data, the additional data including: an identification of a specific pet health device from which the initial, intervening and / or the later data originated; a date and / or time stamp from when the initial, intervening, and / or the later data was generated; an identification of a specific animal associated with measured trait and / or sensed condition; and / or a user account and / or household associated with the specific health device and / or the specific animal.Claim 71. The method of any of Claims 47 to 70, wherein the plurality of initial data, one or more intermediate data, and / or the later data include or are associated with one or more of the following: entry of the animal into the pet health device; exit of the animal into the pet health device; detection of an object by a laser sensor; the animal within detecting proximity to the pet health device; mass of an animal; mass of an overall pet health device or a specific portion of the pet health device; mass of a pet health device prior to use by the animal; mass of a pet health device during use by the animal; mass of a pet health device after use by the animal; mass of waste disposed by the animal; mass of the pet health device at a predetermined time or time interval; mass and / or volume of food present within a pet health device; mass and / or volume of food consumed by the animal; mass and / or volume of liquid present within a pet health device;mass and / or volume of liquid consumed by the animal; body temperature of the animal; temperature of one or more components of the pet health device; temperature of an ambient environment in which the animal or the pet health device is located; one or more videos, frames, and / or images of an animal, an exterior of a health device, an interior of a health device, and / or an ambient environment; one or more videos, frames, and / or images of waste excreted into a litter device; recording of one or more sounds; electromagnetic field(s) associated with an animal (e.g.. EEG. ECG); biomarkers or vitals including heart rate, blood oxygen level, body temperature, and / or respiratory rate of an animal; position and / or location of an animal; change in status of a touch sensor; acceleration and / or velocity associated with an animal; identification data from an identifier; identity of an animal associated with an identifier; identity of an animal from visual recognition.Claim 72. The method of any of Claims 47 to 71 wherein one or more initial data signals, intermediate data signals, and / or later data signals generated from sensing the one or more measured traits and / or sensed conditions are used to derive further calculated data based on one or more measured traits and / or sensed conditions, and includes one or more of: duration of any of the initial, intervening, and / or later data signals; time elapsed (e.g., time interval) between one data signal and a subsequent occurring similar data signal; duration of the animal at. in, or otherwise using the pet health device; duration of the animal in proximity to the pet health device; frequency of use of the pet health device over one or more time periods; change in mass of an animal; change in mass of the pet health device; time duration associated with an increase or decreased in monitored mass; amount of food consumed over a single visit or any other period of time (e.g., day, week); amount of food remaining in a feeder; amount of liquid consumed over a single visit or any other period time (e.g., day, week); amount of liquid remaining in a liquid dispensing device; type of waste (stool, urine) eliminated by the animal; duration of time an animal is at rest or sleeping; duration of time an animal is moving;change in temperature; time duration associated with an increase or decrease in temperature; timestamp associated with a change in status of a touch sensor; duration associated with a change in status of a touch sensor.Claim 73. The method of Claim 72, wherein the duration, the frequency, tire amount, or any other values of any of the calculated data can be from a single visit, a portion of a day, daily, weekly, monthly, quarterly, annually, and / or any other time period.Claim 74. The method of any of Claims 47 to 73, wherein the method includes the adjusting of the one or more operations of the one or more pet health devices which includes: dispensing a lesser or greater amount of food; dispensing a different food or blend of type of food; changing the accessibility to the food (e.g., opening / closing lid at a certain time based on expected arrival time of animal); dispensing food at lesser or greater frequencies; circulating and / or refilling a liquid (e.g., water) more or less frequently; dispensing a lesser or greater amount of clean litter into a litter device; increasing or decreasing a frequency at which to alert the user for cleaning a waste receptacle of a litter device; and / or turning a light on at an expected usage time of the animal.Claim 75. The method of any of Claims 47 to 74, wherein tire method includes the notifying the user which includes: displaying information or a notification via an application as part of the computing device; displaying information or a notification via a dashboard accessible by a browser of the computing device; sending one or more SMS messages to the computing device: sending one or more emails accessible by the computing device; generating one or more notifications via the application of the computing device; the like; or any combination thereof.Claim 76. The method of any of Claims 47 to 75. wherein the method further includes automatically notifying one or more medical professionals (e.g., veterinarian) of the one or more results from comparing the one or more trend values to the one or more threshold values.Claim 77. The method of any of Claims 47 to 76, wherein the displaying on the application or the dashboard includes: displaying one or more numerical values associated with a central tendency (e.g.. median, mean, mode) of one or more traits of the animal, a pet health device, or both; displaying one or more previously occurring measurements associated with the animal, the pet health device, or both; one or more charts displaying a plurality of numerical values related to a plurality of measurements associated with the animal, the pet health device, or both; and / or one or more trendlines on the one or more charts or one or more other charts.Claim 78. The method of Claim 77, wherein the one or more trendlines include a simple trendline or a least squares regression line.Claim 79. The method of any of Claims 47 to 78, wherein the one or more sensing devices are associated with one or more pet health devices, the animal, or both.Claim 80. The method of any of Claims 47 to 79, wherein the one or more processors may be located locally on the one or more pet health devices, remotely from the one or more pet health devices (e.g., cloud computing), or a combination of both (e.g., edge computing).Claim 81. The method of any of Claims 47 to 80, wherein the method is repeatedly performed once further later data is obtained.Claim 82. The method of any of Claims 47 to 81wherein the one or more initial data, the one or more later data, and / or one or more intennediate data are related to one or more initial data signals, initial data entries, intermediate data signals, intermediate data entries, later data signals, later data entries, or a combination thereof.Claim 83. The method of any of Claims 47 to 82, wherein the one or more initial data signals, intermediate data signals, and / or later data signals are automatically generated from one or more sensing devices associated with the animal and / or the one or more pet health devices.Claim 84. The method of Claim 83, wherein the one or more initial data signals, intermediate data signals, and / or later data signals may be the same as or resulting from one or more status signals from one or more sensing devices.Claim 85. The method of Claim 81 or 84, wherein the one or more initial data signals, intermediate data signals, and / or later data signals are automatically relayed to and received by the one or more processors.Claim 86. The method of any of Claims 47 to 85, wherein the method includes the one or more processors automatically converting and storing a plurality of initial data signals as one or more initial data entries in one or more storage mediums.Claim 87. The method of any of Claims 47 to 86, wherein the method includes the one or more processors automatically calculating further initial data from the one or more initial data and storing the further initial data in the one or more storage mediums.Claim 88. The method of any of Claims 47 to 87, wherein the method includes the one or more processors automatically converting and storing a plurality of later data signals as one or more later data entries in one or more storage mediums.Claim 89. The method of any of Claims 47 to 88, wherein the method includes the one or more processors automatically calculating further later data from the one or more later data and storing the further later data in the one or more storage mediums.Claim 90. The method of any of Claims 47 to 89, wherein the method includes the one or more processors automatically converting and storing a plurality of intermediate data signals as one or more intermediate data entries in one or more storage mediums.Claim 91. The method of any of Claims 47 to 90, wherein the method includes the one or more processors automatically calculating further intermediate data from one or more intermediate data and storing the further intermediate data in the one or more storage mediums.Claim 92. The method of any of Claims 47 to 91, wherein the initial data, intermediate data, and / or later data is correlated to additional data prior to, simultaneous with, and / or after being stored in the one or more storage mediums.Claim 93. A method for monitoring behavior of an animal relative to one or more pet health devices, the method including: a) receiving a pl ura 1 i ty of initial data signals over a first time period related to the animal and / or the one or more pet health devices, wherein the plurality of initial data signals are related to a measured trait and / or a sensed condition of the animal and / or the one or more pet health devices;b) optionally, converting and storing the plurality of initial data signals as one or more initial data entries in one or more storage mediums; c) optionally, calculating further data from the one or more initial data entries and storing the further data in the one or more storage mediums; d) receiving one or more later data signals from a later time or a later time period related to the animal and / or the one or more pet health devices, wherein the one or more later data signals are related to the measured trait and / or the sensed condition of the animal and / or the one or more pet health devices; e) optionally, converting and storing the one or more later data signals as one or more later data entries in the one or more storage mediums; f) optionally, calculating additional data from the one or more later data entries and storing the additional data in the one or more storage mediums; g) determining one or more trends associated with the initial data entries, the further data, the one or more later data entries, the additional data and related to the animal and / or the one or more pet health devices; h) comparing the one or more later data signals and / or the additional data to the one or more trends and determining if the one or more later data signals are within the trend or deviate from the trend; and / or comparing a trend inclusive of the one or more later data signals and / or the additional data to a threshold trend and determining if the trend is below, meets, or exceeds the threshold trend; i) based on the comparison, one or more of; i) adjusting one or more operations of the one or more pet health devices based on the trend, the deviation from the trend, and / or the trend comparison to the threshold trend; ii) notifying a user via a user interface on a computing device of the trend, the deviation from the trend, and / or the trend comparison to the threshold trend; iii) notifying the user via the user interface of the computing device of one or more potential health conditions of the animal; iv) notifying the user via the user interface of the computing device of one or more recommended lifestyle changes for the animal (e.g., diet, activity, environment); v) the like; or vi) any combination thereof.Claim 94. The method of Claim 93, wherein the plurality of initial data signals from the first time period include one or more initial data signals and one or more intermediate data signals.Claim 95. The method of Claim 93 or 94, wherein the one or more trends includes determining one or more trend values.Claim 96. The method of Claim 95, wherein the one or more trend values are those of any of Claims47 to 92.Claim 97. The method of any of Claims 93 to 96, wherein the threshold trend includes one or more threshold values.Claim 98. The method of Claim 97. wherein the one or more threshold values are those of any of Claims 47 to 92.Claim 99. The method any of Claims 93 to 98, wherein determining the one or more trends includes determining one or more trendlines and / or trend values according to any of Claims 47 to 92.Claim 100. The method of any of Claims 93 to 99, wherein the determining the one or more trends is achieved via executing statistical analysis, machine learning, artificial intelligence, the like, or any combination thereof.Claim 101. The method of any of Claims 93 to 100, wherein the statistical analysis includes determining a mean, mode, median, range, maximum, minimum, standard deviation, variance, minimum variable, maximum variable, kurtosis, skewness, the like, or any combination thereof related to the initial data entries, the further initial data, the later data entries, the further later data, or a combination thereof.Claim 102. The method of any of Claims 93 to 101, wherein the machine learning includes analysis of the initial data entries, the further initial data, the later data entries, the further later data, or a combination thereof with linear regression, logistic regression, support vector machine, hierarchal clustering, k-means clustering, self-organized mapping, the like, or a combination.Claim 103. The method of any of Claims 93 to 1 2. wherein the one or more trend and / or regression lines includes one or more linear trendlines, logarithmic trendlines, polynomial trendlines (including spline interpolation), power trendlines, exponential trendlines, and / or moving average (mean, median, mode) trendlines.Claim 104. The method of any of Claims 93 to 103, wherein one or more linear trendlines are utilized when data is expected to be substantially stable.Claim 105. The method of any of Claims 93 to 104, wherein one or more logarithmic trendlines are utilized when there is an expected high rate of change followed by stabilization (e.g., kitten to adult cat growth, pregnancy of an animal, intentional weight loss of an animal).Claim 106. The method of any of Claims 93 to 105, wherein one or more polynomial trendlines are utilized when data is expected to fluctuate (e.g., intentional weight loss after weight gain of an animal).Claim 107. The method of any of Claims 93 to 106, wherein the displaying on the application or the dashboard includes displaying one or more predicted times the animal is expected to conduct a predicted behavior based on the one or more trends.Claims 108. The method of any of Claims 93 to 107 incorporating any part of the method according to any of Claims 47 to 93.Claim 109. A method, system, or both according to any or all of the present teachings.

Images