Pet Activity Sensor Monitoring for Wellness Alert Detection
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Solution Overview
Problem
There is a need for a system and method to effectively monitor pet activity and health conditions to enhance pet safety and health monitoring.
Innovation Solution
A system and method that utilizes sensors, such as gyroscopes and magnetometers, to collect data on pet activity, analyze it, and generate wellness assessments, including health scores and alerts, which are communicated to pet owners through mobile devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive sensor data collection and analysis systems are implemented for pet health monitoring, then health detection accuracy is improved, but device complexity increases
Solution Approach 1:
The system divides the complex health monitoring task into separate modules: activity recognition module that processes sensor data to identify movements, health indicator determination module that calculates wellness metrics from activities, and alert generation module that notifies owners of potential issues. This segmentation allows each module to specialize in one function, improving overall detection accuracy while managing system complexity through modular design.
Solution Approach 2:
The computing system acts as an intermediary between the simple sensor data collection and the complex health assessment. It receives raw sensor data, processes it through multiple analysis layers (activity recognition, health indicator calculation), and outputs simplified wellness assessments and alerts to pet owners, thereby bridging the gap between raw data and actionable health insights.
2Reliability
If continuous pet activity monitoring is performed to detect health conditions early, then health management effectiveness is improved, but energy consumption increases
Solution Approach 1:
Instead of continuously processing all sensor data, the system periodically analyzes activity patterns at defined intervals. The computing system collects sensor data over time periods, then performs batch processing to recognize activities and calculate health indicators, reducing continuous computational energy consumption while maintaining effective health monitoring through regular assessment cycles.
Solution Approach 2:
The system processes only the necessary portion of sensor data required for health assessment rather than analyzing every single data point continuously. It focuses on key activity patterns and health indicators that are most relevant to pet wellness, performing partial processing that achieves effective health monitoring with reduced energy expenditure compared to exhaustive continuous analysis.
Data Source
AI summary
In one embodiment, a method includes accessing sensor data captured by sensors, wherein the sensor data is associated with a first pet, detecting activities of the first pet within a specified time period based on the sensor data, determining health indicators of the first pet based on one or more of the activities, wherein the health indicators are based on metrics associated with the one or more activities, generating a wellness assessment of the first pet based on the health indicators, wherein the wellness assessment comprises one or more of a wellness score or an alert of a possible medical condition, and sending instructions to a user device for presenting the wellness assessment of the first pet to a user.