Veterinary Acoustic Biofeedback Device for Animal Welfare Monitoring
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Solution Overview
Problem
Current methods for monitoring animal welfare are labor-intensive and inadequate in providing a comprehensive diagnostic of animal health, particularly in livestock and wildlife management, as they fail to effectively detect behavioral and pathological changes related to disease, distress, and environmental factors.
Innovation Solution
A veterinary acoustic and biofeedback device that utilizes sensors and machine learning algorithms to analyze acoustic, behavioral, and environmental data to determine animal welfare and pathological states, providing real-time feedback and alerts to caregivers through a wearable or peripheral device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual monitoring methods are used to track animal behavior and welfare, then caregivers can directly observe and assess animals, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The patent replaces manual mechanical observation with an automated electronic system comprising sensors, processors, and communication devices. The system automatically collects behavioral data through various sensors (accelerometers, gyroscopes, microphones) and processes this data to determine animal welfare states, eliminating the need for continuous manual monitoring while maintaining or improving assessment accuracy.
2Device complexity
If simple monitoring devices are used to track basic animal activities, then device complexity is reduced, but the ability to provide comprehensive diagnostic of animal health deteriorates
Solution Approach 1:
The patent implements a multi-functional monitoring system where a single device performs multiple functions: tracking physical activity through accelerometers, monitoring vocalizations through microphones, detecting environmental conditions through various sensors, and processing this data to assess multiple aspects of animal welfare including health status, behavioral states, and distress levels. This universal approach provides comprehensive diagnostics without requiring multiple separate devices.
Solution Approach 2:
The system segments the monitoring function into distinct sensor modules (motion sensors, audio sensors, environmental sensors) that can independently collect specific types of data, then integrates these segmented data streams through a processor to generate a comprehensive welfare assessment. This segmentation allows each component to remain relatively simple while the integrated system provides complete diagnostics.
3Loss of time
If continuous monitoring is implemented to detect behavioral changes in real-time, then timely detection of health issues is improved, but energy consumption and device resource usage increase
Solution Approach 1:
The patent implements periodic sampling of animal behavioral data rather than truly continuous monitoring. The system collects data at predetermined time intervals using the sensors, processes these periodic samples to detect behavioral changes, and triggers alerts only when significant changes are detected. This periodic approach reduces energy consumption compared to continuous monitoring while maintaining timely detection of health issues through strategic sampling.
Solution Approach 2:
The system performs full-depth analysis and processing only when necessary - specifically when behavioral changes exceed predetermined thresholds or when specific concerning patterns are detected. During normal periods, the system uses lighter processing and only performs essential monitoring functions, thereby reducing energy consumption while maintaining the capability for timely detection of health issues when they actually occur.
Data Source
AI summary
A device includes one or more sensors and one or more output components. The device receives, from the one or more sensors, data, and determines that the data is indicative of sound generated from an animal. Based at least in part on the data being indicative the sound generated from the animal, the device determines one or more biomarkers associated with the sound. The one or more biomarkers include at least an amplitude associated with the sound. The device determines that the one or more biomarkers fail to satisfy a threshold associated with a pathological state of the animal. The device then causes, based at least in part on the one or more biomarkers failing to satisfy the threshold, output of a notification via the one or more output components.