Mobile Disturbance Detection Using Repurposed Smart Devices

The patent changes the functional parameters of older smart devices by transitioning them from primary computing tasks to specialized disturbance detection and monitoring roles. The device's computational capabilities are repurposed through software-based neural network models that leverage the device's existing processing power for a different function, thereby extending its useful life and preventing resource waste.

The system enables older smart devices to serve themselves by performing disturbance detection and classification tasks autonomously. The device captures disturbances, processes them through local neural network models, and generates alerts without requiring constant connection to powerful central servers, thus utilizing the device's own computational resources effectively.

The patent extracts the complex disturbance analysis functionality into separate neural network models that are downloaded and executed on the older smart device. This separation allows the device to gain advanced disturbance detection capabilities without permanently altering its core architecture, maintaining versatility while managing complexity through modular, on-demand software components.

The system implements multi-functionality by enabling older smart devices to perform both their original functions and new disturbance detection tasks. The device serves multiple purposes: maintaining its primary computational role while simultaneously acting as a disturbance detection and classification device, thereby increasing versatility without requiring complete system redesign.