Autonomous Wound Monitoring Through a Wireless Network of Smart Bandages

We present a novel approach to health monitoring through the development of a smart bandage network utilizing distributed machine learning (ML) and Bluetooth low energy (BLE) communication technology. Each smart bandage is equipped with an ultra-low-power microcontroller that hosts machine learning algorithms to analyze data from a network of attached sensor nodes in real time, enabling the detection of anomalies and immediate feedback through a portable edge unit. The edge-enabled central unit (ECU) facilitates communication with multiple smart bandages, employing BLE for efficient and reliable data transmission. Our system is designed for scalability, featuring a dynamic registration process that seamlessly integrates new bandages into the network, simplifying deployment and expanding coverage. By decentralizing data processing and implementing fault-tolerant communication strategies, the system ensures robust and continuous monitoring. This research advances healthcare technology by providing a scalable, energy-efficient, and dependable solution for real-time remote health monitoring in diverse clinical and nonclinical settings.