SRC: Sustainable Reactive Computing for Battery-free Edge Intelligence

This paper proposes SRC, a novel framework for efficient and reliable inference on battery-free smart Internet of Things (IoT) devices. SRC supports various configurations that follow reactive configuration while using the innovative state machine and a safe threshold mechanism to proactively halt operations, reducing store/load operations by up to 75%. It strategically stores essential convolutional neural network (CNN) data (layer, kernel, etc.) to optimize input/output feature map management. This reactive design allows seamless task resumption across power cycles, ensuring continuity in unpredictable energy environments. Experiments show significant gains, with SRC achieving on average ~ 81.85% reduction in read/write operations and approximately 57.18% improvement in sensing compared to conventional reactive methods based on the intermittent Energy Trace 1.