A specially designed microcontroller with event-driven sensor data processing unit (EPU) is proposed to provide energy-efficient\nsensor data acquisition for Internet of Things (IoT) devices in rare-event human activity sensing applications. Rare-event sensing\napplications using a remotely installed IoT sensor device have a property of very long event-to-event distance, so that the inaccurate\nsensor data processing in a certain range of accuracy error is enough to extract appropriate events from the collected sensing data.\nThe proposed signal-to-event converter (S2E) as a preprocessor of the conventional sensor interface extracts a set of atomic events\nwith the specific features of interest and performs an early evaluation for the featured points of the incoming sensor signal. The\nconventional sensor data processing such as DSPs or software-driven algorithm to classify the meaningful event from the collected\nsensor data could be accomplished by the proposed event processing unit (EPU). The proposed microcontroller architecture\nenables an energy efficient signal processing for rare-event sensing applications.The implemented system-on-chip (SoC) including\nthe proposed building blocks is fabricated with additional 7500 NAND gates and 1-KB SRAM tracer in 0.18um CMOS process,\nconsuming only 20% compared to the conventional sensor data processing method for human hand-gesture detection.
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