  Introducing HyperSense, our co-designed hardware and software system
efficiently controls Analog-to-Digital Converter (ADC) modules' data generation
rate based on object presence predictions in sensor data. Addressing challenges
posed by escalating sensor quantities and data rates, HyperSense reduces
redundant digital data using energy-efficient low-precision ADC, diminishing
machine learning system costs. Leveraging neurally-inspired HyperDimensional
Computing (HDC), HyperSense analyzes real-time raw low-precision sensor data,
offering advantages in handling noise, memory-centricity, and real-time
learning. Our proposed HyperSense model combines high-performance software for
object detection with real-time hardware prediction, introducing the novel
concept of Intelligent Sensor Control. Comprehensive software and hardware
evaluations demonstrate our solution's superior performance, evidenced by the
highest Area Under the Curve (AUC) and sharpest Receiver Operating
Characteristic (ROC) curve among lightweight models. Hardware-wise, our
FPGA-based domain-specific accelerator tailored for HyperSense achieves a 5.6x
speedup compared to YOLOv4 on NVIDIA Jetson Orin while showing up to 92.1%
energy saving compared to the conventional system. These results underscore
HyperSense's effectiveness and efficiency, positioning it as a promising
solution for intelligent sensing and real-time data processing across diverse
applications.
