mlsanityData to 7 Oct 2026

HyperSense: Hyperdimensional Intelligent Sensing for Energy-Efficient Sparse Data Processing

arXiv 2401.10267 ↗First posted 4 Jan 2024cs.AR cs.AIcited by 7

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Abstract (arXiv)

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.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 11 of its 38 references that are in the map. First posted on arXiv 4 Jan 2024.

Builds on

11 of 38 references.

References · 11

  1. 2020YOLOv4: Optimal Speed and Accuracy of Object Detectioncited by 1,624
  2. 2020NVAE: A Deep Hierarchical Variational Autoencodercited by 635
  3. 2019Edge Intelligence: Paving the Last Mile of Artificial Intelligence with Edge Computingcited by 225
  4. 2022Constrained Few-shot Class-incremental Learningcited by 93
  5. 2021Brain-inspired computing: We need a master plancited by 51
  6. 2022GraphHD: Efficient graph classification using hyperdimensional computingcited by 28
  7. 2021Rethinking of Radar's Role: A Camera-Radar Dataset and Systematic Annotator via Coordinate Alignmentcited by 23
  8. 2023Operating critical machine learning models in resource constrained regimescited by 6
  9. 2022PISA: A Binary-Weight Processing-In-Sensor Accelerator for Edge Image Processingcited by 4
  10. 2023CamJ: Enabling System-Level Energy Modeling and Architectural Exploration for In-Sensor Visual Computingcited by 3
  11. 2020Neurosciences and 6G: Lessons from and Needs of Communicative Brainscited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 2; 2026: 2.

7 papers.