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

arXiv: https://arxiv.org/abs/2401.10267 · HTML: https://mlsanity.com/paper/2401.10267/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 38 references that are in the map.
- First posted on arXiv 4 Jan 2024.

## Builds on (most cited first, 11 of 11)

- [YOLOv4: Optimal Speed and Accuracy of Object Detection](https://mlsanity.com/paper/2004.10934/) (2020)
- [NVAE: A Deep Hierarchical Variational Autoencoder](https://mlsanity.com/paper/2007.03898/) (2020)
- [Edge Intelligence: Paving the Last Mile of Artificial Intelligence with Edge Computing](https://mlsanity.com/paper/1905.10083/) (2019)
- [Constrained Few-shot Class-incremental Learning](https://mlsanity.com/paper/2203.16588/) (2022)
- [Brain-inspired computing: We need a master plan](https://mlsanity.com/paper/2104.14517/) (2021)
- [GraphHD: Efficient graph classification using hyperdimensional computing](https://mlsanity.com/paper/2205.07826/) (2022)
- [Rethinking of Radar's Role: A Camera-Radar Dataset and Systematic Annotator via Coordinate Alignment](https://mlsanity.com/paper/2105.05207/) (2021)
- [Operating critical machine learning models in resource constrained regimes](https://mlsanity.com/paper/2303.10181/) (2023)
- [PISA: A Binary-Weight Processing-In-Sensor Accelerator for Edge Image Processing](https://mlsanity.com/paper/2202.09035/) (2022)
- [CamJ: Enabling System-Level Energy Modeling and Architectural Exploration for In-Sensor Visual Computing](https://mlsanity.com/paper/2304.03320/) (2023)
- [Neurosciences and 6G: Lessons from and Needs of Communicative Brains](https://mlsanity.com/paper/2004.01834/) (2020)

## Built on by (most cited first, 7 of 7)

- [TaskCLIP: Extend Large Vision-Language Model for Task Oriented Object Detection](https://mlsanity.com/paper/2403.08108/) (2024)
- [Recoverable Anonymization for Pose Estimation: A Privacy-Enhancing Approach](https://mlsanity.com/paper/2409.02715/) (2024)
- [DecoHD: Decomposed Hyperdimensional Classification under Extreme Memory Budgets](https://mlsanity.com/paper/2511.03911/) (2025)
- [LogHD: Robust Compression of Hyperdimensional Classifiers via Logarithmic Class-Axis Reduction](https://mlsanity.com/paper/2511.03938/) (2025)
- [Continuous GNN-based Anomaly Detection on Edge using Efficient Adaptive Knowledge Graph Learning](https://mlsanity.com/paper/2411.09072/) (2024)
- [FusionSense: Tri-Stage Near-Sensor Learning for Runtime-Adaptive Multimodal Edge Intelligence](https://mlsanity.com/paper/2605.22868/) (2026)
- [Vector Symbolic Policy Gradient](https://mlsanity.com/paper/2608.18404/) (2026)

## 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.