# A Low-Resolution Infrared Array for Unobtrusive Human Activity Recognition That Preserves Privacy

## TL;DR

This paper introduces a privacy-preserving system for real-time human activity recognition using a low-resolution infrared array.

## Contribution

The novel system uses thermal pixels and mathematical measures without machine learning to recognize human states unobtrusively.

## Key findings

- The system efficiently recognizes multiple human states in real-time using thermal data.
- It preserves privacy by avoiding traditional camera-based image processing.
- The method's accuracy is validated using traditional machine learning approaches.

## Abstract

This research uses a low-resolution infrared array sensor to address real-time human activity recognition while prioritizing the preservation of privacy. The proposed system captures thermal pixels that are represented as a human silhouette. With camera and image processing, it is easy to detect human activity, but that reduces privacy. This work proposes a novel human activity recognition system that uses interpolation and mathematical measures that are unobtrusive and do not involve machine learning. The proposed method directly and efficiently recognizes multiple human states in a real-time environment. This work also demonstrates the accuracy of the outcomes for various scenarios using traditional ML approaches. This low-resolution IR array sensor is effective and would be useful for activity recognition in homes and healthcare centers.