Lightweight, privacy-compliant motion detection system for constrained devices

Shaju, Alexis Tom, Shifa, Amna, & Asghar, Mamoona Naveed. (2025). Lightweight, privacy-compliant motion detection system for constrained devices. Paper presented at the 36th Irish Signals and Systems Conference (ISSC), Atlantic Technological University (ATU), Galway, Ireland 9–10 June.

Abstract

In a rapidly evolving digital landscape, embedded vision systems are becoming increasingly prominent in applications such as home security, surveillance, and autonomous monitoring. However, existing solutions often lack computational efficiency for embedded hardware or fail to meet key ethical and regulatory requirements. This paper presents a lightweight, privacy-compliant motion detection system with integrated facial recognition deployed on the Qualcomm RB5 platform. The system enforces data minimisation by recording video only when motion is detected, reducing unnecessary data collection. To protect privacy, facial anonymisation is applied using Gaussian blurring, and Role-Based Access Control (RBAC) restricts access to sensitive data. Experimental evaluations demonstrate an approximate 80% reduction in storage requirements compared to continuous recording while maintaining acceptable CPU and memory usage. The system also achieves reliable detection accuracy while aligning with data protection principles, making it suitable for privacy-sensitive, resource-constrained devices.

Funder

European Union’s Horizon 2020

Publisher

Institute of Electrical and Electronics Engineers

Rights

CC BY

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