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International Journal of Advanced Engineering Application

ISSN: 3048-6807

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Distributed Edge Computing Architecture for Fall Detection in Senior Care Facilities

Author(s):Ananya M., Karthik S., Meherosh F.

Affiliation: Department of Computer Science, Regional Institute of Technology, Coimbatore, Tamil Nadu Centre for Applied Systems, Metropolitan Technical University, Bhopal, Madhya Pradesh

Page No: 1-5

Volume issue & Publishing Year: Volume 3, Issue 3, 2026-03-01

Journal: International Journal of Advanced Engineering Application (IJAEA)

ISSN NO: 3048-6807

DOI:

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Abstract:
The integration of high-reliability monitoring systems in senior care facilities has become a critical engineering priority. This paper explores the development of an edge-cloud orchestrated framework designed for real-time fall detection. Traditional centralized systems often face latency bottlenecks and bandwidth constraints that can delay emergency responses during critical incidents. Our research proposes a decentralized architecture where initial data processing occurs at the "edge"—utilizing on-site gateways and wearable sensors—to enable near-instantaneous anomaly detection. The framework was implemented across multiple testbed facilities using a combination of tri-axial accelerometers and infrared occupancy sensors. This study evaluates the trade-off between local processing power and central data storage, focusing on reducing false positives while optimizing the battery life of low-power devices. Findings demonstrate that edge-based inference reduces response latency significantly compared to conventional architectures. This work provides a technical blueprint for smart healthcare infrastructure that prioritizes localized intelligence and resident privacy.

Keywords: Edge Computing, Internet of Medical Things (IoMT), Gerontechnology, Fall Detection, Low-Latency Networking, Smart Sensors, Cloud Orchestration, Wearable Devices, Predictive Analytics, Healthcare Infrastructure.

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