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Intelligent Monitoring System with Privacy Preservation Based on Edge AI.

Soohee Kim1, Joungmin Park1, Youngwoo Jeong1

  • 1Department of Electronic Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea.

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Summary

This study introduces an intelligent edge AI monitoring system for elderly individuals living alone, enhancing privacy and cost-efficiency. The system achieves high accuracy, addressing concerns with traditional server-based monitoring.

Keywords:
SoCedge AIintelligent monitoring systemprivacy preservation

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Electrical Engineering

Background:

  • Increasing numbers of elderly individuals living alone necessitate advanced monitoring solutions.
  • Existing sensor-based monitoring systems often face challenges with cost-effective maintenance and data privacy.
  • Server-dependent architectures pose risks of personal information leakage and communication bottlenecks.

Purpose of the Study:

  • To propose an intelligent monitoring system utilizing edge Artificial Intelligence (AI) for enhanced privacy and cost-efficiency.
  • To develop a system that mitigates privacy risks by processing data locally on an edge AI module.
  • To improve the efficiency of data traffic management through edge computing.

Main Methods:

  • An edge AI module was designed using Verilog Hardware Description Language (HDL).
  • The edge AI module was implemented on a Field-Programmable Gate Array (FPGA).
  • The system architecture was designed to block direct communication between camera modules and servers, processing data at the edge.

Main Results:

  • The proposed edge AI system achieved an accuracy of 95.34% over 6144 frames.
  • Synthesis results using 180 nm CMOS technology showed a gate count of 1,516,000 (1516 K) and power consumption of 344.44 mW.
  • The edge AI approach demonstrated cost competitiveness and enhanced security by localizing data processing.

Conclusions:

  • The developed edge AI monitoring system offers a secure, private, and cost-effective solution for elderly individuals living alone.
  • Edge computing significantly improves data traffic efficiency and reduces reliance on centralized servers.
  • The FPGA implementation demonstrates the feasibility and performance of the proposed privacy-preserving monitoring system.