Cargando…

Intelligent Monitoring System with Privacy Preservation Based on Edge AI

Currently, the trend of elderly people living alone is rising due to rapid aging and shifts in family structures. Accordingly, the efficient implementation and management of monitoring systems tailored for elderly people living alone have become paramount. Monitoring systems are generally implemente...

Descripción completa

Detalles Bibliográficos
Autores principales: Kim, Soohee, Park, Joungmin, Jeong, Youngwoo, Lee, Seung Eun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536670/
https://www.ncbi.nlm.nih.gov/pubmed/37763912
http://dx.doi.org/10.3390/mi14091749
_version_ 1785112922139131904
author Kim, Soohee
Park, Joungmin
Jeong, Youngwoo
Lee, Seung Eun
author_facet Kim, Soohee
Park, Joungmin
Jeong, Youngwoo
Lee, Seung Eun
author_sort Kim, Soohee
collection PubMed
description Currently, the trend of elderly people living alone is rising due to rapid aging and shifts in family structures. Accordingly, the efficient implementation and management of monitoring systems tailored for elderly people living alone have become paramount. Monitoring systems are generally implemented based on multiple sensors, and the collected data are processed on a server to provide monitoring services to users. Due to the use of multiple sensors and a reliance on servers, there are limitations to economical maintenance and a risk of highly personal information being leaked. In this paper, we propose an intelligent monitoring system with privacy preservation based on edge AI. The proposed system achieves cost competitiveness and ensures high security by blocking communication between the camera module and the server with an edge AI module. Additionally, applying edge computing technology allows for the efficient processing of data traffic. The edge AI module was designed with Verilog HDL and was implemented on a field-programmable gate array (FPGA). Through experiments conducted on 6144 frames, we achieved 95.34% accuracy. Synthesis results in a 180 nm CMOS technology indicated a gate count of 1516 K and a power consumption of 344.44 mW.
format Online
Article
Text
id pubmed-10536670
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-105366702023-09-29 Intelligent Monitoring System with Privacy Preservation Based on Edge AI Kim, Soohee Park, Joungmin Jeong, Youngwoo Lee, Seung Eun Micromachines (Basel) Article Currently, the trend of elderly people living alone is rising due to rapid aging and shifts in family structures. Accordingly, the efficient implementation and management of monitoring systems tailored for elderly people living alone have become paramount. Monitoring systems are generally implemented based on multiple sensors, and the collected data are processed on a server to provide monitoring services to users. Due to the use of multiple sensors and a reliance on servers, there are limitations to economical maintenance and a risk of highly personal information being leaked. In this paper, we propose an intelligent monitoring system with privacy preservation based on edge AI. The proposed system achieves cost competitiveness and ensures high security by blocking communication between the camera module and the server with an edge AI module. Additionally, applying edge computing technology allows for the efficient processing of data traffic. The edge AI module was designed with Verilog HDL and was implemented on a field-programmable gate array (FPGA). Through experiments conducted on 6144 frames, we achieved 95.34% accuracy. Synthesis results in a 180 nm CMOS technology indicated a gate count of 1516 K and a power consumption of 344.44 mW. MDPI 2023-09-07 /pmc/articles/PMC10536670/ /pubmed/37763912 http://dx.doi.org/10.3390/mi14091749 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kim, Soohee
Park, Joungmin
Jeong, Youngwoo
Lee, Seung Eun
Intelligent Monitoring System with Privacy Preservation Based on Edge AI
title Intelligent Monitoring System with Privacy Preservation Based on Edge AI
title_full Intelligent Monitoring System with Privacy Preservation Based on Edge AI
title_fullStr Intelligent Monitoring System with Privacy Preservation Based on Edge AI
title_full_unstemmed Intelligent Monitoring System with Privacy Preservation Based on Edge AI
title_short Intelligent Monitoring System with Privacy Preservation Based on Edge AI
title_sort intelligent monitoring system with privacy preservation based on edge ai
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536670/
https://www.ncbi.nlm.nih.gov/pubmed/37763912
http://dx.doi.org/10.3390/mi14091749
work_keys_str_mv AT kimsoohee intelligentmonitoringsystemwithprivacypreservationbasedonedgeai
AT parkjoungmin intelligentmonitoringsystemwithprivacypreservationbasedonedgeai
AT jeongyoungwoo intelligentmonitoringsystemwithprivacypreservationbasedonedgeai
AT leeseungeun intelligentmonitoringsystemwithprivacypreservationbasedonedgeai