Abstract
Advances in Artificial intelligence (AI) and embedded systems have resulted on a recent increase in use of image processing applications for smart cities’ safety. This enables a cost-adequate scale of automated video surveillance, increasing the data available and releasing human intervention. At the same time, although deep learning is a very intensive task in terms of computing resources, hardware and software improvements have emerged, allowing embedded systems to implement sophisticated machine learning algorithms at the edge. Additionally, new lightweight open-source middleware for constrained resource devices, such as EdgeX Foundry, have appeared to facilitate the collection and processing of data at sensor level, with communication capabilities to exchange data with a cloud enterprise application. The objective of this work is to show and describe the development of two Edge Smart Camera Systems for safety of Smart cities within S4AllCities H2020 project. Hence, the work presents hardware and software modules developed within the project, including a custom hardware platform specifically developed for the deployment of deep learning models based on the I.MX8 Plus from NXP, which considerably reduces processing and inference times; a custom Video Analytics Edge Computing (VAEC) system deployed on a commercial NVIDIA Jetson TX2 platform, which provides high level results on person detection processes; and an edge computing framework for the management of those two edge devices, namely Distributed Edge Computing framework, DECIoT. To verify the utility and functionality of the systems, extended experiments were performed. The results highlight their potential to provide enhanced situational awareness and demonstrate the suitability for edge machine vision applications for safety in smart cities.
Funder
European Union’s Horizon 2020 research and innovation program
Subject
Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging
Reference111 articles.
1. Security, Privacy and Risks Within Smart Cities: Literature Review and Development of a Smart City Interaction Framework;Ismagilova;Inf. Syst. Front.,2020
2. (2022, July 18). Edge Computing & Security Platform|NXP Semiconductors. Available online: https://www.nxp.com/applications/enabling-technologies/edge-computing:EDGE-COMPUTING.
3. What the Fog? Edge Computing Revisited: Promises, Applications and Future Challenges;Gedeon;IEEE Access,2019
4. Mobile edge computing, fog et al.: A survey and analysis of security threats and challenges;Roman;Future Gener. Comput. Syst.,2018
5. Stojmenovic, I., and Wen, S. (2014, January 7–10). The Fog computing paradigm: Scenarios and security issues. Proceedings of the 2014 Federated Conference on Computer Science and Information Systems, Warsaw, Poland.
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