Intelligent Aerial-Ground Surveillance and Epidemic Prevention with Discriminative Public and Private Services
Document Type
Article
Source of Publication
IEEE Network
Publication Date
1-1-2022
Abstract
Since complete surveillance is essential to provide safe daily life to citizen in smart cities, the issue of how to achieve secure surveillance has been driven by various research communities. Also, due to recent epidemic spread such as COVID-19, it is obvious that we should focus on how to manage a cooperative framework for possible future pandemic fights and allied medical services continuously. To support those purposes, it is anticipated that we can utilize AI-assisted communications and technologies using a variety of devices and equipment, including UAVs, mobile robots, and smart devices on the aerial and ground sides. In this article, an aerial-ground cooperative infrastructure is designed to study surveillance and epidemic prevention with managing energy recharge and AI-supported communications through collected or pre-knowledge information for public and private areas. Also, in the proposed architecture, we specify system settings, promising scenarios, and strategies in order to satisfy several objectives and tasks. Then possible research challenges and issues are addressed for successful realization and management of intelligent surveillance and efficient epidemic prevention.
DOI Link
ISSN
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
36
Issue
3
First Page
40
Last Page
46
Disciplines
Computer Sciences
Keywords
COVID-19, Smart cities, Pandemics, Surveillance, Medical services, Mobile robots, Autonomous aerial vehicles
Scopus ID
Recommended Citation
Kim, Hyunbum; Ben-Othman, Jalel; Hwang, Kwang Il; and Choi, Byoungjo, "Intelligent Aerial-Ground Surveillance and Epidemic Prevention with Discriminative Public and Private Services" (2022). All Works. 5247.
https://zuscholars.zu.ac.ae/works/5247
Indexed in Scopus
yes
Open Access
no