Intelligent Aerial-Ground Surveillance and Epidemic Prevention with Discriminative Public and Private Services
Hyunbum Kim, Jalel Ben‐Othman, Kwang‐il Hwang, B.J. Choi
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.