The database containing catalogs of human activity classification, thermal-human behavioral maps, gesture datum, etc., that will be used by the algorithms to classify and predict heinous activities.
Published in Chapter:
Urban Intelligence and IoT-UAV Applications in Smart Cities: Unmanned Aerial Vehicle-Based City Management, Human Activity Recognition, and Monitoring for Health
Prince R. (Quilon, India), Navneet Munoth (Maulana Azad National Institute of Technology, Bhopal, India), and Neha Sharma (Mindtree, India)
Copyright: © 2022
|Pages: 33
DOI: 10.4018/978-1-7998-8763-8.ch006
Abstract
The objective of this chapter is to propose a model of an automated city crime-health management that can be implemented in future smart cities of developing countries. The chapter discusses how a suitable amalgamation of existing technologies such as IoT, artificial intelligence, and machine learning can output an efficient system of unmanned city management systems, thereby facilitating indirect engendering of innovative scopes for technology workers and researchers and alleviating the living standards within the city fabrics, catalyzing infrastructure development. In this chapter, the authors have structured an ideal UAV-matrix layout for city fabric surveillance built over the scopes of artificial intelligence. Succinctly, this chapter provides a platform that would galvanize the possibilities and that could be reimagined to structure a more resourceful working model of new emerging smart cities and enlighten the settings of existing ones.