Toward a Deep Smart Waste Management System based on Pattern Recognition and Transfer learning

Abstract

Smart cities essentially combine the use of Information and communications technology (ICT) to provide services for better living conditions inside. The recent developments in the Internet of Things (IoT) opened vast opportunities for researchers and developers to implement various systems and applications in the field of Smart Cities and Intelligent Transportation Systems (ITS). It is a diverse topic of discussion with several application areas such as smart traffic management, smart street lights or gas and water leak detection. Among these applications, Efficient Waste Collection (WC) is considered a fundamental service for helping maintain a healthier environment for the citizens while reducing operating costs. This paper proposes a new architecture for a smart wastes management system based on artificial intelligence techniques and focuses on the combined use of the Internet of Things (IoT) and surveillance systems as an assistive technology for high Quality of Service (QoS) in waste collection. By integrating deep learning techniques in this sector, important cost reductions can be made while maintaining optimal performance.