A Systematic Review of Waste Management Solutions Using Machine Learning, Internet of Things and Blockchain Technologies: State-of-Art, Methodologies, and Challenges

Urbanization and rising populations are contributing significantly to the problem of garbage generation in cities. For a quite long time, big cities all around the world have been particularly concerned about rising waste. For countries with inadequate waste management procedures and faster-rising garbage volumes, this is a severe problem. Many of the waste management systems in use in cities today do not come with features like operational transparency, traceability, audit, security, and trusted data provenance. The way solid waste is managed has evolved as a result of the Internet of Things, Global Positioning System, and cloud computing methods. The research community has also developed numerous waste management methods based on the Internet of Things and blockchain, and machine learning. Using the method of a systematic literature review, this research examines several waste management approaches. Based on the considered 178 research papers, this paper provides the opportunities brought about by the Internet of Things, machine learning, Global Positioning System, and Blockchain in various waste management techniques, their application scenarios, real-time tracing and tracking of waste, reliable channelization and compliance with waste treatment, efficient waste resource management, protection of waste management documentation, and fleet management. Based on the conducted review, this paper presents open challenges associated with waste management techniques that act as future research directions. Waste bin placement and its security, internet connectivity with waste management components, transportation of waste, and waste disposal techniques are the main categories of challenges associated with waste management. This paper also provides a comparison of the presented review with other published review papers.