Machine Learning Approaches for Sustainable Cities Using Internet of Things

Abstract

As these tech-based cities continue to emerge, so do the experts dive deeper into the research on the various Internet of Things methods, and the most plausible machine learning techniques. What is Machine Learning? What role does it play in IoT-based platforms? How does it contribute to the continuous advancement of smart cities? What is IoT? How has it changed the lives of urban households residing in smart cities? How does IoT interact with machine learning to ensure more efficient cities? This research paper delves into the various existing literature in a bid to respond to these questions as effectively as possible. It looks the research that have handled issues of IoT and machine learning. The search criteria are set out in the methodology section that has inclusion and exclusion criteria for the articles considered in this paper. There is systematic evidence showing that IOT and machine learning can be used for the management of the future cities. The results suggest that IoT and machine learning are at the core of the development, maintenance, and sustainability of smart cities. Further studies are required on how IOT can be securely used by analysis some of the security vulnerabilities faced by these systems.