ABSTRACT
This chapter discusses the machine learning (ML) techniques used in smart city (SC) and presents the architecture and components of an SC considering different SC use cases. It provides some application of ML in SCs and demonstrates the main design factors to be considered in developing and deploying an ML solution in SC. The chapter describes the commercial products provides Internet of Things (IOT) Platform as a Service in SC and presents the used metrics in the evaluation of ML algorithm. SC applications generally require algorithms with different types of data inputs and outputs that will perform real-time learning on this big data. Adopting ML in military application enhances the processing and utilization of data, which in turn improves the speed of decision-making on the battlefield. Sensing, collecting, merging, transmitting, or even reverse controlling the data in the SC are all possible tasks to be performed by an IoT device/node.
