Abstract
Increasing traffic, population, and public safety are major issues of cities. Many cities face social and environmental sustainability challenges such as pollution and environmental deterioration. One challenging application area of big data analytics and machine learning that has huge potential to enhance our lives is smart cities. Intelligent services connected with smart devices and sensors deployed all around the area can provide efficient and sustainable cities. This idea is challenged with the fact that the amount of data that needs to be processed has increased to a level that new algorithms and techniques are required. Besides, constantly changing nature of cities requires adaptable architectures and learning systems. In this chapter, we present some open source tools for handling huge amounts of data that can be used to create solutions for smart cities. Also, we discussed some open research issues and enabling technologies such as energy consumption models, heterogeneous networks, and security.
Source : https://link.springer.com/chapter/10.1007%2F978-3-030-14718-1_8
