Machine Learning Technique for Smart City Development-Focus on Smart Mobility

  • Md FasihuddinEmail author
  • Mohd Fazal Ul Haque Syed
Conference paper
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 3)


This work summarizes the current state of understanding the smart city concept and how machine learning can be applied for the development of the Smart City. The main innovations coming from the Smart City concept is the rise of a user-centric approach considering urban issues from the perspective of the citizen’s needs. Smart City concept has been defined to get an understanding on how it can contribute towards urban development. In the approach to the Smart Cities Mission, the objective is to promote cities that provide core infrastructure and give a decent quality of life to its citizens, a clean and sustainable environment and application of Smart Solutions. This paper presents a theoretical perspective on the smart cities focused on data mining using machine learning technique. In a smart city, a lot of data need to be automatically processed and analyzed. A review has been done on the machine learning algorithms applied on smart city. A smart city is to improve the quality and efficiency of urban services by using digital technologies or information and communication technologies. Data analytics plays an important role in smart cities. An insight has been brought into machine learning integrated with data mining applied to smart mobility and future focus to be on smart energy.


Smart city Machine learning Data mining Smart mobility K-means clustering 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Computer Science Engineering DepartmentMaulana Azad National Urdu UniversityNagarbhavi, BangaloreIndia
  2. 2.Computer Science Engineering DepartmentMaulana Azad National Urdu UniversityGachibowli, HyderabadIndia

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