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Machine Learning and Big Data for Smart Generation

  • Anandakumar Haldorai
  • Arulmurugan Ramu
  • Suriya Murugan
Chapter
Part of the Urban Computing book series (UC)

Abstract

The rapid development and deployment of smart cities result in huge data generation at an increased rate. This huge volume of data is exhausted without extracting potential knowledge due to insufficient algorithms and data analytics mechanisms. This dynamic nature of smart cities demands for advanced machine learning algorithm that supports efficient data processing and adaptive learning from real-time data. Intelligent and adaptive learning structure for smart urban areas is investigated that utilize numerous levels of enormous information created by smart urban areas in order to provide diverse level of knowledge abstractions. This learning framework can manage data as labeled and unlabeled data based on user feedback, thereby utilizing all available data and is capable of managing the scalable requirements of smart generation. The challenges of big data and the importance of machine learning algorithms for intelligent generation are highlighted here. Various challenges and future research scope for consolidating AI and abnormal state knowledge for smart age administrations and also the cognitive nature of smart city are explored in this chapter, thereby improving their performance.

Keywords

Big data Machine learning Deep learning IoT Smart data Smart city 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringSri Eshwar College of EngineeringCoimbatoreIndia
  2. 2.Department of Computer Science and EngineeringPresidency UniversityYelahanka, BengaluruIndia
  3. 3.Department of Computer Science and EngineeringKPR Institute of Engineering and TechnologyCoimbatoreIndia

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