A Collaborative Approach of IoT, Big Data, and Smart City

A Collaborative Approach of IoT, Big Data, and Smart City

K. Jayashree (Rajalakshmi Engineering College, India), R. Abirami (Rajalakshmi Engineering College, India) and R. Babu (Rajalakshmi Engineering College, India)
Copyright: © 2019 |Pages: 13
DOI: 10.4018/978-1-5225-6207-8.ch002
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During the last two decades, a number of new nations emerged and played their intense role in changing human lifestyle. The growing demand for smart city and big data stimulates innovation, and the development of new smart applications is becoming important. Internet of things comprises billions of devices, people, and services, and entitles each to connect through sensor devices. The economic development of a city leads to better life quality and improved citizen services. Thus, this chapter discusses the background of big data, IoT, and smart city. It also discusses the collaborative approach of all the above. The various related work and future research direction for implementing smart city with the concept of big data and IoT would be addressed in this chapter.
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IoT has become popular in connecting the devices with devices and with people every-second and every day with the help of low-cost wireless sensors like radio-frequency identification sensors and technologies like web technologies. These sensors and approaches are useful in collecting and analyzing the data all over the world. As the result the enormous volume of data will be collected from multiple sources. Big data handles and organizes these huge volumes, multiple forms, and rapidly changing data through various statistical and machine learning approaches (Kune et al., 2016).

To improve the economic growth and quality of life of citizens government of India has started a new initiative called Smart cities mission. In smart cities, data are generated in real time and in large volume and are collected from various sensors, devices, audio, video, networks, log files, transactions, web and through social media. To handle or to process enormous data the following terminologies are to be known: Data integration, Aggregation, Validation, Cleansing, Data anonymization and visualization, encryption, shuffling, substitution, masking and data variance.

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