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

Background

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.