Abstract
The rapid growth in the population density in urban cities demands additional, smart, and fast provision of services and infrastructure. Countries and metropolitan authorities are really interested to provide smart and intelligent environment and real-time facilities to their citizens. Citizens also want to be facilitated by the provision of real-time information regarding anything like traffic, flood, security, pollution, etc. To meet the requirements of both the metropolitan authorities and the citizens, we proposed the use of Internet of Things (IoT)-based smart systems for smart city establishment and the urban planning as well. In this chapter, we propose an IoT-based system that uses the massive volume of data, termed as big data, generated by the smart systems to establish smart city and to do urban planning for the bright future. The data are generated from the smart home sensors, vehicular networks, weather and water sensors, smart parking systems, surveillance objects, etc.A four-tier architecture is proposed which include (1) bottom tier-1: responsible for the management and deployment of IoT sources, data generations, and collections; (2) intermediate tier-1: handles all type of communication between sensors, relays, base stations, the Internet, etc.; (3) intermediate tier-2: levers the data management and processing using Hadoop framework; and (4) top tier: is responsible for application and usage of the data analysis, results generation, and smart decisions. The system implementation consists of various phases including data generation and collecting, aggregating, filtration, classification, preprocessing, computing, and decision making. The proposed system implementation is done in Hadoop ecosystem with spark, voltDB, storm or S4 for real-time processing to generate results in order to establish the smart city. For urban planning or city future development, the offline historical data are used using MapReduce programming in Hadoop environment. IoT-based datasets generated by smart homes, smart parking, weather, pollution, and vehicle datasets are used for analysis and evaluation. The system is evaluated with respect to efficiency in terms of throughput and processing time.
| Original language | English |
|---|---|
| Title of host publication | Managing the Internet of Things |
| Subtitle of host publication | Architectures, theories and applications |
| Publisher | Institution of Engineering and Technology |
| Pages | 155-183 |
| Number of pages | 29 |
| ISBN (Print) | 9781785610288 |
| State | Published - 25 Nov 2016 |
