LAUSR

Abstract Integration of all smart systems (such as smart home, smart parking, etc.) and the IoT devices (such as sensors, actuators, and smartphones) in the city can play a vital role to develop the urban services by building their city digital and smarter. However, interconnection of lots of IoT objects to collect urban data over the Internet to launch a smart digital city, effects vast volume of data generation, termed as Big Data. Thus, it is a challenging task to integrate IoT devices and smart systems in order to harvest and process such big amount of real-time city data in an effective manner aimed at creating a Smart Digital City. Therefore, in this paper, we have established an IoT-based Smart City by using Big Data analytics while harvesting real-time data from the city. We used sensors’ deployment including sensors at smart home, smart parking, vehicular networking, surveillance, weather and water monitoring system, etc., for real time data collection. The complete system is described by its proposed architecture and implementation prototype using Hadoop ecosystem in a real environment. In addition, the Smart Digital City services are extended by developing the intelligent Smart Transportation System by means of big graph processing to facilitate citizens while providing real-time traffic information and alerts. The proposed system consists of number of stages including data generation and collection, aggregation, filtration, classification, preprocessing, computing, and decision making. The efficiency of the system is extended by applying Big Data processing using Apache Spark over Hadoop. Whereas, the big city graph processing is achieved by using Giraph over Hadoop. The system is practically implemented by taken existing smart systems and IoT devices as city data sources to develop the Smart Digital City. The proposed system is evaluated with respect to efficiency in terms of scalability and real-time data processing.