Abstract

The use of IoT devices like sensors, actuators, smartphones etc. is the very rapid and useful source in order to cope smartly with the public and community growth requirements. Nevertheless, when you connect thousands of IoT devices to create a smart network as you communicate over the Internet, you produce a massive amount of data, known as Big Data. Integrating IoT services to receive city data in real time and then efficiently processing large amounts of data to create a smart city is a challenge. Therefore, in this paper the smart town framework based on IoT using Big Data Analytics was proposed and developed. We use sensors such as smart home sensors , network cars, water and weather sensors, smart parking sensors, tracking objects, etc. The entire design and implementation model is proposed and implemented in a specific world using Hadoop ecosystems. The system is implemented in various steps , starting from data collection , aggregation, filtering, classification, preprocessing, computing and decision-making. Spark over Hadoop achieves reliability in the production of big data. The program is realistic for building smart cities by using intelligent systems as the city data base.

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