The fast growth in the population density in urban areas demands more facilities and resources. To meet the needs of city development, the use of Internet of Things (IoT) devices and the smart systems is the very quick and valuable source. However, thousands of IoT devices are interconnecting and communicating with each other over the Internet results in generating a huge amount of data, termed as Big Data. To integrate IoT services and processing Big Data in an efficient way aimed at smart city is a challenging task. Therefore, in this paper, we proposed a system for smart city development based on IoT using Big Data Analytics. We use sensors deployment including smart home sensors, vehicular networking, weather and water sensors, smart parking sensor, and surveillance objects, etc. initially a four-tier architecture is proposed, which includes 1) Bottom Tier: which is responsible for IoT sources, data generations, and collections 2) Intermediate Tier-1: That is responsible for all type of communication between sensors, relays, base stations, the internet, etc. 3) Intermediate Tier 2: it is responsible for data management and processing using Hadoop framework, and 4) Top tier: is responsible for application and usage of the data analysis and results generated. The collected data from all smart system is processed at real-time to achieve smart cities using Hadoop with Spark, VoltDB, Storm or S4. We use existing datasets by various researchers including smart homes, smart parking weather, pollution, and vehicle for analysis and testing. All the datasets are replayed to test the real-time efficiency of the system. Finally, we evaluated the system by efficiency in term of throughput and processing
