Big Data and Internet of Things

Abstract

The growing city population demands the delivery of services and infrastructure. The use of Internet of Things (IoT) devices, such as sensors, actuators, and smartphones, etc., and the smart system is the valuable source in order to meet increasing demands. However, thousands of interconnecting IoT devices effects in producing an enormous volume of data, termed as Big Data. To integrate IoT services and processing Big Data in an efficient way to achieve smooth urban planning is a challenging task. In this paper, we propose an IoT-based urban planning system using Big Data Analytics. The system consists of various types of IoT-based smart system including smart home, vehicular networking, weather and water system, smart parking, and surveillance objects, etc. A four-tier architecture is proposed that includes 1) Bottom Tier-1: responsible for IoT data generation, and collections 2) Intermediate Tier-1: responsible for all type of communication between sensors, relays, base stations, 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 proposed system is implemented in Hadoop ecosystem environment with MapReduce programming. The system produced results with higher throughput and low processing time, which proves the scalability and efficiency of the system.