Energy aware smart city management system using data analytics and Internet of Things

Abstract The rise of Internet of Things (IoT) concept founded the realization of a smart city. Energy management has lately turn out to be a vital concern for the services of a smart city as IoT devices consume massive energy constantly. This concern needs to be addressed to devise a practical method. Efficient energy utilization aims to promise smart city sustainability. Moreover, IoT devices produce enormous data that is required to be processed efficiently. In this article, a framework is proposed that assures the energy efficiency of IoT devices along with data analysis for cities. This article proposes a general design for smart city energy management that assures the energy efficiency of IoT devices along with data analysis. The proposed model includes three different components that are energy management, data processing, and service management. The energy management component is dependent on infrastructure optimization. The energy-efficient clustering, peak load shaving, optimized scheduling, and load balancing algorithms are integrated to achieve efficient energy management. The data processing is performed using distributed framework. The service management is performed using rules and thresholds. The experiments are performed using authentic datasets and the result highlights the efficiency of the proposed model.