Research

Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST) algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism.

Published in Sensors (2018)

With the evolution of IoT, many attempts were made to realize the notion of smart cities. However, demands for processing enormous amount of data and platform incompatibilities of connected smart things hindered the actual implementation of smart cities. Keeping it in view, we proposed a Big Data analytics embedded smart city architecture, which is further integrated with the web via a smart gateway. Integration with the web provides a universal communication platform to overcome the platform incompatibilities of smart things. We introduced Big Data analytics to enhance data processing speed. Further, we evaluated authentic datasets to determine the threshold values for intelligent decision-making and to present the performance improvement gained in data processing. Finally, we presented a representational state transfer (RESTful) web of things (WoT) integrated smart building architecture (smart home) to reveal the performance improvements of the proposed smart city architecture in terms of network performance and energy management of smart buildings.

Published in Future Generation Computer Systems (2017)

As the smart home networks continue to grow in size and complexity, it is essential to address a handful among the myriads of challenges related to data loss due to the interference and efficient energy management. In this paper, we propose a smart home control system using a coordinator-based ZigBee networking. The working of the proposed system is three fold: 1) smart interference control system controls the interference caused due to the co-existence of IEEE 802.11x-based wireless local area networks and wireless sensor networks; 2) smart energy control system is developed to integrate sunlight with light source and optimizes the energy consumption of the household appliances by controlling the unnecessary energy demands; and 3) smart management control system to efficiently control the operating time of the electronic appliances.

Published in IEEE Access (2016)