Total views : 352

Smart Energy Management and Scheduling using Internet of Things


  • School of Computing, SASTRA University, Thanjavur – 613401, Tamil Nadu, India


Objectives: Increasing energy usage will affect the sustainability due to the presence of elevated level of greenhouse gases. The primary aim of energy management is to ensure optimum energy utilization, thereby minimizing energy costs and extenuating environmental effects. Real time energy monitoring and management assist consumers to overcome the burden of load shedding, energy surcharges and dependence on secondary energy sources like generators and inverters in residential buildings. Methods: A low cost, advanced embedded hardware with ethernet communication, i.e Arduino Mega 2560 and smartphone with cloud computing technologies are used to develop a prototype model. It will provide optimal solutions to the consumer for real time monitoring of energy for self regulation as well as to choose the energy provider for competitive energy price. A joint scheduling of electric supply and demand of consumer through Internet of Things (IoT) based smart energy management system on interruptible and shiftable load is proposed. Findings: The energy provider needs to regulate the energy usage during peak hours to manage massive energy demand of individual customer or on the whole. This also can be used to prevent the problem of overload on residential generator power supply system and subsequent damage to it. Application/Improvement: Low cost, scalable proposed system regulates the peak load by means of load sharing at lower production cost with maximum service utilization is achieved.


Automated Energy Management, Energy management system, Energy Monitoring, Internet of Things.

Full Text:

 |  (PDF views: 318)


  • Raju L, Milton R, Amalraj Morais A. Autonomous Energy Management of a Micro-Grid using Multi Agent System. Indian Journal of Science and Technology. 2016; 9(13):1–6.
  • Rengasamy R, Pradesh A, Kumaravel R. Abstracts Gesis 2010-Chennai A novel approach for energy generation from wind power. 2010; 1–164.
  • Keshtkar A, Arzanpour S, Keshtkar F, Ahmadi P. Smart residential load reduction via fuzzy logic, wireless sensors, and smart grid incentives. Energy and Buildings. 2015; 104:165–80.
  • Porcarelli D, Brunelli D, Benini L. Clamp-and-Forget: A self-sustainable non-invasive wireless sensor node for smart metering applications. Microelectronics Journal. 2014; 45(12):1671–78.
  • Shrouf F, Miragliotta G. Energy management based on Internet of Things: practices and framework for adoption in production management. Journal of Cleaner Production. 2015; 100:235–46.
  • Gubbi J, Buyya R, Marusic S, Palaniswami M. Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems. 2013; 29(7):1645–60.
  • Hong S, Kim D, Ha M, Bae S, Park S, Jung W. SNAIL: an IP-based wireless sensor network approach to the internet of things. IEEE Wireless Communication. 2010; 17(6):34–42.
  • Weinert N, Chiotellis S, Seliger G. Methodology for planning and operating energy-efficient production systems. CIRP Annals - Manufacturing Technology. 2011; 60(1):41–4.
  • Collotta M, Pau G. Bluetooth for Internet of Things: A fuzzy approach to improve power management in smart homes. Computers and Electrical Engineering. 2015; 44:137–52.
  • Lee S, Kwon B, Lee S. Joint Energy Management System of Electric Supply and Demand in Houses and Buildings. IEEE Transaction on Power System. 2014; 29(6):2804–12.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.