Decision Tree-Based Electricity Optimization Using Intelligent Appliance Controller

With the growth of infrastructural development, the demand for electricity has exponentially increased. An average human consumes about 14,000 to 7000 KWH of electrical energy alone per. To meet this demand, 75% electricity is generated from conventional resources like thermal, nuclear and hydro, and 15% electricity is generated from renewable resources like wind, solar and biomass. The ¾th portion of electricity is generated from non-renewable resources which cannot be produced. Hence it needs to be used with utmost care. Unavailability of electricity not only stops the digital cycle of the world but also disturbs individual life. The first and the biggest impact of unavailability of electricity is on the health sector. One example of such an impact is the outage in Mumbai on October 12, 2020 where the major grid failure caused nearly a full day outage in some regions of Mumbai. Hospitals in Mumbai struggled to keep essential patient services running to provide necessary treatments causing loss of lives. Though there are many reasons like standby consumption, poor insulation, poor infrastructure, etc., responsible for electricity wastage, one of the smallest and most ignored but important reason is human tendency of inefficient use of electricity. Hence, we propose an intelligent electricity optimization solution which takes advantage of already installed CCTV systems to detect the number of people present in an area with accuracy of 98.33% and thus accordingly takes immediate and accurate decisions to optimize the usage of required appliances.