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Govt. of India Trust : E/11049/Rajkot
Income tax of India 80G : AADTK8161HF20221
Income tax of India 12A : AADTK8161HE20217


Volume 1 – Issue 2 – 2020

Automatic Power Supply Control Using Raspberry Pi And Image Processing

S.V.Jagadeesh Chandra1*, B.Eswara Rao1, J.Babu2, CH.V.V.Ramana3*

1Department of Electronics and Communication Engineering, Vignan’s Institute of Information Technology, Duvvada, Visakhapatnam – 530049, Andhra Pradesh, (INDIA)
2Department of Electronics and Communication Engineering, Dadi Institute of Engineering and Technology, Anakapalli, Visakhapatnam – 531002, Andhra Pradesh, (INDIA)
3Department of Electrical and Electronics Engineering Science, University of Johannesburg, Auckland Park Campus, Private Bag 524, Johannesburg 2006, (SOUTH AFRICA)

PAGE NO: 101-109


A life which we are living cannot be imagined without electricity and this electricity became the basic fundamental need for every human being. Thus, it became an obligation for every human being to spare power. However, because of the existing busy schedule  now–a–days, frequently a most of us neglected to turn off lights and fans whenever they are not obligatory at specific places, such as auditoriums or rooms in Academic Institutions, offices and even house hold issues, which increases the unnecessary usage of electricity. Repeatedly we used to find lights and fans in an auditorium or a specific room were in working, though the room is empty which increases the exponential wastage of power. This is the major issue in most of the educational institutions and public/private sector offices. In India alone 20% – 30% of power is misspent due to negligence, which is nearly 3 billion units of electricity is being wasted. To overcome this problem, we plan to create a power control device that detects whether the room is empty and thus disables the lights and fans. Our paper demonstrates the detection of human faces as a parameter to decide whether to switch on/off the power supply. This paper mainly deals with the reduction of unwanted power consumption by employing Raspberry Pi and image processing technology.