Gestures Controlled Home Automation using Deep Learning: A Review

Amruta S. Bankar1; Avinash D. Harale; Kailash J. Karande

doi:10.14741/ijcet/v.11.6.4

Amruta S. Bankar1 Student, Department of Electronics and Telecommunication Engineering, SKN Sinhgad College of Engineering, Korti, Pandharpur, Taluka-Pandharpur, District-Solapur, Pin-413 304, Maharastra, India.
Avinash D. Harale Department of Electronics and Telecommunication Engineering, SKN Sinhgad College of Engineering, Korti, Pandharpur, Taluka-Pandharpur, District-Solapur, Pin-413 304, Maharastra, India.
Kailash J. Karande Department of Electronics and Telecommunication Engineering, SKN Sinhgad College of Engineering, Korti, Pandharpur, Taluka-Pandharpur, District-Solapur, Pin-413 304, Maharastra, India.

DOI: https://doi.org/10.14741/ijcet/v.11.6.4

Keywords: Gesture Recognition, Image Classification, Deep Learning, Home Appliances.

Abstract

This paper presents the review of the studies carried out on the application using computer vision for hand gesture recognition. Hand gestures can be used to operate the electronic devices. Therefore, it is very much essential to review on the scientific studies whose aim is to develop a technique to achieve more precise and faster sign language recognition system for plain and cluttered backgrounds with different humans to help speech and hearing impaired in their life, robot control, human–computer interaction (HCI), home automation and medical fields. The objective of this paper is to give an overall literature review of the work done related to identify the current technology and methodology used in hand gesture recognition as well as home automation system. This paper mainly describes various images or vision based sign language recognition system comprising pre-processing, feature extraction and classification. The system conversion of sign language to text. The recognized text can be sent to the control model. The gesture based automation communicates directly with control model to control home appliances.