This paper is published in Volume-7, Issue-4, 2021
Area
Mechanical Engineering
Author
Shravan Aruljothi, Sharad Dewanand Parate, Harshit S., Nehal Dinesh Andani
Org/Univ
New Horizon College of Engineering, Bengaluru, Karnataka, India
Pub. Date
12 July, 2021
Paper ID
V7I4-1269
Publisher
Keywords
IoT, Deep Learning, Raspberry Pi, BOLT, OpenCV, Haar Cascade Classifier, Viola-Jones Algorithm, LBPH Algorithm

Citationsacebook

IEEE
Shravan Aruljothi, Sharad Dewanand Parate, Harshit S., Nehal Dinesh Andani. Development of a home security Robot using Deep Learning and IoT, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Shravan Aruljothi, Sharad Dewanand Parate, Harshit S., Nehal Dinesh Andani (2021). Development of a home security Robot using Deep Learning and IoT. International Journal of Advance Research, Ideas and Innovations in Technology, 7(4) www.IJARIIT.com.

MLA
Shravan Aruljothi, Sharad Dewanand Parate, Harshit S., Nehal Dinesh Andani. "Development of a home security Robot using Deep Learning and IoT." International Journal of Advance Research, Ideas and Innovations in Technology 7.4 (2021). www.IJARIIT.com.

Abstract

The major problem in every urban city is the lack of security to residential areas. The number of thefts, electricity and food wastage at homes in urban areas increase every year due to human error. As per the National Crime Records Bureau (NCRB), 2,44,119 cases of robbery, theft, and burglary took place in residential premises in 2019. Also, electricity consumption in Indian homes has tripled since 2010. In 2019, an urban Indian household consumed about 90 units (kWh) of electricity as a monthly average which is one-third of the monthly world average. To solve these issues, we have proposed an idea of a “Home Security Robot” for a smart city using AI. The Home Security Robot will help in eliminating the reliance on security guards and will effectively monitor everything in the house (if there are any gas leakage, fridge malfunctions, unnecessary electricity wastage, indoor air quality and any unknown movements inside the house). If the owner is under attack, he/she can shout out “HELP” or “SAVE ME "so that the robot can take in the voice command to automatically call the police. The navigation part is done by Arduino and Bluetooth RC Controller App. There are 2 parts (Face Detection & Recognition using Raspberry Pi and IoT system using BOLT module with sensors). The first part has three python programs used for facial detection and recognition using OpenCV with Haar Cascade Classifier and LBPH algorithm. The first program (Face Dataset) is used for collecting images of known users and storing it in a database using Haar Cascade Classifier. The second program (Face Training) is used to train the stored images using LBPH algorithm so the model can distinguish between the users whose faces are stored in database and then these trained images are stored in the trainer.yml file. The third program (Face Recognition) is used to read the trained images stored in the trainer.yml file and then uses Haar Cascade Classifier to recognize the detected face and identifies whether the face belongs to a user or an intruder. The IoT system with the help of BOLT module helps in checking the temperature in the room and checking if any unnecessary lights are on in the room. If the room temperature is outside the safe range specified or if any lights are on, owner will get an alert via SMS.