Deep learning for smart home security systems: CNN-based home security
by M. Balasubramanian; Kiran Shrimant Kakade; Sulakshana B. Mane; Sujatha Jamuna Anand
International Journal of Electronic Security and Digital Forensics (IJESDF), Vol. 16, No. 4, 2024

Abstract: A smart home enables new modes of connection and the consumption of various services. Additionally, AI and deep learning have aided in the enhancement of many services and jobs by making them more automated. In this study, we used IoT and deep learning to create a safe and efficient home automation system. Using deep learning approach, the user is able to operate appliances such as fans, televisions, bulbs, and other electronic or electrical equipment by either speaking commands into their mobile device or using an application that is pre-installed on their mobile device. The results of the trials that were carried out demonstrate that the suggested deep learning model is more accurate than the KNN method, and that the RL system improves the user's quality of experience by as much as 3.8 points on a scale of 10.

Online publication date: Fri, 05-Jul-2024

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Electronic Security and Digital Forensics (IJESDF):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com