The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
AI-Driven Computer Vision for Intelligent Home Automation and Surveillance Systems
|
|
Author(s): Edwin Shalom Soji (Bharath Institute of Higher Education and Research, India), Sonia Gnanamalar (Dhaanish Ahmed College of Engineering, India), Nagarajan Arumugam (Dhaanish Ahmed College of Engineering, India), S.Silvia Priscila (Bharath Institute of Higher Education and Research, India), N. Selvam (Dhaanish Ahmed College of Engineering, India)and S. Suman Rajest (Dhaanish Ahmed College of Engineering, India)
Copyright: 2024
Pages: 16
Source title:
Explainable AI Applications for Human Behavior Analysis
Source Author(s)/Editor(s): P. Paramasivan (Dhaanish Ahmed College of Engineering, India), S. Suman Rajest (Dhaanish Ahmed College of Engineering, India), Karthikeyan Chinnusamy (Veritas, USA), R. Regin (SRM Institute of Science and Technology, India)and Ferdin Joe John Joseph (Thai-Nichi Institute of Technology, Thailand)
DOI: 10.4018/979-8-3693-1355-8.ch015
Purchase
|
Abstract
Home automation is a rapidly advancing field, driven by its increasing affordability and convenience. The ability to control various aspects of our homes and have them respond to automated events has gained immense popularity due to its inherent safety features and cost-effectiveness. In this chapter, the authors have developed a model for fully automating our household while incorporating a robust security system. The core objective of this chapter is to build a completely automated home that can be economically viable. The authors were able to drastically lower the overall cost of installation by utilizing off-the-shelf components. This research further explores pertinent literature, analyses optimal current datasets, and ceases operations by addressing home automation issues while suggesting potential future paths. The central concept of this paper revolves around proposing a system that seamlessly integrates MATLAB with a camera and an Arduino board to monitor and control various household appliances. In this envisioned system, the Arduino board communicates with MATLAB via serial connectivity to simplify household gadget control. MATLAB is linked to image-capturing equipment by enabling real-time monitoring of the status of different household equipment through a Graphical User Interface (GUI) developed in MATLAB. This GUI allows users to issue commands for the corresponding household appliances, interface with the Arduino through a relay board, and respond by turning ON/OFF as instructed. Moreover, the system can send alert messages or signals if any abnormalities are detected. This enhances the overall security and functionality of the home automation setup. The field of human motion recognition, a vital component of this paper, has a rich history spanning over two decades, resulting in a substantial body of literature. As the paper advances, it contributes to this existing body of knowledge while addressing contemporary challenges in the domain. Looking ahead, the future of home automation holds promising prospects for enhancing our daily lives with convenience, security, and efficiency.
Related Content
|
Kula A. Francis, Kenny A. Hendrickson.
© 2026.
26 pages.
|
|
Summyr Burton, Savannah Baus, Stephen A. Murphy.
© 2026.
50 pages.
|
|
Kesley Richardson, Colby Cavanaugh.
© 2026.
30 pages.
|
|
Angela M. Hill, Kevin B. Sneed, Deborah Austin, Deanna B. Wathington, Hiram B. Green, Michael B. Morgan, Janet B. Roman, Feng B. Cheng, John E. Clark, Natasha Rubie, Kristy Andre, Thea Moore, Antionette Davis, Feng Cheng, Karia Doreen MacAulay, Maisha Standifer, Judette Louis, Joseph Diamond, Kyaien Conner, Victor Obi, Samantha Thompson.
© 2026.
22 pages.
|
|
Angela Stephanie Mazzetti, Anniken Grønstad, John Blenkinsopp.
© 2026.
32 pages.
|
|
Marie Grace Avelino Gomez, Kenith B Villaruel.
© 2026.
30 pages.
|
|
Carolyn Allen.
© 2026.
30 pages.
|
|
|