Md. Mahbubur Rahman

Work place: Department of Computer Science and Engineering (CSE), Dhaka International University (DIU), Dhaka-1205, Bangladesh

E-mail: mahbub.shimulbd@gmail.com

Website: https://orcid.org/0000-0003-2502-4634

Research Interests: Mathematics of Computing, Data Structures and Algorithms, Computer Architecture and Organization, Computational Learning Theory, Artificial Intelligence

Biography

Md. Mahbubur Rahman is a smart sensing-based researcher at the Department of Computer Science and Engineering, Dhaka International University. He has completed his B.Sc. (Eng.) and M.Sc. (Research) degree from the department of computer science and engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh. His research interests are in the field of Artificial Intelligence, Internet of Thing (IoT), Machine Learning and Smart Sensing. Now Mr. Rahman serves as a faculty member at Dhaka International University in the Department of Computer Science and Engineering.

Author Articles
Artificial Intelligence Based Domotics Using Multimodal Security

By Khandaker Mohammad Mohi Uddin Naimur Rahman Md. Mahbubur Rahman Samrat Kumar Dey

DOI: https://doi.org/10.5815/ijisa.2023.03.04, Pub. Date: 8 Jun. 2023

All electronic devices in our cutting-edge technology world must be networked together via the Internet if users want to have remote access to them. As a result, it may raise a variety of serious security issues. This study suggests a remote access home automation security system that incorporates utilizing the Internet of Things (IoT), and Artificial Intelligence (AI) for ensuring the security of the house. For a highly efficient security system, Face recognition has been used to maneuver the door access. In case of power outage or for any technical issues, an alternative security PIN has been added which is only accessible by the owner. Moreover, individuals are able to monitor and control the door access along with other attributes of the house using an application. In this work, Face detection is performed using the Haar Cascade classifier, while face recognition is performed using the Local Binary Pattern Histogram (LBPH). 95.7% accuracy in recognizing faces has been achieved after evaluating the proposed system.

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Smart Home Security Using Facial Authentication and Mobile Application

By Khandaker Mohammad Mohi Uddin Shohelee Afrin Shahela Naimur Rahman Rafid Mostafiz Md. Mahbubur Rahman

DOI: https://doi.org/10.5815/ijwmt.2022.02.04, Pub. Date: 8 Apr. 2022

In this fast-paced technological world, individuals want to access all their electronic equipment remotely, which requires devices to connect over a network via the Internet. However, it raises quite a lot of critical security concerns. This paper presented a home automation security system that employs the Internet of Things (IoT) for remote access to one's home through an Android application, as well as Artificial Intelligence (AI) to ensure the home's security. Face recognition is utilized to control door entry in a highly efficient security system. In the event of a technical failure, an additional security PIN is set up that is only accessible by the owner. Although a home automation system may be used for various tasks, the cost is prohibitive for many customers. Hence, the objective of this paper is to provide a budget and user-friendly system, ensuring access to the application and home attributes by using multi-modal security. Using Haar Cascade and LBPH the system achieved 92.86% accuracy while recognizing face.

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