NSU IR :: Browsing by Author "Atiqur Rahman"

Browsing by Author "Atiqur Rahman"

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Open Access
Augmented Reality Home Decorator
(North South University, 2019) AL-AMIN; SHARIEAZ KAVIER; Atiqur Rahman; 1520664042; 1513192642
This project presents an application of Augmented Reality (AR) for interior design. Due to huge advancements in computer vision algorithms and cheap hardware, Augmented Reality is becoming mainstream. All over the world, most of the sales come from physical stores. Buying furniture from brick-and-mortar shops is cumbersome and time-consuming. AR is changing the furniture industry. In an AR environment, virtual furniture could be placed and manipulated in the physical world in real time, which allows the user to have an interactive experience. Users would be able to visualize exactly how a table would look in their kitchen, dining room, bedroom, or anywhere they want. When people can place an actual couch in the living room or visualize how a bookshelf would look in a Different color. The risk of product return and logistics is drastically reduced. As online stores replace brick-and-mortar shops. AR will play a vital role in the furniture sales. This project provides new ways an individual/enterprise could utilize AR to design interiors.
Open Access
Deep Learning Approach for Keypoint-Based Bangla Word Sign Detection for Videos
(North South University, 2023) Arnop Singh Durjoy; MD. Shahidul Islam; Mahidul Islam Bhuiyan; Atiqur Rahman; 2011061042; 2011703642; 2011111642
This research delves into the realm of Bangla sign language recognition, focusing on developing a robust system for interpreting and analyzing gestures depicted in videos. Employing a keypoint based approach and leveraging deep learning technology, specifically a two-layer LSTM architecture, our methodology aims to interpret Bangla word signs accurately. The project's foundation lies in a meticulously curated custom dataset featuring 51 unique signs captured by two proficient signers, ensuring comprehensive coverage of articulation, speed, and style variations. Our system's tailored approach acknowledges a bridge to communication gaps and enhances accessibility for the Bangla-speaking Deaf community. Beyond technical advancements, this research aims to elevate societal awareness and foster employment opportunities for the Deaf population, ultimately contributing to a more inclusive world. The outcomes of this project have the potential to not only revolutionize Bangla sign language recognition but also pave the way for broader applications in accessibility and advancements in deep learning technology for diverse sign languages worldwide.
Open Access
E-Care Management System by Web Technology
(North South University, 2021) Tareq Rahman; Mohammad Ali; Tahia Tasnim; Atiqur Rahman; 1611097042; 1612571042; 1811155042
We built a project that will improve hospital experience among patients, doctors, and hospital authorities. That’s why the name of our project is “E-Care Management System”. The entire system will be based on the Internet. People will be able to schedule appointments with doctors, obtain prescriptions, and seek advice from doctors through this website, and doctors will be able to communicate with patients. This project aims to create a general-purpose e-care system that will allow patients to get their preferred service during critical periods from the comfort of their own home over the Internet. Our project's key objectives are to administer the entire system and put hospital officials, doctors, and patients under one roof to make the system transparent and user-friendly[1].
Open Access
Efficient Intelligent Solar Tracking Control System
(North South University, 2021) Mahima Anwar; Asif Abbas; Tahsin Tabassum Urnisha; Atiqur Rahman; 1631549043; 1721367043; 1632001043
The electricity demand of Bangladesh has been increasing at an average pace of 10% over the last decade. There is still a scarcity of electricity in many rural areas of Bangladesh. A renewable-energy-based system will bring more benefits than conventional power. Solar energy is a renewable, free source of energy that is sustainable and also a non-polluting source of energy. Nowadays, solar power is being used to meet the shortfall of electricity. The paper considers an efficient intelligent solar tracking system to increase the efficiency of solar energy production. The purpose of the paper is to generate electricity from solar energy & increase efficiency. In the project, two dual-axis solar panels, which have been attached with two servo motors, collect solar energy by rotating both vertically and horizontally. Another solar panel is connected, which lies in a horizontal plane, to compare the difference in the electrical output of the two different setups and calculate the efficiency. Data is collected in different weather conditions by the solar panels. The RF module is used to transmit data over the wireless channel. The receiver part of the RF module is connected to the computer, and the received data is monitored in real time. The main aim of this project is to increase the efficiency of the solar panel to meet the rising demand for electricity at a lower cost in Bangladesh. Solar energy can be widely used for different purposes in Bangladesh by installing large solar grids to minimize the cost and get maximum efficiency.
Open Access
Innovative System for Mask Detection & Distance Maintainer
(North South University, 2021) Md. Nasir Uddin; Sheikh Imam Hossain; Md. Mahfuzur Rahman Shakil; Atiqur Rahman; 1811274642; 1812617643; 1812918642
Covid-19 is a novel virus that has never been seen in humans before. This disease was first detected in December 2019 in Wuhan, China, and has been spreading since worldwide. The virus can easily pass from person to person through breathing & making physical contact, which is why it is spreading rapidly. To stop the transmission of Covid-19, wearing face mask and maintaining social distance are crucial disciplines to follow. But these disciplines are not being followed properly because of the lack of monitoring system that could enforce such disciplines among people especially in places of social gathering. As a result, lockdowns are being enforced & many work places, industries, garments, educational institutions are being shut down in order to stop the spread. Which is damaging our economy & productivity to a great extent. In order to prevent further damage & to recover the losses due to pandemic, we have come up with a project plan that deals with ensuring a system which is capable of detecting faces with & without masks and also capable of measuring distance between person to person & displaying the information in details on big screen for monitoring. The project is AI and deep learning-based. Various types of electronic devices & components are required to make this system. The system we are developing is productive, feasible & can be easily implemented. And for being cost efficient, it can be mass produced as well. By implementing such system in places of social gathering can prevent the transmission of the virus. As the system enforces people to wear masks & maintain certain distance from each other at gathering places, it significantly reduces the possibility of transmission. And because of the implementation of the system, lockdowns will no longer be necessary & people can continue working in their respective work places. Productivity & progress will continue, even during the pandemic. This project can bring forth significant changes in economic progress & development of the country and can assist in recovering the productive losses due to the pandemic.
Open Access
Real-Time Face Mask Detection
(North South University, 2021) Muanna Zilan; Ijaz Ahmed; Asif Anan; Atiqur Rahman; 1530810042; 1620483042; 1621358042
Nowadays, COVID-19 is a global problem. To ensure safety, the government announced that everyone should wear a face mask. Everyone should maintain this rule. But some people don't follow this rule. Some people don't wear a face mask when they are in a public place. And police are also monitoring face mask safety. But the authority can't maintain it all the time. So, we are building an application that will detect the face mask using a camera in real-time. This system's primary goal is to see the face mask using a camera. This system will help the government or the respective authority determine who wears a face mask and who does not wear a mask, and take necessary action against those persons. The algorithm is trained to capture facial features in real-time video streams and images and recognize whether everyone is wearing a protective mask with a standard accuracy rate. Equally useful for both individual and group detection, our face mask detection system can supplement or reduce the number of enforcement agents on the ground. After performing the initial analysis, the system classifies every person as "wearing a mask" or flags as "not wearing a mask" and sends an instant alert, so we can take further action — dispatch a public audio announcement, send a custom message to a digital screen, or a personalized message to the person's phone. Proactively manage and correct visitors' behavior while remaining compliant with privacy regulations.
Open Access
Smart Agriculture Monitoring System
(North South University, 2021) Mohammad Rakib Hasan Tipu; Md. Al-Amin; Joy Saha; Atiqur Rahman; 1530174042; 1520179642; 1520715042
Agriculture is the root to a country's economic development. In recent times, huge scientific advancement has been implemented in various agricultural fields for the betterment of the future. Despite various researches, proper assessment and productivity couldn’t be reached. We have tried to focus on different scientific applications which could be put together in the agricultural field for better accuracy with better productivity using less man-power. Moreover, we include a method for monitoring the agricultural fields from any remote location and assess the basic condition of the field. We also use solar tracking systems to generate the required renewable power supply in agriculture fields that could lead to an eco-friendly way of energy production, leading to a proper step towards the next green world. Bangladesh economy draws its main strength from the agriculture sector. The sector contributes 19.10% to GDP (at current prices) and employs 50.28% of the labour force. However inadequate management practices are one of the driving causes for agricultural productivity to be reduce din Bangladesh. The use of fertilizers, quality seeds, and irrigation together cannot ensure sustainable production unless timely and appropriate measures for the management of other nutrients are simultaneously pursued. Therefore, this project proposes a completely innovative, user friendly technology that assists farmers in maintaining their irrigation without any effort.
Open Access
Smart Green House Farming using IOT
(North South University, 2021) Shawon Das; Smita Roy Jyoti; Atiqur Rahman; 1712591642; 1711615042
The fundamental idea is to increase the growth of different varieties of crops with good quality in a closed environment, usually a Greenhouse. The proposed system can monitor the changes in factors like temperature, humidity, and soil moisture by integrating the sensor elements. Sensor values are inserted on the Ubidots website, which can be used to analyze agricultural data. The website is also used to monitor and control the parameters, weather information, etc. It will reduce the labour cost and time, and also can increase the growth of any kind of homespun and foreign crops.
Open Access
Vehicle Identification and Counting System Using Machine Learning
(North South University, 2021) Md. Shahrior Gohor; B. M Tanvir Hossain; Atiqur Rahman; 1610824042; 1611687042
In the realm of road management, the significance of intelligent vehicle recognition and counting has grown immensely. However, this task is made inherently challenging by the wide variety of vehicle sizes and shapes on the road, which directly influences the accuracy of vehicle counting. To tackle this challenge, we present a robust vision-based vehicle recognition and counting system that employs the Yolo machine learning method. In the context of intelligent road traffic management and control, accurate vehicle identification and comprehensive statistics in road monitoring video sequences are paramount. The proliferation of traffic surveillance cameras has resulted in a vast reservoir of traffic video footage for analysis. An elevated viewing angle is necessary to achieve a broader view of the road surface. But at this increased viewing angle, the size of vehicles varies significantly, and the accuracy of detecting smaller objects situated farther from the road diminishes. In light of these formidable challenges posed by diverse camera conditions, addressing and surmount these obstacles effectively is crucial. In this study, we propose a promising approach for vehicle detection that goes beyond mere identification. The findings from our system serve as a foundational component for multi-object tracking and vehicle counting. Our vision-based approach, utilizing the Yolo machine learning method, is tailored to accommodate the dynamic nature of road traffic. By continuously improving the accuracy of vehicle recognition and counting, we contribute to more intelligent road traffic management and control. The insights gained from this system offer valuable data for traffic analysis and decision making, ultimately leading to safer and more efficient roadways.

Browsing by Author "Atiqur Rahman"

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