Browsing by Author "Hasan, Mahady"

Now showing 1 - 20 of 33

A Car Security System Based on Alerting Driver Drowsiness and Monitoring the State of the Vehicle
(Independent University, Bangladesh (IUB), 2023-10) Hasan, Md Jahid; Abidur Rahman, Sagor; Islam, Mahmudul; Amin, Mahamudul; Mehedi, Rubayed; Hasan, Mahady
Accidents on the road are the primary cause of death, particularly among children and adolescents. Despite having fewer vehicles, low- and middle-income countries account for the preponderance of these fatalities. Consequently, a system that monitors vehicles and takes the necessary precautions to prevent collisions and fatalities is urgently required. lhis paper proposes a system of Open CV image processing techniques to monitor the driver's eye movements in order to prevent accidents caused by behavioral and psychological changes while driving. The main processing unit (MPU) of the system we have developed consists of Raspberry Pi, Microcontroller, and sensors. Both on day and night time, it detects driver drowsiness and alerts them with a wristband. In low-light conditions, two infrared (IR) blasters and multiple light-dependent resistors (LDR) sensors were used to accurately detect driver fatigue. During an accident, the MPU' s accident detection module will identify and send an SMS message to the vehicle owner with the vehicle's location and data. Eventually, the local police station, fire department, and other safety agencies will be able to take immediate action. The novel aspect of this study is the combination of image processing techniques and sensors that accurately monitor driver behaviour and identify fatigue. The accident detection module of the system is also distinct and can provide emergency services with vital information in the event of an accident.
A Hybrid Approach to Overcome Requirements Challenges in the Software Industry
(Independent University, Bangladesh, 2023-05) Hasan, Md. Tarek; Bakar, Nabil Mohammad Abu; Nahar, Nujhat; Hasan, Mahady; Rokonuzzaman, M.
This research paper presents a hybrid approach to overcome the challenges related to inadequate or insufficient client involvement and understanding during the software requirements phase. The aim of this study is to investigate the factors that contribute to this challenge and propose a solution that combines traditional and agile methodologies. To accomplish this, a survey was conducted to collect responses from industry professionals in the software development sector. The survey results showed that inadequate or insufficient client involvement and understanding is a common issue that leads to delays and misunderstandings in software development projects. To address this challenge, the proposed hybrid approach combines the traditional requirements engineering process with agile techniques such as user stories, prototypes, and continuous feedback loops. The hybrid approach aims to improve communication and collaboration between the client and the development team, ensuring that the software’s requirements are well-understood and documented. The results of this study indicate that the proposed hybrid approach is effective in overcoming the challenges related to inadequate or insufficient client involvement and understanding. The findings of this research have practical implications for software development organizations, highlighting the importance of adopting a hybrid approach to ensure successful software development projects.
A study on social media addiction analysis on the people of Bangladesh using machine learning algorithms
(Scopus, 2024-10) Mim, Minjun Nahar; Firoz, Mehedi; Islam, Mohammad Monirul; Hasan, Mahady; Habib, Md. Tarek
: Social media has become a fundamental element of contemporary life, providing countless benefits but also posing substantial concerns. While technology improves connectedness and information exchange, excessive use raises issues about social and personal well-being. The emergence of social media addiction emphasizes its influence on everyday routines and mental health, with many people favoring online activities above vital tasks, resulting in real repercussions. Twitter, Facebook, and Snapchat have a significant impact on emotional well-being, adding to global rates of despair and anxiety. To measure the frequency of social media reliance, we studied data from 1,417 individuals using machine learning methods such as decision tree (DT) classifier, random forest (RF) classifier, support vector classifier (SVC), k-nearest neighbors (K-NN), and multinomial naive Bayes (NB). Understanding the behavioral patterns that drive addiction allows us to create tailored therapies to encourage healthy digital behaviors. This study highlights the critical necessity to address social media addiction as a complicated societal issue. Our major goal is to determine the amount of people who are addicted to social media.
A Study on Social Media Addiction Analysis on the People of Bangladesh Using Machine Learning Algorithms
(Institute of Advanced Engineering and Science (IAES), 2024-10-15) Mim, Minjun Nahar; Firoz, Mehedi; Islam, Mohammad Monirul; Hasan, Mahady; Habib, Md. Tarek
Social media has become a fundamental element of contemporary life, providing countless benefits but also posing substantial concerns. While technology improves connectedness and information exchange, excessive use raises issues about social and personal well-being. The emergence of social media addiction emphasizes its influence on everyday routines and mental health, with many people favoring online activities above vital tasks, resulting in real repercussions. Twitter, Facebook, and Snapchat have a significant impact on emotional well-being, adding to global rates of despair and anxiety. To measure the frequency of social media reliance, we studied data from 1,417 individuals using machine learning methods such as decision tree (DT) classifier, random forest (RF) classifier, support vector classifier (SVC), k-nearest neighbors (K-NN), and multinomial naive Bayes (NB). Understanding the behavioral patterns that drive addiction allows us to create tailored therapies to encourage healthy digital behaviors. This study highlights the critical necessity to address social media addiction as a complicated societal issue. Our major goal is to determine the amount of people who are addicted to social media.
A Sustainable Approach to Establish Industry-Academia Collaboration by Engaging the Rural Community for the Developing Countries
(Australasian Association for Engineering Education, 2023, Rank B, 2023-09) Kabir Peya, Md Mahmudul; Puspita, Afrin Hossain; Alam, Sabrina; Mahbubul Islam, Yousuf; Shahabuddin, A. M.; Hasan, Mahady
Skill and knowledge both play a vital role in sustainable career development. Universities were built to nurture knowledge thus the focus was on offering a knowledge-based curriculum. On the other hand, the industry's requirement is skill. Hence, the demand focuses on employees with real-world and hands-on skills. This gap between academia and industry impacts both students and industry. Furthermore, developing countries commonly lack the infrastructure needed to work with academia to support research that solves industry-specific problems. The motivation of the study is to work in rural development using engineering knowledge from academia. The research question driving the study is, "How can universities of developing countries mitigate the gap between theoretical learning and practical industrial skills?" Due to the rural environments, developing nations rely substantially on small-scale industries related to agriculture, fisheries, forestry, etc. The goal is to develop a model where students will be exposed to rural industry driven problems throughout their academic journey and work to solve the problems. Which will also prepare them for their future professional roles. The research utilizes case study approach by using data from students at Independent University, Bangladesh, where a three-credit Live-in-Field Experience course is in place. This course is a part of the foundational coursework and involves students living in rural areas, identifying issues in the rural sector, and formulating potential solutions. The effectiveness of this approach is evaluated incrementally, with successive student groups improving upon the previously devised solutions. The study shows that incorporating the model into the academic curriculum offers various outcomes. First, the model promotes experiential learning, where students solve real-world problems, particularly in rural areas. This change in teaching practice broadens theoretical concepts and their practical applications. The model creates bridges between academia and industry. Industry personnel will be interested in working and teaching in academia, which will help students get exposure to current industry practices and gain the required skills. The analysis proves that academic curricula that integrate industry-based problem-solving have an impact on both students and industries. The proposed model connects the bridge between academia and industry. Compared to the existing knowledge, this study could redefine our understanding of effective academic-industry collaborations and the role of universities in developing nations to adapt. The novel approach highlights the necessity of a change from knowledge-based education to one that emphasizes application and problem-solving skills.
AI based Software Testing
(Independent University, Bangladesh, 2023-07) Khan, Saquib Ali; Oshin, Nabilah Tabassum; Musfique, Md Masum; Nizam, Mahmuda; Ahmed, Ishtiaque; Hasan, Mahady
As the complexity of software applications continues to increase,software testing becomes more challenging and time-consuming.The use of artiﬁcialintelligence (AI) in software testing has emerged as a promising approach to address these challenges. AI-based software testing techniques leverage machine learning,natural language processing,and other AI technologies to automate the testing process,improve test coverage,and enhance the accuracy of test results.This paper provides an overview of AI-based software testing,including its beneﬁts and limitations,and discusses various techniques and tools used in this ﬁeld.The paper also highlights some of the current research and development eﬀorts in AI based software testing,as well as future directions and challenges.
Artificial Intelligence in Software Testing: A Systematic Review
(IEEE Region 10 Technical Conference (TENCON 2023), Thailand, 2023-07) Islam, Mahmudul; Khan, Farhan; Alam, Sabrina; Hasan, Mahady
Software testing is a crucial component of software development. With the increasing complexity of software systems, traditional manual testing methods are becoming less feasible. Artificial Intelligence (AI) has emerged as a promising approach to software testing in recent years. This systematic review study aims to provide the recent trend and the current state of software testing using AI. This study examines different types of approaches, techniques, and tools used in this area and assesses their effectiveness. The selected articles for this study have been extracted from different research databases using a search string. Initially, 90 articles were extracted from different research libraries. After gradual filtering in three different phases, 20 articles were selected for final review. Around 50 articles were studied to explore the use of AI in software testing and get an in-depth overview of it. The findings of this study suggest that various testing tasks can be automated successfully using AI, including Machine Learning (ML) and Deep Learning (DL), such as Test Case Generation, Defect Prediction, Test Case Prioritization, Metamorphic Testing, Android Testing, Test Case Validation, and White Box Testing. This study concludes that the integration of AI in software testing is simplifying software testing activities while improving overall performance. This study offers a comprehensive analysis of the utilization of AI techniques in different software testing activities.
Automatic Product Sorting And Packaging System
(Independent University, Bangladesh, 2023-06) Sadman, Mahib; Saha, Sourav Kumar; Haque, Sabrina; Sumi, Faria Islam; Khair, Samira Binte; Nadia, Sanzida; Uddin, Mohammad Rejwan; Hasan, Mahady
Automatic product packaging refers to the process of packaging products without the need for manual human intervention. Over the years, automated packaging systems have transitioned from singular machines that automate one step in the packaging process to now integrating all steps seamlessly into the entire packaging process. This system uses various technologies such as sensors, motors, and software to perform these steps automatically, eliminating the need for manual labour. An object is transferred, sorted colour wise and then finally packed- all through an automated process.
Border Security System Using Real-Time Image Processing
(Daffodil International University, 2020-12-31) Halim, Abdul; Hasan, Mahady; Rana, Sohel
In recent times, it has occurred to us that county borders are now more deadly with security flaws. There are millions of stuff being smuggled in and out, neighbour countries security forces having many ways to advance with gunning down people and entering the border area, seizing people and extortion. That's why it’s our effort to detect forces with a faster image processing method so the security personnel can use it to their benefit. Object detection in modern computer science has developed quite a lot in recent years. With the development of neural network algorithms, some notable of them are CNN, RCNN, and faster-RCNN algorithms. Our motive was to develop a real-time object detection system which can be used at the country border to help detect targets in order to increase security. That's why we used the YOLO (you only look once) algorithm to train and test out data. The YOLO algorithm takes a different approach in order to detect objects faster. In this research project, we trained raw data in YOLO and SSD (Single shot multibox detector) and compared their advantages and disadvantages for having a real-time level of detection and accuracy. This detection scheme can be applied in surveillance systems such as cameras, drones and video surveillance, which will require cloud and server-based processing in object detection Application Programming Interface. we’re hopeful that This research project could be one of the early steps to increase border area security.
Breaking Down the Barriers: How Bangladeshi Banks Can Overcome Obstacles to Automation
(Independent University, Bangladesh, 2023-06) Hasan, Mahady; Alam, Sabrina; Mannan, Anaz Bin; Milky, Golam Rakib; Uddin, Arif Moin; Alam, Md Baharul
The banking sector in Bangladesh has been confronted with numerous challenges, prompting a shift towards automation. Increased competition, rising consumer demands, rising expenses, falling profitability, antiquated legacy systems, and cybersecurity risks are just a few of the difficulties the banking industry is currently facing. Numerous solutions have been put up to solve these issues, including automation frameworks, the transformation of digital banking, mobile banking, and impact analyses of technology advancements. However, some banks may find it unworkable due to probable job losses, decreased client interaction, and the significant investments and training needed for technological adoption. Therefore, before implementing any offered remedies, it is crucial to carefully consider them and their potential consequences.
Colour-Based Agro Product Sorting and Disease Detection
(Independent University, Bangladesh, 2023-06) Mondol, Sukanto; Sheepu, Mahmudul Hasan; MoMo, Fatema Jannat; Fowzia, Afza Noor; Najibah, Nuha; Titly, Zarin Tasnim; Uddin, Mohammad Rejwan; Hasan, Mahady
Due to the growing demand for high-quality food, it is challenging for individuals to distinguish between ripe and unripe foods by color and to diagnose sickness with bare eyes. Even color-based fruit and vegetable sorting requires human labor. Using color recognition technology to automate the sorting process allows organizations to increase production and efficiency while saving time and money. The NodeMCU microcontroller, the TCS3200 color sensor, and servo motors are used to create the color-based sorting device. The system's IoT interface uses the NodeMCU microcontroller. The color sensor detects the product's color and sorts it accordingly. Data about the detected color is transmitted to the website, in this instance, thingspeak is used.
Design and Development of a Nursing Robot for Non-Invasive Monitoring of Human Body Temperature and Heart Rate
(Independent University, Bangladesh, 2023-06) Chowdhury, Alphy Shahrin; Shehnil, Rafia; Hossain, Riyad; Mujnebin, Md Safiul; Sajed, Md; Uddin, Mohammad Rejwan; Hasan, Mahady
This paper describes a nursing robot named RI-YANA developed for measuring human body temperature and monitoring heart rate. Robots are an emerging field of research and development aimed at providing assistance to healthcare professionals. These intelligent machines are mainly designed to take care of the elderly patients, physically disabled patients, patients having contagious diseases such as Covid-19, and also remote area patients where doctors and nurses cannot go instantly. In our robot we have used ECG measurement module for monitoring heart rate and Contactless temperature sensor using Infrared radiation. The nursing robot will record these data and send them to the web page from where the doctor can access the information and take necessary steps. The nursing robot's performance in measuring body temperature and heart rate could be compared with that of traditional measurement methods, such as oral thermometers and pulse oximeters, to determine its utility in a clinical setting.
Develop a System to Analyze Logs of a Given System Using Machine Learning
(Independent University, Bangladesh (IUB), 2023) Hasan, Md. Tarek; Sadia, Farzana; Hasan, Mahady; Rokonuzzaman, M.
Software error detection is a critical aspect of software development. However, due to the lack of time, budget, and workforce, testing applications can be challenging, and in some cases, bug reports may not make it to the final stage. Additionally, a lack of product domain knowledge can lead to misinterpretation of calculations, resulting in errors. To address these challenges, early bug prediction is necessary to develop error-free and efficient applications. In this study, the author proposed a system that uses machine learning to analyze system error logs and detect errors in real time. The proposed system leverages imbalanced data sets from live servers running applications developed using PHP and Codeigniter. The system uses classification algorithms to identify errors and suggests steps to overcome them, thus improving the software’s quality, reliability, and efficiency. Our approach addresses the challenges associated with large and complex software where it can be difficult to identify bugs in the early stages. By analyzing system logs, we demonstrate how machine learning classification algorithms can be used to detect errors and improve system performance. Our work contributes to a better understanding of how machine learning can be used in real-world applications and highlights the practical benefits of early bug prediction in software development.
Development of Web Based Application-E Learning Platform
(Daffodil International University, 2018-12) Hasan, Mahady; Kundu, Pritom Kumar; Imran, Md. Tajul Islam; Reety, Nishana Yeasneen
This project is intended to develop a web-based application online which will provide easier communication between teacher and student. The proposed project is a web-based application which tries to help the student to learn ICT. In our project, there are two main actors so we defined their activity respectively. First of all, the user has to login in our system. Then the user fills the form as a student or teacher. Admin can be approved or cancel the user request if they are not fulfilling the information. Super Admin can check the profile, approve or cancel the request and Admin see that which account is approved by which Admin. After approving the account, a student can see the facilities. They can see, read, their profile with a personal photo. They can see the lecture material of ICT according to their class. Admin can also post the notice. After the implementation of all functions, the system is tested in different stages and it works successfully as a prototype.
Enhancing Product Market Payoff in Small and Medium Internet-Based Firms: A Survey-Based Analysis of Innovation and Competition Factors
(Independent University, Bangladesh, 2023-05) Bakar, Nabil Mohammad Abu; Hasan, Mahady; Rokonuzzaman, M.
This paper aims to explore the relationship between innovation and competition and identify the conditions that affect the industry’s innovation and welfare. The authors analyze various factors, including the properties of product market payoffs, to determine whether competition increases or decreases industry innovation. The ultimate goal of this study is to provide policy recommendations that support innovation and competition.To achieve this objective, the authors conducted a survey to collect responses from industry professionals and identify the challenges that hinder innovation and competition. They examined several models and case studies,to understand how competition drives innovation. Despite the challenges, leading business consultants found that increased competition leads to higher productivity in various industries, including manufacturing and services.The study’s findings reveal that the recommended policy effectively overcomes the challenges related to innovation and competition sustainability. These findings have practical implications for regulatory organizations, highlighting the importance of adopting these policies to ensure innovation and competition for small and medium-sized internet-based firms.This paper presents a thorough examination of the correlation between innovation and competition, outlines the key elements that foster both innovation and competition, and suggests policy measures to bolster innovation and competition while improving product market outcomes.
Factors to Form Business Strategy for Online-Based Ride-Sharing Services
(Second World Conference on Information Systems for Business Management (ISBM), 2023, Springer, 2023-06) Islam, Mahmudul; Khan, Farhan; Nahar, Nujhat; Hasan, Mahady
In terms of social, economic, sustainability, and environmental challenges, ride-sharing services play a significant role in reducing traffic congestion and the number of automobiles on the road. The objective of this study is to investigate the important factors for the business of ride-sharing services. Also to understand how the ride-sharing companies’ software marketing strategies evolved especially amid the COVID- 19 pandemic to attract consumers and keep customer retention consistent. This research was done through a blended approach of quantitative and qualitative methods. Google forms have been used to collect data from respective stakeholders. In data analysis, Python has been used to extract statistical data and to evaluate variables that played a vital role in customers’ and companies’ perspectives. In this survey research, 108 responses have been received from consumers and 4 responses from companies. Collected survey data shows that safety issue was the most critical factor during the pandemic while avoiding traffic jams before the pandemic. Promotional marketing such as offering discounts on special hours plays a vital role to attract customers. Emergency contact alert, live location sharing, better quality helmets, and ride-sharing with multiple people these facilities have been demanded by the survey respondents. Customers showed a positive perception regarding extra services provided by ride-sharing companies during COVID-19. The results of this study discovered improvement factors that can be used to make business strategies for ride-sharing companies. This study will also help marketing strategists to get a better understanding of their shortcomings and have a scope for a more detailed investigation further in the future.
Fake News Detection Using Machine Learning Techniques
(Independent University, Bangladesh, 2023-03) Sultana, Achhiya; Islam, Mahmudul; Hasan, Mahady; Ahmed, Farruk
A lot of information is spread by people in the social media to update their status and share crucial news with others. But the majority of these platforms don’t promptly validate the individuals or their posts and people aren’t able to identify the fake news manually. Therefore, there is a need for an automated system capable of detecting fake news. This research has proposed to build a model using four machine learning algorithms. The dataset employed in the experiment is a composite of two datasets containing almost equal amounts of true and fake news articles on politics. The preprocessing stages begin with cleaning the data by removing punctuation, tokenization, special characters, white spaces, redundant word elimination, numerals, and English letters followed by stemming and stop with data discretization. Then, we analyzed the collected data and 80% of the data has been used to train each model initially. After that, the four manifested classification algorithms are applied. For identifying fake news from news articles, methods like Logistic Regression, Decision Tree, Random Forest, and Gradient Boosting Classifier were used. The trained classifiers’ accuracy has been evaluated using the remaining 20% of the data. The results show that the decision tree model produces the best accuracy of 99.60% and gradient boosting of 99.55%. Besides, the random forest shows 99.10% along with the logistic regression 98.99%. Moreover, we have explored the best model to achieve the highest precision, recall, F1-score based on the confusion matrix’s outcome.
Food Rotting Prediction and Detection System for warehouse
(Independent University, Bangladesh, 2023-07) Rahman, Mahfuzur; Shafi, Fardin Ahsan; Khatun, Halima; Oshin, Nabilah Tabassum; Sufian, MD Abu Sauri; Kabir, Ashraful; Uddin, Mohammad Rejwan; Shidujaman, Mohammad; Hasan, Mahady
this thesis paper presents an elementary approach to food spoilage detection and prediction in a warehouse setting, offering a practical and cost-effective solution to reduce food waste and improve food safety. This project develops a device that can predict and detect food spoilage in a timely and accurate manner by utilizing different gas sensors, temperature, and humidity sensor to predict and detect the presence of spoilage in stored food. The gathered data from the stored food is then processed and analyzed by the system. The output is displayed on an LED screen and a buzzer goes off to alert the food keepers. The project also involves the development of a user-friendly interface to allow for easy monitoring and management of the system. It uses a Bluetooth module to transmit the resulting data from the system. The findings of the study demonstrated the effectiveness of the Food Rotting Prediction and Detection System, with the sensors providing reliable data for predicting and detecting food spoilage. A mixed method analysis including thematic analysis and predictive modeling allows for more robust validation of the findings, as the results can be triangulated across different data sources.
Fruit Quality And Monitoring Using Deep Learning
(Independent University, Bangladesh, 2023-06) Shochcho, Muhtasim Ibteda; Mahmud, Md.Ridwan; Rahman, Mohammad Ashfaq Ur; Sohag, Md Maruf Kamran; Shams, Daiyan Mohammad; Samiha, Mysha; Uddin, Mohammad Rejwan; Hasan, Mahady
This paper proposes the use of Internet of things (IOT) technology in commercial shop for scanning a product and monitor its quality. The paper present overall monitoring system based on IOT, which includes sensor hubs for collecting its required data for scanning a product and monitoring it. The proposed system consists of multiple levels system, providing a new way for shop owners to access their shop’s product information. The paper presents an automated system for identifying a product quality, and monitoring system. The proposed automated product scanning system can help shop owners to maintain their good way of service, for this system, shop owners can reduce their labour cost. The use of IOT technology isn’t new for commercial shop owners, but they use different types of products for different kinds of sections. But in this proposed system they can control an overall system from products scanning to monitoring and it will be more cost effective than other system.
Impact of COVID-19 on the Factors Influencing On-Time Software Project Delivery: An Empirical Study
(18th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE), April 24 - 25, 2023 Prague, Czech Republic, 2023-03) Islam, Mahmudul; Khan, Farhan; Hasan, Mehedi; Sadia, Farzana; Hasan, Mahady
The objective of this research paper is to investigate the impact of COVID-19 on the factors influencing ontime software project delivery in different Software Development Life Cycle (SDLC) models such as Agile, Incremental, Waterfall, and Prototype models. Also to identify the change of crucial factors with respect to different demographic information that influences on-time software project delivery. This study has been conducted using a quantitative approach. We surveyed Software Developers, Project Managers, Software Architect, QA Engineer and other roles using a Google form. Python has been used for data analysis purposes. We received 72 responses from 11 different software companies of Bangladesh, based on that we find that Attentional Focus, Team Stability, Communication, Team Maturity, and User Involvement are the most important factors for on-time software project delivery in different SDLC models during COVID-19. On the contrary, before COVID-19 Team Capabilities, Infrastructure, Team Commitment, Team Stability and Team Maturity are found as the most crucial factors. Team Maturity and Team Stability are found as common important factors for both before and during the COVID-19 scenario. We also identified the change in the impact level of factors with respect to demographic information such as experience, company size, and different SDLC models used by participants. Attentional focus is the most important factor for experienced developers while for freshers all factors are almost equally important. This study finds that there is a significant change among factors for on-time software project delivery before and during the COVID-19 scenario.