Theses - Undergraduate

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Open Access
3-SURVIVORS: Rough Terrain Negotiable Teleported Mobile Rescue Robot with Object Detection
(North South University, 2019) Rafia Alif Bindu; Sazid Alam; Nusrat Jahan Moni; Dr. Shahnewaz Siddique; 1510080643; 1511394042; 1510531042
Today, technology is developing in the same direction in line with rapidly increasing human needs. The work done to meet these needs makes life easier every day, and these studies are concentrated in robotic arm studies. Robot arms work with an outside user or by performing predetermined commands. Nowadays, the most developed field of robot arms in every field is the industry and medicine sector. When we talk about robots, people tend to think that robots are only suitable to use in the industry or just for the scientist to test new technologies. However, the main function of robots is to help humans in doing work either in the industries or just helping out doing normal household chores. To bridge the gap of the normal perception of “robots are for the industries only” is omitted for our project. This project presents the development of a radio-controlled robotic arm. The movement of the robot arm can be controlled by a FlySky FS-CT6B 2.4GHz 6CH Transmitter and a radio controller. This robot can be used to demonstrate that a robot can be used inside a home or outside for daily human chores. The robot is controlled by Arduino that interfaced with the controller by a 500 GHz receiver. Designed and realized in the project, the robot arm has the ability to move in 6 axis directions with 6 servo motors. Two types of analysis was done for this project that is servo motor analysis and accuracy test. The accuracy test shows that the results of the actual output of the servo motor as compared to the input send to Arduino Uno via controller is between 90% to 95%. This prototype of the robot showed that the operation was successful. This user-friendly robot is expected to bridge the gap between robot and household chores
Open Access
360 Degree Rotating Autonomous Line Follower Vehicle
(North South University, 2019) Shakila Reza Falgunee; Md. Forhad Sarker; Mahdia Maimuna Maisha; Shazzad Hosain; 1511463643; 1430046042; 1430720643
Our project has four features. It is initiated via a Bluetooth controller. Operator fixes the designated checkpoint. It can be controlled both manually and can run autonomously. Then vehicle runs on distinguishing the black path with the white space around via 4 IR sensors attached ahead of the vehicle. There is ultrasonic sonar that detects any obstacle in front on the following path. Sonar stops the vehicle keeping a distance of 15 cm away from that obstacle. This vehicle is set up algorithmically to take the rightmost path when any obstacle comes over its black line path. Our project is made to carry an approximately 10kg weight and reach to the designated checkpoint targeted by operator via Bluetooth. It has no limitation for unloading. The main unique feature is that it can take a rotation of 360 degree when task is completed after unloading. Vehicle comes back to the original point from where it has been started after 360 degree rotation from the end point. It is designed with 4 customized wheels connected with 4 Dc gear motor at four different corners under a PVC board. Over the board there is motor shield connected in parallel with Arduino mega. Ultrasonic sonar and 5 IR sensors and 12 volt battery are connected with Arduino too.
Open Access
3D Multiplayer First Person Shooter Game
(North South University, 2019-08-31) Samira Mahmood; Maruf Ahmed; Nafisa Mahbub Piyal; Md. Hayder Ali; AKM Bahalul Haque; 1520265042; 152 0054 042; 152 1230 642; 152 1231 642
Video Games have always been a leading form of entertainment being available for people of all ages. Eventually, with the evolution of technologies improving the functionality of playing video games, multiplayer games have received increased popularity. In a multiplayer game, several people interact in real-time over a network like internet or a local connection. One of the primary reasons for multiplayer games receiving so much enthusiasm and attention is because of the thrilling experience of competing with human counterparts. Over the years, Bangladesh has become a significant part of the gaming community, yet there aren‘t many startups or individuals who are seeking to get involved in the lucrative game industry. In reference to the aforementioned facts and enormous popularity of multiplayer games, our incentive is to contribute and to be part of the global game industry. We plan to create a 3D multiplayer FPS (First Person Shooter) game with appealing graphics and visuals, and we‘ll also include some features to make the game stand out
Open Access
A CLOUD BASED MICROPAYMENTS SYSTEM FOR E-COMMERCE PURCHASES: SECURED USING FINGERPRINT AUTHENTICATION AND ENCRYPTION.
(North South University, 2019) Tahmid Khan Nafee; Zubair Rahman; Fariha Islam; Sadman Mahmud; Zunayeed Bin Zahir; 1430312040; 1430133042; 1530704042; 1530948042
Online payments are a big pain point in Bangladesh, especially in the context of the rapidly growing e-commerce industry. Most people don't have easy access to credit cards, due to the increasing fear of money laundering and theft. Moreover, even when credit cards are issued, there is a significant monthly cap, which hinders the industry. In this report, a solution in the form of a mobile payments system is presented. The customers are able to deposit money into their accounts as easily as re-charging their cell phone plans and the merchants are able to accept payments from these customers through secure generation of invoices. Therefore, with certain assertion it can be stated that steps have been taken in the right direction to actually solve the problem of online payments in Bangladesh.
Open Access
A Comparative Study of Machine Learning Techniques for Autism Spectrum Disorder (ASD) Detection
(North South University, 2022) Zahid Hasan; Towsif Muhtadi Khan; Dr. Atiqur Rahman; 1911509042; 1911576042
Autism Spectrum Disorder (ASD) is a developmental impairment caused by brain differences. ASD patients may have a recognized difference, such as a genetic disease [1]. Autism can be diagnosed at any age and is referred to as a "behavioral disorder" since symptoms often develop within the first two years of life [1]. In this study, we have implemented different classifier algorithms such as Decision Tree Classifier, Logistic Regression, and Multi-layer Perceptron classifier (MLP Classifier) for detecting ASD in three types of people - adults, adolescents, and children. The proposed techniques are evaluated on publicly available three different non-clinically ASD datasets [2]. After applying various machine learning techniques and handling missing values, results strongly suggest that ANN-based prediction models work better on all these datasets with higher accuracy of 98.58%, 98.30%, and 95.24% for Autistic Spectrum Disorder Screening Data for Adults, Children, and Adolescents, respectively.
Open Access
A Deep Learning approach using Action Recognition for Pedestrians & Vehicle Overtaking of Bangladesh Highway Road Dataset & it’s Implementation
(North South University, 2022) Kazi Tamzid Akhter, Md Hasib Iftekhar Islam Khan Pranta, Shams Saniat, A. S. M. Samiul Islam ; Dr. Nabeel Mohammed; 1620570042; 1721194042; 1821848042; 1921826042
Intelligent transportation systems have been met with resounding approval from individuals, governments and automobile manufacturers located all over the globe. The primary problems in the field of intelligent and self-driving & non self driving vehicles are identifying impediments, particularly people, and preventing accidents with them. In order to advance intelligent transportation systems for both self-driving cars and all other manual cars, we focused on using deep learning methods to identify pedestrians. After that, some of the most popular deep learning techniques were covered. The accurate identification of pedestrians in self-built automobiles still has a lot of flaws. This study highlights the challenges the transportation industry faces. The solutions are intended to help reduce traffic, accidents. Large automakers (including Google and Tesla) , working to develop self-driving and non-selfdriving vehicles that can transport passengers safely even while the driver is sleepy. Sensors that can sense their surroundings, identify what is close by, and communicate that information to the driver must be installed in these cars. neural networks, which often include several hidden layers and nonlinear processing units, are the basis for most deep learning approaches.
Open Access
A Low-Cost Biomedical Device to measure Body Temperature, Heart Rate, ECG and Fractured Angle Through Motion
(North South University, 2019-04-30) Tarek Ahmed Khan ID # 1520436; Fairooz Alam; Debashis Bhowmik; Sabbir Ahmed; Dr. Mahdy Rahman Chowdhury; 1320350043; 1513216642; 1521155642; 1520436042
This report presents the design and the implementation of a mobile application based smart Health Care system in Bangladesh. In this system, any patient can communicate with their doctor easily through app simultaneously. There is a lackof proper management in the hospitals of our country. The main purpose of this project is to provide better opportunity for those sufferer patients who face difficulties while communicating with their doctors at the time of their need. The system has been designed in such a manner that will help a patient as well as a doctor of both rural and urban areas. This system also allows doctors to keep their patients under monitoring all the time. We developed this system to help the people of our country who are badly suffering from not having a good healthcare system in an easy and affordable way. The system will be accessible from android app via the internet. The report includes content designing, hardware implementation and android mobile application development
Open Access
A Machine Learning and Embedded Approach to Detect Fire, Identify the Cause of it and Extinguish Using the Best Possible Extinguisher
(North South University, 2023-02-01) Md. Rashiqur Rahman; Sabbir Ahmed; Md Shafin Islam Rudro; Sadia Aktar; Md. Shahriar Hussain; 1812366042; 1813515042; 1821054642; 1821516042
Chemical fires are a major cause of devastating situations and fatalities in Bangladesh, where inadequate knowledge of extinguishing such fires has led to numerous deaths, including those of firefighters. To address this issue, we propose a machine learning and embedded systems approach to design a dynamic and portable prototype that can remotely monitor the fire incident and determine its cause. The prototype uses a dashboard camera to stream video and gas sensors to detect the chemical gas information in the environment to identify and extinguish the fire. The embedded approach clarifies the cause of the fire and suggests the most suitable extinguisher to the user. The device is economical, portable, user-friendly, and marketable in Bangladesh. The system produces satisfactory results with high accuracy in fire detection and maintains its objective of being low-cost and user-friendly. The device can be remotely controlled using a mobile phone and web-based application. The system's machine learning approach uses appropriate datasets and algorithms (YOLOV5), while the embedded approach employs suitable sensors and a microcontroller (ESP32). The system's accuracy has been shown to be perfect.
Open Access
A Medical Community Android App, Detect COVID 19 and Pneumonia Using Deep-learning
(North South University, 2021) Shuva Chowdhury; Istiak Ahamed Saif; Faijul Abedin; Amirul Ahsan Simon; Riasat Khan; 1731245042; 1712196642; 1711316642; 1632129642
COVID-19 is the biggest headache for the whole world, including detecting COVID-19-affected patients. Early detection of COVID-19 may aid in the development of a treatment strategy and disease containment decisions. Also, a community through application among doctors, nurses, and patients can reduce deprivation of treatment and health care services. In this paper, we make a medical community Android application for doctors, nurses, and patients that can detect COVID-19 from chest X-ray photographs developed using a convolutional neural network deep learning algorithm (VGG16). The COVID-19, Pneumonia, and standard chest X-ray images are collected and joined from a public source, Kaggle. 9000 chest X-ray photographs were used for training, including 3000 COVID-19 chest X-ray photographs, 3000 Pneumonia chest X-ray photographs, and 3000 standard chest X-ray photographs. For testing, 3000 chest X-ray photographs were collected, with 1000 COVID-19 chest X-rays, 1000 Pneumonia chest X-rays, and 1000 normal chest X-rays. The accuracy of our training is 98 %, while the accuracy of our validation is 95%.
Open Access
A Multichannel Localization Method for Camouflaged Object Detection
(North South University, 2022) Mohammad Rakibur Rahman; Md Mafri Chowdhury; Md Shohanur Rahaman Sarker; Md Shahriar Karim; 1812964042; 1813393402; 1812457402
Camouflaged objects can be difficult to detect because they blend in with their surroundings. There have been numerous studies on detecting camouflaged objects, and many of these have been recognized as effective approaches. This paper presents a new algorithm for detecting camouflaged objects by focusing on identifying the region of interest, which is crucial for detecting these objects. The algorithm uses Phase Fourier Transformation to create a filtered image, and Entropy to generate a feature map from the filtered image. The feature map is then used to determine the region of interest. This paper proposes a multichannel method for discriminative region localization in Camouflaged Object Detection (COD) tasks. In one channel, processing the phase and amplitude of a 2-D Fourier spectrum generates modified form of the original image, used later for a pixel-wise optimal local entropy analysis. The other channel implements a class activation map (CAM) and Global Average Pooling (GAP) for object localization. We combine the channels linearly to form the final localized version of the COD images. Experimentation in multiple COD datasets demonstrates that the proposed method successfully localizes regions containing more than 80% of the camouflaged objects. Our proposed method does not require memoryintensive devices or prior training on particular image features, making it easily integrated into a resource-constrained environment. Theproposed approach is also applicable to non-COD images
Open Access
A novel Approach to LUFlow Intrusion Detection System Using Machine Learning Method
(North South University, 2021-02-28) Taslima Akter; MD Asif Mahmud; Intisha Islam; Dr Mohammad Monirujjaman Khan; 1721599042; 1712841642; 1711854642
We will create a model that will be taking images as input and extract the Bangla words from there and translate it into English. The main idea is to recognize Bangla texts from images, extract it from there and translate it to English. We will use the knowledge on OCR, NLP, Google Cloud API, etc to make it happen. This application will be helpful to foreigners who will come to visit Bangladesh but don’t know Bangla. They can read any instruction and signs written in Bangla only by taking a photo of the sign and uploading it to our application to get the output.
Open Access
A Portable ECG Machine
(North South University, 2018-04-30) Sabuj Golder; MD Fatin Rahman Behon; Nasik Monowar; Dr. Tanzilur Rahman; 1330061042; 1320907042; 1320164042
Electrocardiography commonly known as ECG is the process of recording electric signals generated from the heart’s rhythm. The accurate Electrocardiogram (ECG) and pulse rate information is one of the most important aspects for the various sorts of heart functioning disorder identification. The paper briefly shows how the project was carried towards the aim and demonstrates a solution for acquiring ECG signals in a portable way. The goal was to make a prototype of a portable ECG-monitoring device is for clinical and non-clinical environments as part of a telemedicine system to provide remote and continuous surveillance of patients. The aim was to make a smart, easy to use, less costly, portable device to observe the heart beat signal from anywhere in any emergency case.
Open Access
A Precise Low Current Measurement Device
(North South University, 2023) Shahriar Shihab; Ibrahim Khalil Ullah; Mahbuba Sarmin; Dr. Nafisa Noor; 1912725043; 1913041643; 1921119043
The main task of this project is to perform very small and precise size current measurement, which includes current measurement at the milli scale, microscale, and nanoscale. The work of this project has been completed through specific metho ds such as literature review, calculation, simulation , and hardware implementation. This project has several important significances including small-scale measurement as well as reducing burden voltage and minimizing the overall cost.
Open Access
A Real Time Pothole and Speed Breaker Detection Using Deep Learning
(North-south University, 2019-04-30) Zahid Hasan; Tasmia Rahman Shahidi; Samsoon Nahar Shampa; Dr. Shahnewaz Siddique; 1510846042; 1521367642; 1511148042
The road accident rate in Bangladesh is increasing day by day due to various reasons. One of these reasons are poor road conditions. Unwanted potholes, missing pitches, improper speed breakers, unfinished manhole covers and slabs transform many roads into obstacles courses thus greatly increasing the probability of serious accidents. However, the arrival of new assistive driving technologies hold much promise in making the roads the safer and avoid serious accidents and damages. The main goal of our project is to create real-time assistive technologies to detect potholes and speed breakers for on-road drivers in general but especially for bikers and cyclists. Our system will provide drivers with advance notification about upcoming potholes and speed breakers and thus assist in avoiding unwanted accidents. Our system will provide drivers sufficient time to react to and avoid these impending road hazards
Open Access
A Smart Online Medicine Selling System Along With DIMS And BDMS
(North South University, 2020-06) Muttakin Ahamed; Md. Golam Haider; Monjur A-Elahi Tanmoy; Dr. Tanzilur Rahman; 1610830042; 1620218042; 1620587042
An Online Medicine Selling System is a platform where the user will be able to buy medicines online. There are some websites available in our country running online medicine selling systems. But the change we have made in ours is to sell not only New Medicines but also Unused Medicines by the user. Pharmaceuticals, generics, and indications will categorize each of the medicines. Pharmaceuticals will help users to know from which company this medicine has been produced, generics will allow users to know which type of drug it is, and indication will help to know for what disease or problem you need to take that medicine. Secondly, we made a Blood Donor Management System from where the user will find out blood donors available in our country for their needs. And finally, we made a Drug Information Management System, which will help users know about medicines in detail like pharmacology, indications, contraindications, side-effects, precautions, dosage & administrations, and so on. We planned to make a platform that will be a complete hospitality system related to the medical sector that will be a great help for the people of our country. From this thought, we collaborated on three important sectors of medical sectors under one single platform.
Open Access
A solution for industrial problem: Predicting the future market price using low amount of data with the help of Time Series Analysis
(North South University, 2019) Istiak Rahman; Zareen Tasnim; Farzeen Ahmed Bashori; Mahdy Rahman Chowdhury; 1530861642; 1511908042; 1510223642
Bangladesh has a lot of potentialities and possibilities as a third world country if it utilizes the blessings of technology properly. With the help of recent technology, different time series analysis models have been developed like ARIMA, ARIMAX, SARIMA, SARIMAX, and even a Facebook developed module called Prophet. Nowadays it is possible to detect the future trend of any business given any type of data. We have applied a similar approach to predict sales for one of the flourishing startups of the country named Rokomari.com. The struggle for any company is to sustain amongst its powerful competitors in its emerging years. It becomes easier to ace over the competitors if the company can have a prior preparation of its upcoming challenges. Our effort was to make the journey smoother so that it can sustain in building a flourishing business amongst its competitors. In order to do so, we have worked with “real world” sparse dataset of the company itself. We were successful in predicting their possible sales for coming years using time series models like SARIMA and Fb Prophet. The paper discuses briefly about the significance and possibilities created due to implementation of our custom build software.
Open Access
A Web and Mobile Application Based Smart Online Health Care System
(North South University, 2019) Md TalatMahmud; Md Shahrear Bin Satter; Md Samiul Basir Rabbi; Mohammad Monirujjaman Khan; 1511653042; 1210128042; 1511703042
This report presents the design and the implementation of a web and mobile application based system where people can connect with a doctor by video calling those who are in online and patients can be prescribed. Besides that people can also store their all medical information through this system. User of this system will also get notification when they need to take medicine. We have developed a web based system and a mobile application named “Online Health Care”. User of this system expresses the strong desire to own an online web and mobile application which is used for their self-management and directly getting advice from the doctor
Open Access
A web application that detects malaria infected red blood cells in real-time
(North South University, 2019-04-30) Fariha Islam; Porsia Tithi; Biswas Nazimuddin Nadim; Dr. Mahdy Rahman Chowdhury; 1511602042; 1420674042; 1410291642
Bangladesh is considered as one of the malaria endemic countries in South Asia hence detecting it at an earlier stage and being able to keep records can save life. The Pathology Assistant is a web app built for Pathologists to be able to create patient profile, upload red blood cell images which is stored in the database and run through a neural network. The neural network can perform binary classification which can tell the pathologist whether the red blood cell is malaria infected or not. This way the pathologist can keep track of the patients condition and upload more images time to time to check the improvements of the patients condition in real time.
Open Access
A Web Service Based on API from where People can get blood in emergency situation
(North South University, 2022-01-01) Ashfi Mehenaz; Sajid Ul Alam; Md Meraj Hasan; Dr. Mohammad Ashrafuzzaman Khan; 1812002042; 1812347042; 1812577042
Our main purpose of this project is to help the people . Basically our project is health oriented and random people would be benefited using this web service named Blood Bank. Before implementing this idea we went through various types of research to check if there were any sort of web service available similar to our idea and we found some web service but we want to implement it in a different pattern so that general people can use it without facing any problem. Suppose, if there is any emergency and anyone needs a necessary group of blood then they can get the necessary information regarding the blood donor and according to their requirement’s they can contact each other through this web service. In the frontend part of our web service we are using html, css, javascript. In the backend part we are using Django. For the documentation and testing we are using Swagger. We are using sqlite for our database and for API’s we are implementing in Restful API. Through the building process of this website, we have to undergo different types of research to make our system even more helpful and easier to access for the general people. We faced several difficulties when we started to implement this because some things were not possible as we intended then tried different ways to solve those problems following comparatively easy procedures. And finally, we are able to make this web service as we desire.
Open Access
A Website and Mobile App Based Intensive Care Unit System
(North-south University, 2018-04-13) Halima Khanom Jolly; Sazzad Hassan Shawon; Junaid Ibna Jafor; Dr. Mohammad Monirujjaman Khan; 1330121042; 1230733042; 1321108042
This report presents the design and the implementation of a website and mobile application based Intensive Care Unit (ICU) system in Bangladesh. In this system any patient and their relatives can find an ICU/CCU/NICU for them with proper information. There is a lack of hospitals and proper ICU facilities in our country. The main purpose of this project is to provide better opportunity for those sufferer patients who can’t find an ICU in their critical time which may sometimes cause a painful death. The system has been designed in such a manner that will help a user as well as a doctor of both rural and urban areas. This system also allows hospitals to share their ICU’s information with the users. We developed this system to help the people of our country who are badly suffering from not having a good ICU system in an easy and affordable way. The system will be accessible from our website and android app via the internet. The report includes content designing, website development and android mobile application development.