Thesis & Design Report (Bachelor of Science in Electrical and Electronic Engineering)

Permanent URI for this collectionhttps://hdl.handle.net/10361/690

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A quadruped robot for real-time inspection and responsive operations
(BRAC University, 2026-05) Hossain, Md. Shahariar; Abrar, Rafin Md; Shadid Al Akib; Ahmed, Tazwar; Rahman, Touhidur; Alam, Shahed; Oni, Atib Mohammad; Department of Electrical and Electronic Engineering
Industrial inspection in hazardous environments such as chemical plants, oil and gas facilities, power systems, and nuclear sites poses significant risks to human workers due to exposure to toxic gases, extreme temperatures, high voltage, and confined spaces. To address these challenges, this project presents the design and implementation of a quadrupedal robot capable of performing real-time inspection and responsive operations with minimal human intervention. The robot integrates a multi-sensor inspection framework for detecting structural and operational abnormalities, with particular focus on identifying surface cracks, microcracks or other early signs of equipment degradation. The system architecture combines a legged mobility platform, onboard computing unit, wireless communication module, and sensor suite including camera, ultrasonic, and IR-based sensing components. These subsystems enable the robot to collect and transmit real-time inspection data to operators for rapid monitoring and decision-making. In addition to routine inspection, the robot is also equipped with a manipulation mechanism for limited emergency operations such as operating switches or mechanical levers when direct human access is not feasible. The quadruped structure provides greater adaptability than conventional wheeled or tracked platforms in stairs, narrow passages, and uneven surfaces, making it more suitable for industrial inspection scenarios. This study addresses key limitations in existing inspection systems, including limited autonomy, infrastructure dependency, and high operational costs, by proposing a modular, cost-effective, and energy-efficient design. Experimental analysis demonstrates that the system can perform reliable inspections while reducing human exposure to hazardous environments. By enabling real-time crack and microcrack detection alongside general hazard inspection, the system supports predictive maintenance, reduces unplanned downtime, and improves worker safety. Overall, this work contributes a modular and practical robotic solution aligned with the growing industrial demand for intelligent, autonomous, and inspection-centric systems.
Smart whiteboard management system
(BRAC University, 2025-10) Raiyan, Ekram Ahmed; Mercy Al Hossain; Mushfiq Us Salehin; Manjur, Md.; Rasheduzzaman, Mirza; Rahman, Md. Mosaddequr; Department of Electrical and Electronic Engineering
Our Smart Whiteboard Management System transforms the traditional classroom into a modern, interactive space. It's a portable, electric-powered system that cleans the board automatically using 99.5% of the surface area. A 5MP camera captures everything written--notes, equations, and diagrams--and converts them into editable LaTeX PDFs and shares them through a Flask-based web portal. The system also includes an AI chatbot tutor that provides instant help and reduces the need for human assistants by up to 50%. Using reed sensors and ESP32 microcontrollers, it selectively cleans only the required areas, making the process efficient and sustainable. With excellent digitization accuracy, it reduces paper waste and supports eco-friendly learning.
Early stage ML based non invasive breast cancer screening
(BRAC University, 2026-01) Khan, Mohammad Fasiul Abedin; Nowshad, Farrdin; Nahean, Abrar Maksud; Mridul, MD. Abu Anas; Jahan, Nahid Akhter; Rasheduzzaman, Mirza; Rahman, Md. Mosaddequr; Department of Electrical and Electronic Engineering
Early breast cancer detection in low- and middle-income countries is limited by high screening costs, lack of infrastructure, and dependence on specialized facilities. This project presents a portable, low-cost, non-invasive AI-assisted breast cancer screening system using infrared thermography and machine learning, designed for deployment in resource-constrained settings. The system captures multi-view thermal images and analyzes temperature asymmetry and abnormal heat patterns using a convolutional neural network deployed on an embedded edge-computing platform. A structured engineering approach was followed, including evaluation of multiple design alternatives, optimization, sustainability, economic analysis, ethical compliance, and project management. The system provides an output, Benign or Malignant, to support clinical decision-making without replacing diagnostic procedures. The results demonstrate technical feasibility, affordability, and sustainability, establishing a strong foundation for IRB-guided clinical validation and scalable community-level screening.
Design and implementation of residential building management system
(BRAC University, 2025-10) Khandaker, Md. Takky Hasan; Kabir, Mohammad Ibtehaz; Chowdhury, Fidaul Mowla; Siddique, Mohammad Samir; Hossain, A K M Shakhawat; Rahman, Md. Mosaddequr; Rasheduzzaman, Mirza; Rahman, Md. Mosaddequr; Department of Electrical and Electronic Engineering
This project presents the design and implementation of a Residential Building Management System (BMS) aimed at improving energy efficiency, safety and comfort in modern homes. The proposed system integrates IoT-based automation using the ESP8266 NodeMCU microcontroller and various sensors to monitor temperature, humidity, motion, fire and gas leakage. It allows real-time supervision and remote operation of lighting, HVAC, safety and security systems and can be controlled through the Blynk IoT platform. Centralized BMS was optimized for cost, performance and scalability in comparison to all three design approaches Distributed, Centralized and Hybrid. Our testing confirmed reliable communication, fast response and 15-25% reduction in energy consumption. The system minimizes power waste, ensures safety and keeps cost down that supports sustainability goals. In conclusion, the system shows an effective, scalable and ethical engineering solution for smart, sustainable residential environments in Bangladesh and similar urban areas.
Autonomous waste collecting device for Sugandha point of Cox's bazar sea beach
(BRAC University, 2026) Uddin, Mohammad Riaz; Sreoshi, Sabrina Afrin; Hossain, Md. Shariar; Musabbi, Abdullah Al; Rahman, Dr. Mosaddequr; Islam, Mohaimenul; Bobby, Aldrin Nippon; Department of Electrical and Electronic Engineering
The issue of waste pollution of the coastal territories is also increasingly becoming a rising problem in Bangladesh, especially at the most popular sites like the Sugandha Point of the Cox's Bazar Sea Beach where tons of plastic and solid waste are becoming a daily occurrence and current means of clean-up is based mostly on manual labor. In this project, the proposal is to design and develop a cheap yet fully autonomous waste collector with the creation of a particular device designed to perform effectively in sandy and salty beaches. The proposed system will include an autonomous rover to identify typical wastes along with AI based computer vision, GPS based covering, ultrasonic and infrared sensors to avoid obstacles and a mechanical mechanism of waste collection in the form of a shovel. Once the waste is detected with the help of a camera and trained machine learning model, the rover is capable of autonomously picking a piece of garbage and placing it into an on-board container, which is emptied at a designated dumping point once full. Various design solutions have been considered, such as a robotic arm and a conveyor belt system, and the shovel mechanism has been chosen because of the simplicity of the mechanism, its lasting capacity, energy- efficiency, and its application in non-even sandy areas. There are experimental findings to prove that the device can be effectively used to clean a predetermined beach area with reducing the cost of operation and less human intervention. The above system can serve as a viable solution to sustainable beach cleaning, and it can place autonomous robotics in an environmentally-sustainable context, especially in developing nations.
IOT based centralized net meter monitoring and management system for grid connected solar PV
(BRAC University, 2026) Mujahid, Md. Mustaq; Zuboraz, Md. Zubayet Hossain; Iqtiad, Ajmain; Hasan, Md. Shakil; Khan, Dr. Shahidul Islam; Rasheduzzaman, Dr. Mirza; Rahman, Md. Mosaddequr; Department of Electrical and Electronic Engineering
The integration of rooftop solar photovoltaic (PV) systems through net metering has significant potential to improve energy sustainability in Bangladesh; however, the lack of intelligent monitoring and control often leads to inefficient utilization of installed systems. This project presents the design and hardware implementation of an IoT-based centralized net meter monitoring and management system for a grid-connected solar PV battery setup. The ESP32 microcontroller is a component of the system that measures real-time electrical parameters (voltage, current, power, energy import/export, and battery state-of-charge). Control logic based on relays is used to have automatic control over grid import, grid export and battery operation. The visualization of system data is provided with an IoT dashboard to give a clear understanding of net metering behavior. A hardware prototype was created and tested in order to confirm the system performance. The feasibility was also assessed by carrying out an economic analysis based on cost breakdown, payback period and sensitivity analysis. The outcomes showcase a better visibility of energy, efficiency in operations and realistic use as far as rooftop solar systems are concerned.
Design and implementation of a weather station for flood-prone agricultural lands
(BRAC University, 2026-01) Mohiuddin, Akif; Mojumder, Arfanul Hoq; Inshaniate, Brinto; Sakib, Tanjil Abrar; Rahman, Md. Mosadeqqur; Islam, Mohaimenul; Bobby, Aldrin Nippon; Department of Electrical and Electronic Engineering
One of the frequent natural hazards in Bangladesh is flooding which has a devastating impact on the agricultural productivity especially in the low-lying and rural areas. The absence of localized, real-time weather surveillance and the early notification of floods frequently causes a lot of crop loss, economic setbacks, and a decrease in livelihood of the agricultural people. This project will constitute the design and deployment of a low-cost, IoT based weather station that will be specifically designed to work on flood prone agricultural land. The system, proposed, incorporates the various environmental sensors to measure the significant parameters of rainfall, temperature, humidity, soil moisture, wind speed, atmospheric pressure, and water level in real-time. To process, store, and analyze data, data is sent via long-range and low-power LoRa communication network to a cloud-based platform. The prediction model application is based on machine learning to analyze real-time and historical data and estimate flood risks to provide early warnings. The system runs off a solar-powered energy management unit which has battery backup thus making it operate continuously in off-grid and remote regions. The system sends real-time alerts via SMS and a user-friendly web dashboard to the farmers. Experimental analysis proves to have credible data transmission, reasonable sensor accuracy, power-saving, and useful flood risk forecasting. The proposed solution provides a cost-effective, energy-efficient, and scalable solution to enhance flood preparedness, loss of crops, and sustainable agricultural practices in flood prone areas of Bangladesh.
TorqueSAM: unsupervised kidney CT analysis with localization and SAM-integrated torque clustering segmentation
(BRAC University, 2026-02) Rahat, Shahzalal Khan; Apurbo, Shah Miran; Pranty, Anika Tazin; Yesmin, Mahejabin; Biplob, Md. Asif Hasan; Alam, Md. Golam Rabiul; Department of Computer Science and Engineering
Chronic kidney disease is a growing public health hazard that often leads to permanent renal system failure if not diagnosed and treated by experts within a treatable time interval. In addition to that, the shortage of expert nephrologists in unprivileged areas slows down the early detection and prevention. However, AI driven solutions can play a vital role in ensuring early detection and prevention despite the shortage of experts in many cases. But most existing AI driven automated renal disease detection systems heavily rely on manually annotated data, which still needs the experts’ intervention to detect any chronic renal illness. To address this issue, this study proposes and tests a fully unsupervised method to detect one critical chronic renal disease: Renal stone, often interpreted as a stone that does not rely on any annotated data. In this regard, our proposed method, namely TorqueSAM, introduces a different approach to work with modern detection and segmentation models, along with a classification module to detect any Renal Stone without relying on any ground truth labels. Our approach is tested on a dataset of 6,454 axial and coronal CT scan images. Our study focuses on one alarming illness that is highly dominant and associated with long-term kidney failure. TorqueSAM shows that the unsupervised image segmentation and classification surpass the classical supervised approaches significantly in terms of reducing the annotation overhead, time, and resources. For renal stone, TorqueSAM showed dice scores of 0.5767, IoU of 0.4183, precision of 0.9296, recall of 0.4655, accuracy of 0.9992, and specificity of 0.9998. However, the classification results of the clustering is found to be 0.8232 and 0.8472 for ARI and NMI, respectively. Despite having some limitations in the segmentation, this research shows the potential to outperform the classical supervised techniques, prioritizing the optimization of the region of interest (ROI) to enhance the predictive accuracy while reducing annotation overhead, which allows TorqueSAM to be a scalable solution to mitigate the sufferings of renal stone detection.
Design and implementation of an indoor hydroponic system for enhanced crop production
(BRAC University, 2026) Tuli, Mahabuba Akter; Hasan, Md. Samir; Islam, Md. Sazzadul; Shakib, Sadman; Bhuian, Mohammed Belal Hossain; Islam, Md. Mahmudul; Ahmed, Sabbir; Department of Electrical and Electronic Engineering
Urban agriculture in densely populated regions, which faces severe constraints due to limited arable land, soil degradation, and water scarcity, requires efficient and space-saving cultivation solutions. This project introduces an automated Indoor Vertical Hydroponic System specifically designed for space-constrained urban environments. By incorporating IoT sensors that monitor TDS, turbidity, water level, temperature, and humidity, the system allows for precise environmental tracking to automate nutrient delivery and optimize crop health. The system operates largely independently of outdoor weather by utilizing spectrum-controlled LED lighting and a camera module for real-time visual monitoring, ensuring year-round production. The use of automated water and oxygen pumps guarantees efficient resource circulation, significantly minimizing water waste compared to traditional soil-based farming. Moreover, the system is designed as a scalable, ready-made agricultural product, providing a user-friendly solution that maximizes yield per square foot. By addressing both space constraints and resource efficiency, this project not only improves the competitiveness of the agricultural sector but also promotes sustainable food security in Bangladesh's land-scarce markets.
Psychmatrix: empowering users through advanced interactive control
(BRAC University, 2025-10) Rifat Bin Reza; Ahmed, Shadman; Afrin, Barida; Mrida, Imtiaj Saiem; Khan, Shahidul Islam; Zunaed, Mohammad; Chowdhury, Saad Mahbub; Department of Electrical and Electronic Engineering
This project introduces the concept of PsychMatrix, a very simple yet effective and affordable assistive technology for controlling home appliances using hand gestures without touching the appliance. The system makes use of wearable gloves embedded with flex sensors to obtain information related to the bending of the fingers and muscles. These signals are processed by ESP32 microcontroller which sends commands to a cloud-based firebase realtime database via Wifi . These commands are then sent to a second ESP32 unit which works as a home controller by turning appliances on and off using relays. An assistant mobile application gives the system real-time monitoring and user interface. PsychMatrix is a control board with a safe, responsive design (with a measured end-to-end Latency of under 500ms) arranged to benefit the elderly and those with disabilities, as well as high-voltage workers, which has an interaction recognition accuracy rate of 98%. The system proves that with low-cost off-the-shelf components, a well-built, cloud-connected assistive technology can be enacted to ensure a higher degree of independence and safety.
MediTrack: a smart medication adherence system using OCR, IoT, and cloud-based centralized health database
(BRAC University, 2026-01) Alam, Sayed Shahriar; Rehman, Akib; Riya, Kazi Shanzid Hossain; Saha, Anurag; Saha, Rony Kumer; Das, Bristy; Muhiuddin, Md. Muhiul Islam; Department of Electrical and Electronic Engineering
Medication non-adherence is a critical healthcare challenge, particularly among elderly and chronically ill patients in developing countries where limited healthcare infrastructure, fragmented medical records, and lack of caregiver support increase the risk of missed or incorrect doses. This paper presents MediTrack, an integrated smart medication management system designed to improve medication adherence through automated dispensing, sensor-based intake verification, and cloud-enabled prescription management. The proposed system combines optical character recognition (OCR) and natural language processing to digitize handwritten and printed prescriptions in both Bangla and English, enabling automatic schedule generation and centralized electronic health record storage. A microcontroller-driven dispensing unit utilizes stepper motors for precise dosage delivery, while infrared sensors and load-cell–based weight measurement verify pill dispensing and patient intake in real time. To address missed doses, a multi-level alert mechanism is implemented, incorporating audible alerts, visual notifications, and a mobility-enabled line-following robot that physically delivers medication to patients when necessary. Environmental monitoring ensures proper medicine storage by controlling temperature and humidity. Experimental validation demonstrates reliable dispensing accuracy, high intake detection performance, and effective missed-dose handling, while maintaining low power consumption and affordability. The system is designed to operate under limited internet connectivity and supports scalable deployment in home-care and institutional settings. MediTrack offers a cost-effective, localized, and scalable solution that enhances patient safety, reduces caregiver burden, and supports the transition toward digital healthcare systems in resource-constrained environments.
Development of a smart system to translate sign language for deaf and mute individuals
(BRAC University, 2025-05) Khan, Raheela Rubaiyat; Billah, Modassir; Rounok, MD. Shahriar Rahman; Hossain, MD. Forhad; Rahman, Touhidur; Alam, Shahed; Oni, Atib Mohammad; Department of Electrical and Electronic Engineering
Communication is another major barrier that the deaf and the mutes are faced with in mostly a vocal society. More than 13 million individuals in Bangladesh experience some hearing impairments and impediments on speech. They use sign language thus they cannot communicate well most of the time because the one being signed can not understand sign language. The idea of the proposed project is to design a smart wearable device that can be used to translate sign language into speech by hard of hearing persons and actors with impaired voices. The system involves flex sensors, a 6 axis accelerometer-gyro which is mounted into a glove in order to pick up the hand motions and hand postures. The data is processed in the form of sensor data transmitted to a microprocessing unit that has a machine learning ready with such information. In case such a person is a deaf mute, he/she will move his/her hands and our model will identify it and provide us with the corresponding sign (word) by means of a speaker. This solution addresses the shortfalls of the earlier systems since it allows translation in real time regardless of the environmental situation. The solution also improves the accessibility to communication, social inclusion, and safety among the users especially in emergencies and the day-to-day situations.
Hydropace: advancing conventional pacemakers by implementing hydrogel-based electrodes and cardiac health monitoring system
(BRAC University, 2025-09) Sadath, Sheikh Md. Nazmus; Alam, Rafiul; Hossen, Md. Emran; Mohammad, Istiaq; Mahmood, Sk. Zayed; Azad, AKM Abdul Malek; Rafi, Md. Rafiqul Islam; Avash, Ihteyaz Aqaeed; Department of Electrical and Electronic Engineering
The rising prevalence of cardiac disorders, coupled with the limitations of conventional pacemakers such as rigidity, short lifespan, repeated surgical interventions and risk of complications, have created the need for innovative biomedical devices. This research work examines the feasibility of improving the functionalities of conventional pacemakers by replacing certain traditional methods with novel solutions. This comprises the implementations of hydrogel-based electrodes and sensor heads that integrate flexibility, biocompatibility, and multifunctional sensing capabilities. The proposed design incorporates hydrogel as a soft and conductive medium to enable seamless integration with cardiac tissue, while supporting embedded sensor heads made with hydrogel for ECG, temperature, and biochemical/biomarker level monitoring. The HydroPace system also includes energy harvesting and wireless communication modules to enhance device longevity and minimize the need for invasive replacements. The primary objective of this study is to design and prototype a system that not only maintains effective pacing for patients with arrhythmia but also ensures improved diagnostic accuracy and enhanced patient safety. By addressing both the engineering and biomedical constraints, this research aims to contribute to the advancement of sustainable, accessible, and next-generation cardiac care technologies.
An autonomous rover for efficient waste segregation and collection in urban parks and fields
(BRAC University, 2025-09) Khan, Nafim Karim; Hassan, Farhad; Huq, Rubaya; Khan, Shah Rasul; Bhuian, Mohammed Belal Hossain; Islam, Md. Mahmudul; Ahmed, Sabbir; Department of Electrical and Electronic Engineering
This project presents the design and implementation of an autonomous rover system for efficient waste segregation and collection in urban parks and fields. Bangladesh faces significant challenges in solid waste management due to rapid urbanization and limited infrastructure which results in environmental and health hazards. To address this, we developed a rover equipped with a Raspberry Pi 5, Pi camera and a 4-DOF robotic arm. A YOLOv8n machine learning model enables real-time waste detection and classification into biodegradable and non-biodegradable categories with over 84% accuracy from practical scenarios. The rover follows a zigzag navigation path where it autonomously detects and picks up the waste which is then deposited into a compartmentalized bin that rotates through a servo. Extensive simulations and tests were conducted which validated its efficiency and achieved complete field coverage within 20 minutes while maintaining sustainable power usage. This solution demonstrates a scalable, cost-effective, and eco-friendly approach to urban waste management which promotes cleaner environments and improved public health.
Smart gas leakage detection and management system
(BRAC University, 2025-09) Jannat, Raiyan; Begum, Fatema; Khan, Mansia Samrana; Rahman, Fardeen; Hossain, Md Golam Sorwar; Kabir, Md. Saif; Jalal, Junaid; Department of Electrical and Electronic Engineering
Liquefied Petroleum Gas (LPG) is widely used in Bangladeshi households, but its high flammability makes LPG leakage a critical safety concern. Very few detection systems exist, and the conventional ones are often expensive, grid-dependent and limited to alarms. This project presents a solar-powered smart gas leakage detection and management system for residential kitchens. The prototype integrates dual gas sensors (MQ-2, MQ-6), Arduino Uno controllers, GSM-based remote alert, Bluetooth-enabled subsystem communication, automatic ventilation through an exhaust fan and linear actuator and a solenoid valve to cut off gas supply. The batteries of the entire system are solar-charged and ensure continued operation with no human intervention. Testing under simulated leakage conditions confirmed accurate detection at a 2000 ppm threshold, rapid activation of safety measures, and stable performance for up to three hours on solar backup. Therefore, the system demonstrates a cost-effective, sustainable solution to improve household gas safety.
AI-powered object sorting mechanical arm with easy replaceability
(BRAC University, 2025-09) Mahbub, Imon; Mesbah, K. M. Fatin; Zim, Ahmed Zoha; Kabir, Rayhan; Huda, A. S. Nazmul; Taz, Nahid Hossain; Shams, Sharif Mohammad; Department of Electrical and Electronic Engineering
This project presents the design and implementation of an AI-powered object sorting mechanical arm that integrates decision-making capabilities of AI to enhance flexibility and efficiency in industrial automation. The proposed system eliminates the need for manual reprogramming by employing a large language model (LLM), Gemini 2.0, for object recognition and decision-making. Equipped with a 4-DOF robotic arm, high-resolution cameras, and a gripper mechanism, the system is capable of identifying, classifying, and placing objects with high accuracy. The approach demonstrates improvements in adaptability, reduced setup time, and sustainable applicability across various sectors, aligning with the needs of modern industry and society.
Design and implementation of a user-level, real-time smart waste management system for university
(BRAC University, 2025-09) Hamin-Al-Araf, Md.; Siddique, Yasir Anaf; Islam, Afrida; Patwary, Ikram; Rahman, Mosaddequr; Islam, Mohaimenul; Bobby, Aldrin Nippon; Department of Electrical and Electronic Engineering
Waste management is one of the most serious issues of contemporary campuses and urban areas that may lead to an unsanitary environment, resource wastage and environmental damage. This project introduces the design and implementation of an intelligent waste management system, which combines the use of IoT sensors, machine learning, and cloud-based monitoring. Two design dimensions were taken into account, a low-cost sensor-based design and a machine learning design with a Raspberry Pi and YOLOv8n classifier. The latter was found to be better by comparison, with 92% classification accuracy, consistent hazard detection, and real-time monitoring. Actuator control and power consumption were verified through MATLAB and Proteus simulations, and a physical prototype tested proved to be effective in segregation and optimal collection. The system minimizes the number of trips to collection, promotes recycling and allows responsible user behavior by a reward system. In keeping with the global sustainability objectives, the project will provide a replicable and scalable model of cleaner, smarter, and more sustainable communities.
Intelligent robot communication systems for network switching in indoor industrial environments
(BRAC University, 2025-06) Mukit, Abdul; Tahseen, Mahira; Khan, Md. Omar Hossain; Saha, Rony Kumer; Das, Bristy; Muhiuddin, Md. Muhiul Islam; Department of Electrical and Electronic Engineering
From 2008 to 2022, Bangladesh’s telephone bandwidth density increased by 71.35%, with projections indicating a further 44% rise in the next 11 years [1][2]. This growth, coupled with the rising demand for efficient bandwidth and signal utilization, has drawn the attention of researchers, academics, and industry leaders. In the current telecommunications landscape, Bangladesh hosts 3 government-owned, 4 franchise-based, and 2 emerging network service providers. This research focuses on the design and analysis of a robust system capable of Dynamic Network Switching and Seamless Connectivity Protocols to address challenges such as limited resources, high constraints, and fluctuating network performance. The project’s industrial application based on dual Wi-Fi adapter centers on improving communication reliability in resource-constrained environments.
Design and implementation of an affordable braille reader for converting PDF text into refreshable braille output
(BRAC University, 2026) Rahman, Md. Hafizur; Mostofa, Mubtasik Nafe; Alvee, Nafis Ahmed; Sheikh, Mohammad Asifur Rahman; Chowdhury, Shabab Scimitar; Rahman, Touhidur; Rasheduzzaman, Mirza; Rahman, Mossaddequr; Department of Electrical and Electronic Engineering
This project demonstrates the development and the design process of an Electronic Braille Module Display which is affordable and user friendly. Additionally, it also broadens the accessibility for the visually impaired people. The processing unit, which is Raspberry Pi in our case, controls solenoid for Braille output. It works real time by translating digital texts (PDFs) into braille output. The process of hardware design emphasises on low-cost ensuring reliability and suitable for the education for the visually impaired people. The validation of functionality confirms the fast refreshing, tactile feedback. This project not only addressed the high priced barrier of existing braille modules but also promotes the braille literacy among the visually impaired people across the globe.
Energy efficient human hauler with enhanced safety for urban mobility
(BRAC University, 2026-01) Shahria, MD; Hossain, Sabab; Saiyed, MD Takrim; Ahsan, MD Fardin; Bhuian, Mohammed Belal Hossain; Islam, Md. Mahmudul; Ahmed, Sabbir; Department of Electrical and Electronic Engineering
Electric rickshaws play a vital role in urban transportation in Bangladesh, but their growing use has increased pressure on the national power grid and raised concerns about energy efficiency and sustainability. This project presents the design and implementation of a hybrid electric rickshaw system that combines human pedaling with controlled motor assistance, solar energy harvesting, and regenerative braking. The Pedal Assist Sensor (PAS) to sense the level of peddling is attached, and an Arduino-based motor controller assists with a maximum of 80 percent of the effort of the rider with a safe maximum speed. The use of solar panels and a regenerative system allows one to recharge a battery during work and become less dependent on grid electricity. The mathematical modeling, simulation, and hardware testing prove that the proposed system reduces battery usage, increases the driving range, and has more energy efficiency. The implemented model is cheap, safe and can be used in the real world, hence is a viable solution to the transportation problem in urban Bangladesh.

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