• Stress / Workload Assessment Using Multimodal Approach 

  Aina Shireen, 01-132212-005; Kamal Hussain Shah, 01-132212-020; Muhammad Sohail, 01-132212-029 (Computer Engineering, Bahria University Engineering School Islamabad, 2025)

  The growing interest in monitoring cognitive workload has sped up the research in intelligent systems that utilize physiological signals. Mental workload (MWL), if unmanaged, can degrade human performance in safety-critical ...
• Object 3D Reconstruction Using Photogrammetry and AI 

  Arooj Yousaf, 01-132212-010; Hasnain Ayaz, 01-132212-016; Muhammad Hassan Aamir, 01-132212-026 (Computer Engineering, Bahria University Engineering School Islamabad, 2025)

  This thesis focuses on 3D object reconstruction using photogrammetry combined with artificial intelligence (AI), a rapidly evolving field with uses in the gaming industry, e-commerce, digital archiving, interior designing, ...
• Kinesis Pro Standing Wheelchair 

  Ali Uzair, 01-132212-006; Jawad Ali Mirza, 01-132212-019; Muhammad Masharib Khan, 01-132212-028 (Computer Engineering, Bahria University Engineering School Islamabad, 2025)

  Mobility limitations present significant challenges for individuals with physical disabilities, particularly in low- and middle-income countries where access to advanced assistive devices is restricted by high costs and ...
• Brain Tumor Detection and Segmentation MRI Images Using Deep Learning 

  Adan Irshad, 01-132212-046; Hussain Ali Syed, 01-132212-057; Talha Shahzad, 01-132212-059 (Computer Engineering, Bahria University Engineering School Islamabad, 2025)

  Because of the intricate nature of tumor formations and their neurological effects, brain tumor identification and segmentation continue to be significant issues in medical imaging. With an AlexNet-based CNN for classification ...
• Early Diabetes Detection 

  Hina Arif, 01-132212-043; Sana Arif, 01-132212-044 (Computer Engineering, Bahria University Engineering School Islamabad, 2025)

  Diabetes, one of the most prevalent metabolic disorders worldwide, requires early and accurate detection for effective management and prevention of complications. This study focuses on addressing the challenges of timely ...
• Early Fire Detection in Forest Using Image Processing 

  Alishba Riaz, 01-132212-007; Arman Iftikhar, 01-132212-009; Muhammad Taimoor, 01-132212-031 (Computer Engineering, Bahria University Engineering School Islamabad, 2025)

  Early fire detection stays vital because forest fires threaten natural ecosystems as well as local wildlife population and nearby residential areas. Fire detection methods that depend on manual patrolling and satellite ...
• Smart Traffic Light System 

  Abdul Manan, 01-132212-001; Muhammad Abdullah, 01-132212-023; Haris Ajmal, 01-132212-048 (Computer Engineering, Bahria University Engineering School Islamabad, 2025)

  Traffic congestion is a critical challenge in urban environments, particularly in densely populated regions like Pakistan, where static, time-based traffic signals fail to adapt to real-time traffic conditions. These ...
• Mental Health Chatbot With AI 

  Ahmad Faraz, 01-132212-004; Sadeed Ullah, 01-132212-038 (Computer Engineering, Bahria University Engineering School Islamabad, 2025)

  An increasing number of individuals face mental health problems, including anxiety, stress, and depression, because academic, social, and personal demands keep rising. The conventional mental health services encounter ...
• Rapid Rovers 

  Abdullah Saeed, 01-132212-003; Syeda Sania Zehra, 01-132212-040; Anum Noor, 01-132212-047 (Computer Engineering, Bahria University Engineering School Islamabad, 2025)

  Urban mobility faces growing challenges due to increasing traffic congestion, sedentary lifestyles, air pollution, and overreliance on private vehicles. These issues degrade the quality of life, harm public health, and ...
• Deep Learning-Based Cancer Detection in Histopathological Images of Breast Pathology 

  Muhammad Awais, 01-132212-024; Mujtaba Ahmed, 01-132212-034; Muhammad Jalal Haider, 01-132212-050 (Computer Engineering, Bahria University Engineering School Islamabad, 2025)

  On a global scale there are an estimated 2.3 million new cases of breast cancer per year. For improvement of patient outcomes and increase of the survival rate, it is essential to detect early and diagnose accurately. ...
• Solar Panel Maintenance 

  Haiqa Aurangzeb, 01-132212-015; Ayesha Nadeem, 01-132212-042 (Computer Engineering, Bahria University Engineering School Islamabad, 2025)

  The project presented in this final year aims to develop an autonomous solar panel maintenance system that will make the process efficient and reliable through the integration of drone technology, deep learning, and advanced ...
• AI-Driven Wheat Rust Detection 

  Jahanzaib Fareed, 01-132212-018; Suleman Sohail Sarwar, 01-132212-039 (Computer Engineering, Bahria University Engineering School Islamabad, 2025)

  Wheat is a staple crop in Pakistan, contributing significantly to national food security and the agricultural economy. It provides nearly 60% of the daily caloric intake for the population and supports the livelihoods of ...
• Smart Surveillance Drone Using Micro Wave Sensor Technology 

  Abdul Saboor Khan, 01-132212-002; Muhammad Ibtisam Khan, 01-132202-027 (Computer Engineering, Bahria University Engineering School Islamabad, 2025)

  This project presents the development of a Smart Surveillance Drone System utilizing mmWave sensor technology for the real-time detection of humans, animals, and birds in diverse environmental conditions. Traditional ...
• Arm Motion Replicator Using Electromyography (EMG) 

  Daniyal Shaukat Chaudhary, 01-132202-009; Aliza Khan, 01-132202-047; Ahsan Hayat Khan, 01-132182-004 (Computer Engineering, Bahria University Engineering School Islamabad, 2024)

  Paralysis affecting only one limb, known as monoplegia, is frequently caused by brain injuries, strokes, or other neurological illnesses. Since monoplegia patients have severe difficulties performing daily tasks, assistive ...
• Automated Lungs Disease Detection Using Hybrid Deep Learning Technique 

  Kashif Shabbir, 01-132202-049; Muhammad Sanwal Noor, 01-132202-031 (Computer Engineering, Bahria University Engineering School Islamabad, 2024)

  This paper presents a current state of the art approach to the early detection and classification of lung diseases using medical images based on the use of deep learning models – Convolutional Neural Networks (CNNs). ...
• Artificial Intelligence Based Baggage Scanner System 

  Zubair Ahmed, 01-132202-045; Ayesha Noor, 01-132202-008 (Computer Engineering, Bahria University Engineering School Islamabad, 2024)

  The primary objective of an artifcial intelligence-based baggage scanning system is to enhance safety and security in complex environments by effectively detecting contraband items, a crucial measure for public safety. The ...
• Real-Time Driving Assistant using Deep Learning & Object Tracking 

  Muhammad Mahed Ahsan, 01-132202-051; Raffeain Khalil, 01-132202-037 (Computer Engineering, Bahria University Engineering School Islamabad, 2024)

  In this final year design project, we present a real-time driving assistant system that leverages deep learning and object tracking algorithms to provide assistance to the driver of the host vehicle and make our roads ...
• Smart Security System Based On Intrusion And Anomaly Detection 

  Hamza Ullah Khan, 01-132192-012; Muhammad Maaz, 01-132202-028; Ammar Ali Khan, 01-132202-005 (Computer Engineering, Bahria University Engineering School Islamabad, 2024)

  The prevalence of security threats necessitates innovative solutions for effective surveillance and threat detection. In response, we introduce our final year project, the ’Smart Security System Based on Intrusion and Anomaly ...
• AI-Driven Strategies For Detecting Fake News 

  Muhammad Usman Khan, 01-132202-033; Muhammad Uzair Zia, 01-132202-034 (Computer Engineering, Bahria University Engineering School Islamabad, 2024)

  The propagation of disinformation online has become a major factor in undermining the trustworthiness of modern data circulation processes. The main purpose of this fnal year project is to fll this gap by creating such a ...
• Tweet Sense: Decoding Sentiments In Tweets Through NLP and Deep Learning 

  Humaima Anwar, 01-132202-013; Abdul Rehman Akram, 01-132202-002 (Computer Engineering, Bahria University Engineering School Islamabad, 2024)

  This work aims to classify tweets into multiple topics and predict emotions and sentiments from tweets by using techniques like Natural Language Processing (NLP), Transformers, Deep Learning, and Machine Learning based on ...

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