http://hdl.handle.net/123456789/10316 2026-07-16T20:18:42Z http://hdl.handle.net/123456789/21249 Antenna/Radar Positioning System for Enhanced Military Communication Asma Kausar, 01-133222-011; Aneela Kousar, 01-133222-009 Reliable communication is a fundamental requirement in modern military operations, particularly in dynamic and unpredictable battlefeld environments where mobility, obstruction, and environmental interference severely degrade signal quality. Conventional static antenna systems are often unable to maintain optimal alignment under such conditions, leading to reduced signal strength, unstable connectivity, and limited operational effectiveness. To address these challenges, this project presents the design and implementation of an Adaptive Antenna Positioning System based on Infrared (IR) sensing for enhanced communication reliability. The proposed system employs a two-axis motorized antenna mount capable of automatic azimuth and elevation control. Instead of relying on RF signal strength estimation, the system utilizes Infrared (IR) transmitter–receiver modules to determine directional alignment with the signal source. The IR-based sensing mechanism continuously detects the intensity and directionality of incoming infrared signals, enabling the system to identify the optimal orientation for maximum alignment accuracy. A microcontroller-based control unit processes real-time IR sensor data and dynamically adjusts the antenna position using high-precision stepper motors, ensuring smooth and accurate tracking performance. To evaluate system performance under controlled dynamic conditions, a custom-built moving IR signal source mechanism is developed to simulate mobility scenarios. The hardware architecture integrates IR sensing modules, an Arduino-based control system, motor driver circuits, and a wireless monitoring interface for real-time observation and testing. This integrated design allows effective validation of tracking behavior in both static and dynamic environments. Experimental results demonstrate that the proposed IR-based system achieves improved directional accuracy, stable alignment, and reduced signal deviation compared to conventional fxed antenna setups. The system shows reliable tracking capability under simulated movement conditions, confirming its suitability for controlled short-range adaptive communication applications. Overall, the project contributes to the development of intelligent antenna positioning systems by integrating IR sensing technology with embedded control and electromechanical actuation. The resulting framework offers a cost-effective, lightweight, and scalable solution that can serve as a foundation for further advancements in adaptive communication and tracking systems. Supervised by Dr. Nadia Sultan 2026-01-01T00:00:00Z http://hdl.handle.net/123456789/21250 AI Powered Dynamic Control System and Efficiency Optimization for Steam Turbine Rawal Khan, 01-133222-064; Muhammad Sufian, 01-133222-056 Steam turbines are the key elements of thermal power plants. Their efcient functioning is vital for optimizing power production and minimizing operational expenses. But the turbine performance is continuously changing with changing thermodynamic conditions namely main steam pressure, main steam temperature, cold reheat pressure and cold reheat temperature. Traditional industrial control systems such as PID and DCS guarantee the stability of operations, but they are not designed for intelligent optimization of efciency of the operations in the dynamic operating environment. In this work, a physics aware reinforcement learning based supervisory optimization framework is presented for HP steam turbine efciency improvement. The proposed system is a closed loop supervisory architecture combining thermodynamic efciency estimation, reinforcement learning optimization, recommendation evaluation and real-time dashboard visualization. The HP turbine efciency is calculated by thermodynamic relations based on the change in enthalpy of the steam and the calculated efciency is checked with the dataset efciency values for physical consistency and reliability. Three reinforcement learning algorithms (PPO, SAC, and TD3) are trained to provide safe operational recommendations via controlled modifcations in selected thermodynamic operating parameters. Prior to presenting recommendations to the operator, the expected turbine efciency is re-evaluated after each recommended action using the physics-based effciency model. The reinforcement learning models are also compared with No Action and Random Action baseline strategies in terms of efciency improvement and statistical evaluation metrics. A real-time supervisory dashboard is also developed to visualize the current HP turbine efficiency, recommended operational changes, expected optimized efciency, and efciency improvement. The proposed framework also enables real-time data ingestion from an external system that allows live monitoring and recommendation generation in dynamic operating conditions. The system developed serves as a supervisory advisory layer, not interfering directly with the existing industrial PID/DCS infrastructure. The proposed framework demonstrates the potential of the combination of thermodynamic modeling and reinforcement learning to develop intelligent, adaptive, and safe supervisory optimization systems for steam turbine efficiency improvement in modern thermal power plants. Supervised by Dr. Nadia Sultan 2026-01-01T00:00:00Z http://hdl.handle.net/123456789/21253 Battery Pack Cell Balancing and Diagnosis Device for Electric Bikes Muhammad Abdullah, 01-133222-042; Hassan Waheed, 01-133222-026 Electric bikes commonly utilize Lithium Iron Phosphate (LiFePO4) battery packs composed of multiple cells connected in series to achieve high voltage requirements, where the overall performance, safety, and lifespan depend heavily on the equilibrium of individual cells. A single weak or degraded cell can significantly reduce the overall capacity and reliability of the entire pack, yet professional cell-level diagnostic equipment remains expensive and inaccessible to local workshops and general EV users in Pakistan. This project presents a low-cost, discrete component-based Passive Battery Cell Balancing and Diagnostic Device designed specifically for a battery configuration. Unlike active balancing systems that require complex energy transfer components, this system utilizes a switched shunt resistor technique to dissipate excess energy from higher-voltage cells through power resistors, ensuring all cells reach a uniform state of charge. The device performs comprehensive diagnostics by monitoring real-time voltage and status through an analog control logic powered by NE555 timers and Darlington pair drivers. By enabling precise detection and balancing of cells through manual threshold tuning, the proposed solution prevents unnecessary full-pack replacements, making EV maintenance more economical and sustainable. Portable, user-friendly, and locally manufacturable using readily available electronic components, this device offers an affordable alternative to industrial-grade analyzers and directly supports the growing electric vehicle ecosystem. Supervised by Dr. Asad Waqar 2026-01-01T00:00:00Z http://hdl.handle.net/123456789/21251 Modular Autonomous Industrial System for Internal Transport M Ayaan E Rasul, 01-133222-046; Attaullah, 01-133222-012 Material handling is really important in factories. It helps get work done quickly. Robots like Automated Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs) are often used for this. Many of these robots use expensive technology. That makes them hard to use in projects or school work. This project is about making an cheap robot that can move things around. The robot uses an Arduino microcontroller. It also uses RFID technology to know where it is. Infrared sensors help the robot avoid hitting things. An ESP32 module lets the robot talk to devices wirelessly. The robot can even be controlled by hand. It has a lifting part that lets it pick up and put down things. The robot can work in two ways: manually and on its own. This makes it easy to test and use. The design was broken down into parts like sensing, control and movement. This made it easier to build and fx. Most testing was done with the software. The results showed that the robot responds fast to commands. Communication, through Bluetooth works well. The robot was not tested in a factory. It should work well in controlled areas. Overall this project shows that a working robot can be made with different parts by implementing different ideas. It would be a great robot that can work efciently with sensors and navigation. The robot can move things around on its own. Supervised by Dr. Faheem Haroon 2026-01-01T00:00:00Z