This project designs a robot that pollinates greenhouse plants automatically. Using cameras and artificial intelligence, the robot sees flowers and stems, then gently grasps and vibrates them to release pollen—just like bees do. Soft rubber grippers prevent plant damage, while smart planning finds the safest way to reach each flower. With a 92.5% success rate, this technology reduces labor costs, increases crop yields, and helps farmers grow food more sustainably in controlled environments. 

This project investigates the development of an intelligent wearable system for real-time drowning detection using AI-based heart rate and motion analysis. The system integrates physiological and movement sensors with wireless communication to transmit emergency alerts and activate a drone-assisted rescue response. The project aims to enhance beach safety, reduce emergency response times, and improve the effectiveness of aquatic rescue operations through advanced sensing and autonomous technologies.

This project focuses on the design, fabrication, and performance evaluation of a mobile robotic platform for the inspection of underground wastewater pipelines. The system incorporates mobility mechanisms, onboard sensing technologies, and real-time monitoring capabilities to detect structural defects, blockages, and maintenance requirements in pipeline networks. The project aims to improve inspection efficiency, reduce human exposure to hazardous environments, and support predictive maintenance strategies for wastewater infrastructure management.

This project investigates the dynamic behaviour and optimization of a hybrid energy-return prosthetic foot with a tunable coil-over shock absorber. It includes modelling, simulation, and parameter optimization to improve comfort, energy efficiency, and stability, supporting the development of advanced adaptive prosthetic systems that better replicate natural human walking.

This project focuses on creating an automated inspection system for conveyor belts using image processing and vibration sensors. It detects misalignment, surface damage, and jams in real time, enabling early fault identification, reducing downtime, and improving the reliability and safety of industrial material-handling operations. 

The design and development of an adjustable multi-cup sealing machine aim to revolutionize packaging processes in the food and beverage industry. Traditional cup sealers, limited to single cup sizes, pose challenges for businesses handling diverse cup models, leading to increased operational costs and inefficiencies. This innovative machine introduces an adaptable sealing mechanism capable of accommodating various cup sizes, making it a versatile solution for packaging needs.

Plastic cups, widely used for their convenience and affordability, have become indispensable in both domestic and large-scale industries. However, the lack of flexibility in existing sealing equipment often limits their usability. The proposed machine addresses these challenges by enhancing packaging efficiency, reducing costs, and ensuring consistent sealing quality across multiple cup sizes.

This project underscores a commitment to engineering practical and cost-effective solutions, offering a transformative approach to packaging that meets the dynamic demands of modern industries while improving customer satisfaction.