Projects

Selected research and engineering projects in landslide monitoring, electric mobility, artificial intelligence and smart grids.

Integrated and multidisciplinary investigation of high-risk landslides using space, air and ground-based remote sensing

A collaborative project with the University of Azad Jammu and Kashmir, integrating remote sensing and ground-based monitoring to investigate high-risk landslides and support early warning. The project includes the Landslide Monitoring and Alert System (LAMAS) at Lohar Gali.

Funding: PKR 18 million from NCGSA.

Electric Quad Bike

Design and development of an electric quad bike as an alternative to conventional fuel-powered transport. The project explores electric mobility, with an emphasis on energy efficiency, reduced maintenance requirements and environmental sustainability.

Funding: Ignite NGIRI.

AI-Based Railway Crossing Security

A railway crossing safety system that uses cameras, image processing and artificial intelligence to identify vehicles, people and obstacles in real time. The proposed approach combines visual monitoring with warning lights and audible alarms to help reduce collision risks.

Funding: Ignite NGIRI.

Landslide Monitoring Sensor Node

Design and development of equipment to gather sensor data from a landslide site and support monitoring and early warning. Developed under the supervision of Dr. Muhammad Farooq-i-Azam and Dr. Abbas Javed, the system processes sensor measurements to generate alerts as part of an NCGSA-funded research project.

Funding: National Center for GIS and Space Applications (NCGSA).

Electric Grid Temperature Profiling using a UAV

A UAV-mounted thermal imaging system for remotely profiling the temperature of an electric grid. The prototype combines a drone, wireless thermal imaging and ground control, enabling measurements from a distance of approximately 13 feet.

Funding: Ignite NGIRI.

Front Wheel Electric Powered Hybrid Motorbike

A hybrid motorbike that can switch between battery and petrol operation. A brushless DC motor drives the front wheel in electric mode, while a conventional engine powers the rear wheel in petrol mode. The battery can be charged from a standard household power socket.

Funding: Ignite NGIRI.