From Above & Beyond: Drones, Computer Vision & Intelligent Systems in Agriculture
Demonstrating Autonomous Sensing, Aerial Profiling, and AI-Driven Decision Support for Smart Agriculture
Institution / Host
Namal University, Mianwali & Educational Robotics Lab (NUST SEECS)
Location
Namal University, Mianwali, Punjab, Pakistan
Duration / Timeline
2-Day Workshop & Demonstration Session
Collaboration & Support
In collaboration with Nisar Aziz AgriTech Center, Eureka Robotics Centre & British Council
Event Photography & Field Records
Click any photo to enlargeTaking intelligent systems beyond university walls.
At the 2nd Namal Agribusiness School hosted by Namal University, Mianwali, the Educational Robotics Lab (NUST SEECS) presented a hands-on technical workshop titled 'From Above and Beyond: Drones, Computer Vision and Intelligent Systems in Agriculture.'
The initiative was structured to bridge academic laboratory research with physical field applications, showcasing how autonomous robotics, multispectral computer vision, and machine learning models can move beyond the classroom to directly solve challenges faced by rural agricultural communities.
As part of the NUST team under the supervision of Dr. Farkhanda Afzal, we presented three applied technological systems developed to make agriculture more data-driven, sustainable, and productive.
The workshop brought together agricultural entrepreneurs, farmers, researchers, and university students, creating an active forum to demonstrate practical technologies and engage on how technology-driven precision farming can transform productivity in Pakistan.
Demonstrated Systems
PlantView — Plant, Tree & Disease Detection
A computer vision pipeline designed for the aerial detection and mapping of trees and plants, along with the automated identification and diagnosis of their associated diseases from drone imagery.
Drone Swarm — Coordinated Agricultural Operations
Multi-UAV coordination algorithms for wide-area coverage, synchronous flight planning, and scalable agricultural survey over large acreages.
Project Kisan — AI Agricultural Advisory Assistant
An intelligent conversational advisory model providing accessible, localized agricultural insights and predictive guidance to farmers.
Key Outcomes & Skills
- Crop health, vegetative indices, and multispectral vegetation monitoring.
- Water-stress detection and data-driven irrigation management.
- Precision spraying concepts and variable-rate chemical application.
- 3D land topology, elevation, and soil mapping with aerial photogrammetry.
- Automated crop counting, density estimation, and yield prediction.
- AI-based agricultural decision support combining sensor data with local farming knowledge.
Supervision & Mentorship
- Dr. Farkhanda Afzal — Head of Educational Robotics Lab, NUST SEECS
- Dr. Shadan Khan Khattak — Eureka Robotics Centre, Cardiff Metropolitan University (UK)
Internees & Presentation Team
- Hamdan Tariq — BSAI-24, NUST
- Fahad Ali — BSCS-15E, NUST SEECS
- Farhad Khan — BSCS-15D, NUST SEECS
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