Logo MachVis

A 3-day training workshop on

Enabling Sustainable Solutions for Agriculture and Water Resources

Agriculture in the SAR (South Asian Region) is caught in a low equilibrium trap with low productivity of staples, supply shortfalls, high prices, low returns to farmers and area diversification – all these factors can be a threat to food security. Addressing this issue can have a great impact over the lives of the people in this region. Contributing to sustainable water and agriculture resource management systems can be a challenging task. This workshop is among many other initiatives towards a major goal of food security in the South Asian Region through stocktaking of research, potential and role of technology, and other interdisciplinary initiatives.

The intent of this workshop is three-fold. The first is exploration of activities related to research, developing technologies, and other interdisciplinary initiatives. Secondly, it shall identify gaps that can be addressed through research and development, capacity building, and knowledge management. Lastly, it shall provide a platform to the participants to establish multidisciplinary collaborations.

 

Objectives

  • Explore the potential of Artificial Intelligence (AI) and Internet of things (IoT) in developing sustainability in agriculture and water resources
  • Examine agriculture and food global value chain recovery challenges and the importance of enhancing interdisciplinary cooperation within the sector
  • Exchange sustainable agricultural knowledge and technological innovation
  • Share domestic and regional-level best practices for enhancing sustainable agricultural development

Output

  • Improved understanding of agriculture adaptation challenges and opportunities for building the sector’s sustainability and resilience with the use of AI and IoT
  • Constructive dialogue and network building between technology experts and agriculture practitioners
  • Presentations and other workshop materials to be uploaded on the MachVIS lab website.

Participants

  • Technology experts from TIEN member countries NRENs and Associate Organizations
  • Experts from the universities and national research organizations and the practitioners
  • Interested members of the public

Speakers

Prof. Dr. Karsten Berns

Technical University of Kaiserslautern, Germany

Dr Zahid Mehmood

Chief Scientific Officer, NARC Pakistan

Muhammad Jahanzaib

 Scientific officer, NARC Pakistan

Dr Asad Waqar Malik

Associate Professor, SEECS, NUST, Pakistan

Dr Arsalan Ahmed

Associate Professor, SEECS, NUST, Pakistan

Dr Yasir Faheem

Associate Professor, SEECS, NUST, Pakistan

Dr Hasan Ali Khattak

Associate Professor, SEECS, NUST, Pakistan

Jakub Pawlak

Technische Universität Kaiserslautern, Germany

Qazi Hamza Jan

Technische Universität Kaiserslautern, Germany

Axel Vierling

Technical University of Kaiserslautern, Germany

Eike Gassen

Technical University of Kaiserslautern, Germany

Organizers

Muhammad Moazam fraz
Dr Muhammad Moazam Fraz

Associate Professor,  SEECS, NUST, Pakistan

Dr. Zuhair Zafar

Assistant Professor, SEECS, NUST, Pakistan

Program Details

TimeTutorial TopicPresenter
09:00am – 09:30amRegistration 
09:30am – 11:00amIntro to Crop Simulation for Agriculture applications using Unreal Engine-IQazi Hamza Jan, Research Scientist, Technical University of Kaiserslautern, Germany
11:00am – 12:30pmCrop Simulation for Agriculture applications using Unreal Engine-IIJakub Pawlak, Research Scientist, Technical University of Kaiserslautern, Germany
01:00pm – 02:00pmBreak 
02:00pm – 03:30pmRole of Multi-spectral Drone Imagery in Remote Sensing towards Crop Health MonitoringMuhammad Anwaar Khalid, Data Scientist, Machine Vision and Intelligent Systems Lab, SEECS, NUST, Islamabad

Time

Presentation Title

Presenter

09:00am – 09:30am

Registration

 

09:30am – 09:35am

Welcome

Muhammad Salman Akhter (MoC)

09:35am – 09:50am

Research Paradigm in NUST and SEECS

Dr. Arsalan Ahmed, Assoc Prof,  NUST SEECS

09:50am – 10:40am

Use of Semi-autonomous Watercraft for Flooded Environment

Prof. Dr. Karsten Berns, Robotics Research Lab, Technical University of Kaiserslautern, Germany

10:40am – 11:00am

Break

 

11:00am – 11:50 am

Quasi-real-time water quality monitoring for early chemical and/or bio-contamination detection

Dr. Yasir Faheem, Assoc Prof,  NUST SEECS

12:00 pm – 12:50 pm

Opportunities and challenges of wheat crop improvement programme

Dr Zahid Mehmood, Senior Scientific Officer Wheat Programme, National Agricultural Research Centre Islamabad

01:00pm – 02:15pm

Break

 

2:15pm – 03:00pm

Object Detection under image Noises for Agriculture Use-Cases

Axel Vierling, Research Scientist, Technical University of Kaiserslautern, Germany

03:00pm – 03:40pm

Improving Oilseeds crops for climate resilience through innovative approaches

M. Jahanzaib, Scientific officer, Oilseeds Research program,National Agricultural Research Center, Islamabad.

03:40pm – 04:00pm

Break

 

04:00pm – 04:50pm

An Autonomous Lightweight robot for steep slope Agriculture

Eike Gassen, Research Scientist, Technical University of Kaiserslautern, Germany

Time

Presentation Title

Presenter

09:30am – 10:10am

Distributed architectures for agriculture and water resource management applications

Dr. Asad Waqar Malik,  Assoc Prof,  NUST SEECS

10:10am – 10:50am

Exploring on-device classification for Agriculture Use Cases: Potentials and Challenges

Dr. Hasan Ali Khattak,  Assoc Prof,  NUST SEECS

10:50am – 11:00am

Break

 

11:00am – 11:40am

Enabling Smart Yield Boosting: Rice Phenology Estimation Using Airborne Multispectral Remote Sensing Data

Ramesha Murtaza, Research Scientist, Machine Vision and Intelligent System Lab

11:50am – 12:30pm

Application of AI and Multispectral Imagery for health monitoring of Corn Crop and Vineries

Muhammad Usama, Research Scientist, Machine Vision and Intelligent System Lab

12:30pm - 12:45pm

Closing Ceremony

 

Partners

Machine Vision and Intelligent Systems Lab, SEECS NUST

Registration

Completion Certificate will be provided to all the workshop attendees.

Contact Details

Location

Email

Phone Number