IoT-enabled AI-driven Smart Agriculture
Professor Liangxiu Han was a Keynote Speaker at CropWatch-ICP training programme funded through United Nations, Economic and Social Commission for Asia and the Pacific (ESCAP), Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS)
“Precision Agriculture: A Big Data Driven, AI enabled Approach to Crop Disease Diagnosis”
Professor Han participated in a 3 – Day International Workshop discussing our work on Precision Agriculture.
Organised by the National Institute of Disaster Management (NIDM) in India, the workshop covered many aspects of driving development in symbiosis with the environment, including the role of technology in agriculture.
Professors Han’s presentation, ‘Precision Agriculture: Big data driven, AI enabled Approaches to Crop disease Diagnosis and Monitoring’ was a key contribution to this discussion
While the world is dealing with the pandemic in these troubling times we would like to express our support and appreciation to those that are working to safeguard the vulnerable and our consolation to everyone effected.
Due to the disruptions in international travel we have had to delay our scheduled project demonstration and are continuing to work towards improving our solution during these troubling times.
Today we held a meeting to demonstrate the current progress of the project with representatives from numerous industry partners. The goal was to determine how successfully our solution was in solving the issue of Bacterial Leaf Blight detection in rice fields and to discuss ways of improving it to meet the needs of different end users.
The discussion went well with great interest on behalf of the industry partners and excellent feedback to further develop and refine the project.
During a visit to a rice paddy we used our mobile application to automatically survey the field. The literal field test was a great success, our application connected to the Phantom 4 Pro drone without issue, generated a flight path and uploaded it to the drone. The drone was then able to photograph the entire field without any user input. Afterwards the photos were downloaded to the mobile device before being analysed by out disease segmentation model.
We gathered some useful data about improvements to the system and the mobile application while demonstrating the ability to easily control the drone without direct user intervention.
Professor Liangxiu Han gave a presentation, “Precision Agriculture – A Big Data Driven Approach to Crop Disease Detection”, at the Third International Workshop on “Precision Agriculture: Data Driven Approach to Crop Monitoring and Disease Diagnosis”, held in Beijing, China, 25th – 27th September 2019
On August 13-14, 2019, we had a successful face-to-face meeting, which was held in Manchester Metropolitan University, UK. During the meeting, we had discussed the project progress and achievements. Finally, we confirmed and planned the next step.
The DJI Phantom 4 Pro has finally arrived on the 21st September !!!
Shakirin tested out the drone in the campus
AgriONE 