Jakarta, INTI - PT Dabeeo Artificial Intelligence Indonesia is collaborating with IPB University (Institut Pertanian Bogor) to develop artificial intelligence (AI) and satellite imagery-based technology to detect nutrient deficiencies and oil palm plant diseases more quickly and accurately.
For this collaboration, a Memorandum of Understanding (MoU) was signed by Executive VP of Dabeeo, Chang Hoon Moon, and Prof. Anas Miftah Fauzi, Head of LRI Teknologi Maju at IPB University.
Rizky Dantri, Head of Business Development at Dabeeo Indonesia, stated that Dabeeo will support the research, including providing satellite imagery data and funding necessary for the research process.
"We at Dabeeo are ready to provide financial support for this research, especially for data acquisition. So, if the research requires the use of satellites, we are ready to provide it," said Rizky.
AI and Satellite Data for Analysis Accuracy
Through this collaboration, the two parties will develop a method for identifying plant nutrient deficiencies that relies on visual observations and integration of AI and high-resolution satellite imagery. This technology is expected to produce more precise crop management recommendations and detect potential diseases early.
Anas stated that the use of AI and satellite data will improve the accuracy of plant health analysis in large plantation areas.
"Through this collaboration, we want to develop a nutrient deficiency detection method that utilizes artificial intelligence and satellite data to produce more precise recommendations and can be used to identify plant diseases," said Anas.
Integrating Both Parties’ Technologies
This technology development complements Precipalm, an innovation previously developed by IPB University to provide oil palm fertilization recommendations through leaf image analysis.
As a provider of satellite imagery-based solutions, Dabeeo operates satellites with a resolution of up to 30 centimeters to support the agroforestry sector. The technology can identify tree density and canopy cover, and monitor changes in vegetation conditions (change detection) using historical data.
This collaboration is aimed at providing a faster, more accurate, and more efficient plant health monitoring system, enabling earlier management of oil palm plantations and increasing crop productivity.
Conclusion
PT Dabeeo Artificial Intelligence Indonesia and IPB University are collaborating to develop AI-based technology and satellite imagery to detect nutrient deficiencies and diseases in oil palm plants more quickly and accurately. This technology is expected to produce more accurate plant management recommendations and detect potential diseases early, complementing the Precipalm innovation developed by IPB. This collaboration is expected to provide a more efficient plant health monitoring system and increase the productivity of oil palm plantations.
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