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Indonesia: AI, Drones Enhance Crop Management

Image credits: brin.go.id

The agricultural sector continues to experience technological advancements. Artificial Intelligence (AI) has become a part of the modern agricultural industry. AI technology is used in various aspects, from production and management to marketing. Agriculture heavily relies on weather, soil, and the environment. Therefore, AI technology related to drones and sensors is essential to support precision agriculture

Drones’ ability to rapidly scan areas with high-quality sensors is beneficial in various applications, including crop mapping, soil analysis, environmental surveys, livestock monitoring, and infrastructure surveillance.

In light of this, the Food Crops Research Centre (PRTP) of the Agriculture and Food Research Organisation (ORPP) under the National Research and Innovation Agency (BRIN) held an occasion regarding AI technology in the development of drones and sensors and its applications in agriculture.

Puji Lestari, the Head of ORPP BRIN, expressed that this occasion would benefit BRIN and other stakeholders. She emphasised that combining drone and sensor technology would create innovative solutions to address food availability challenges.

Furthermore, Puji also highlighted that precision agriculture is closely tied to the availability of tools. Implementing AI in rapid data analysis as a basis for decision-making, ranging from planting and feeding to irrigation and harvesting, is expected to benefit farmers.

The AI-based capabilities, including high-quality sensors and scanning, enable rapid work and real-time data processing, plant identification, and decision-making to support productivity targets. Therefore, the Food Crops Research Centre should provide more opportunities to utilise AI-based technology that supports increased crop productivity,” he emphasised.

At the same time, the Head of PRTP BRIN, Yudhistira Nugraha, also acknowledged that technological advancements have become inevitable. Through the science community, AI researchers are expected to actively contribute to utilising AI technology, turning it into a valuable science that can be applied to agricultural development in Indonesia.

“We can gain many benefits using AI technology for monitoring agricultural land, including fertiliser usage, fertility identification, plant growth, and with the help of AI technology, farmers can make decisions and take actions that can be applied in the farming system to increase productivity,” he explained.

Tri Surya Harapan, Research Manager at a company that provides sales of drones and surveillance services for agriculture, the environment, defence, forestry, and marine purposes, explained about multispectral cameras that provide information on plant health and management.

“AI is widely known for replicating human intelligence and can be simulated using computer systems. Automation sensors embedded in drones, such as camera sensors, LIDAR sensors, or other advanced sensors, provide valuable information as decision-makers in the field without direct human intervention,” he said.

“The use of AI with drone and sensor technology requires relatively high service costs, so in its implementation, collaboration with stakeholders on a large scale is needed,” Tri clarified.

Meanwhile, Senior Researcher at PRTP BRIN, Muhammad Aqil, discussed the Utilisation of Drone Technology in Food Crop Research. This is in line with the direction of the President of Indonesia in the 2021 National IPTEK Coordination Meeting, which emphasises the use of modern technology and contribution to the era of Industry 4.0, including the application of artificial intelligence technology to support all fields/activities, including agriculture.

“We have gone through several stages before reaching Industry 4.0, and now it’s time to use drone technology to monitor the nutrient status of plants, quickly detect pest attacks (OPT – Plant Pest Organisms), check strain contamination, inspect seed production data cells, and determine the harvest time,” said Aqil.

Aqil concluded that the vegetation index-based model developed for the selection of corn genotypes, which are tolerant to both NDVI and NDRE, has proven capable of predicting harvest yields and the best genotype types in corn variety selection in the field.

“By integrating drones and image analysis, it could support research activities, especially in the field,” Aqil added.


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