Jemie Muliadi, a researcher at the BRIN Research Center for AI and Cyber Security, stated in an online discussion on Wednesday that various AI technologies, such as remote sensing, image segmentation, and shadow remover, can be applied to support Indonesia's food self-sufficiency targets.
"Remote sensing provides an overall picture of rice fields, and AI can interpret that information," he remarked.
He explained that AI-powered image segmentation can precisely distinguish between rice fields and roadways while also identifying plant maturity stages and distinguishing between healthy and diseased plants.
Muliadi elaborated that the AI shadow remover enhances aerial rice field photographs by removing shadows, thereby improving visual clarity and precision.
"The manual method of land inspection requires significant time, resources, and precision. Therefore, with aerial photos that are managed well with AI, agricultural and livestock strategies will be more optimal," he said.
In addition, he drew attention to other technologies that can be applied to detect sick plants by merely observing leaf samples.
He said that this method has been recognized and patented under intellectual property rights.
"This allows farmers and the government to isolate or treat diseases before they spread, preventing failed harvests," he remarked.
He said that by using various technologies that can support food self-sufficiency, the country no longer needs to import foodstuffs but can carry out exports to other countries in need.
Related news: Government reaffirms commitment to strengthening food security system
Related news: Indonesia focuses on infrastructure to boost food security goals
Translator: Sean M, Kenzu
Editor: Anton Santoso
Copyright © ANTARA 2024
