Jakarta, INTI - Food fraud and the use of harmful ingredients remain serious threats to product quality and consumer safety. To address these challenges, the National Research and Innovation Agency (BRIN), through its Research Center for Artificial Intelligence and Cybersecurity (PRKAKS), is promoting the use of modern technologies based on artificial intelligence (AI), smart sensors, and the Internet of Things (IoT) in food safety systems.
This was conveyed by Agustami Sitorus, a researcher at BRIN's PRKAKS, during a visit by students from the Faculty of Engineering of Universitas Pasundan (UNPAS) at the Samaun Samadikun Student Center in Bandung on Monday, May 25.
Agustami expressed that food fraud practices are increasingly complex, with various methods, such as mixing ingredients (adulteration), changing primary ingredients with cheaper alternatives (substitution), and inconsistency of information on product labels (mislabeling).
"This problem requires a technological approach capable of objectively and quickly identifying product quality and authenticity," he said.
He explained that current innovations allow for non-destructive product evaluation, meaning without opening or damaging the product packaging. This technology integrates various modern methods such as smart sensors, spectroscopy, image processing, AI, and machine learning.
This Integration System is Considered More Effective
According to Agustami, the integration of AI, machine learning, IoT, advanced imaging, and nanomaterial-based sensors is believed to increase the effectiveness of food inspections while creating a more modern and reliable food safety system.
He detailed that AI and machine learning are being utilized to enhance the analytical and predictive capabilities of non-destructive technology. Meanwhile, multimodal sensors are being used to combine various sensing methods for more comprehensive product evaluation.
Furthermore, the application of IoT enables continuous monitoring throughout the food supply chain. Hyperspectral imaging technology is also considered effective in detecting defects and contamination that are invisible to the naked eye.
"Nanomaterial-based technology also has great potential to produce sensors with high sensitivity in detecting contaminants," he explained.
Agustami added that the trend of developing this combined technology presents an opportunity for future research to support the quality and integrity of national agricultural and food products. According to him, AI-based automation will revolutionize conventional testing methods into a more comprehensive, efficient, and accurate intelligent inspection system throughout the supply chain.
Conclusion
BRIN is promoting the use of AI-based technologies, smart sensors, IoT, machine learning, and advanced imaging to strengthen Indonesia's food safety system. These technologies are considered capable of detecting food fraud, contamination, and counterfeiting more quickly, accurately, and non-destructively without damaging product packaging. The integration of various modern technologies also enables continuous monitoring of food quality throughout the supply chain and is considered more efficient and reliable.
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