A recent review assessed how technology can play a role in early warning and emerging risk identification systems.

The review covers the existing applications of artificial intelligence, big data, and internet of things (IoT) in developing early warning and emerging food safety risk identification tools and methods. Information comes from 40 original studies and 57 reviews published from 2013 to 2022.

It is important for national authorities and international organizations to be able to identify emerging food safety risks and provide early warning signals. The use of AI for food safety surveillance and hazard source tracking purposes enables the identification of critical points and processes that are susceptible to the introduction of contaminants into the supply chain.

The study, which received funding from the UN Food and Agriculture Organization (FAO), was published in the journal Comprehensive Reviews in Food Science and Food Safety.

Artificial Intelligence, IoT, and big data hold potential as tools to support efficient and effective food safety management by the public and private sectors, said scientists.

New challenges include the increasing complexity of food supplies, climate change, international food trade, new food sources and technologies, and the circular economy.

There are many early warning and monitoring systems in operation. Information from different systems can be integrated to make better predictions.

Barriers to adoption
Implementation may prove challenging, particularly for low- and middle-income countries because of low connectivity and data availability. Appropriate infrastructure and skilled personnel are needed to collect monitoring data. Information obtained through channels such as social media and crowdsourcing should be processed with caution as there is a lack of assurance on data quality. There is also a need to ensure strong cybersecurity.

These issues can be overcome by improving the capability and capacity of national authorities, and enhancing their collaboration with the private sector and international agencies, said the study.

Cost may act as a barrier to adoption. Other challenges linked to IoT are high energy consumption and the incompatibility of different datasets.

Scientists made several recommendations to promote the use of AI and big data in early warning and emerging food risk identification. International organizations can help facilitate the exchange of data and collaboration between countries, through the harmonization of data formats and collection methods and the establishment of platforms and databases.

National authorities should share data and collaborate with other national agencies, fostering data generation and sharing within the private sectors. They should prioritize the creation of adequate ICT, mobile communications, and connectivity infrastructure and an enabling environment with adequate legislation on food safety data and data protection.

The private sector should be encouraged to allow openness of data for public use. They should also co-develop the tools for identifying early warning signals and emerging food safety risks.