WIRN 2024 Workshop Ai For Agriculture 

Artificial intelligence (AI) and Deep Learning (DL), in particular, play a pivotal role in enhancing food traceability and safety across the food supply chain. With the increasing complexity and global nature of food systems, ensuring food safety and traceability has become a fundamental aspect for consumers, regulators, and producers alike. Artificial Intelligence technologies offer several key advantages in this domain. Firstly, AI-powered systems can efficiently track and trace food products from farm to fork, enabling stakeholders to identify the sources of contamination or foodborne illnesses more quickly and accurately. By analysing vast amounts of data, including production chemical analysis, production chain information, and sensors data. AI algorithms can in fact identify potential risks and mitigate them before they escalate into widespread outbreaks. Moreover, AI-driven predictive analytics can be used to forecast potential risks and trends, enabling measures to be taken to prevent contamination or adulteration of food products. Additionally, AI technologies such as machine learning and computer vision facilitate quality control and inspection processes by detecting anomalies, identifying defects, and ensuring compliance with food safety regulations. Through automation and real-time monitoring, moreover, AI empowers food manufacturers, retailers, and regulatory bodies to uphold the highest standards of food safety, bolster consumer confidence, and ultimately safeguard public health. As AI continues to advance, its integration into food traceability and safety systems promises to revolutionize the way we produce, distribute, and consume food, fostering a more transparent, efficient, and secure food supply chain.

As an example, in this context the PNRR funded Agritech (https://agritechcenter.it/it/) project was designed. Agritech is born to address global challenges such as climate change, environmental impact of agriculture, and the need to improve productivity and sustainability. The Research Center focuses on the application of enabling technologies in the Agrifood sector. Five main research objectives are addressed by the Agritech Center:

·       Resilience: Enhancing sustainable productivity and promoting resilience to climate change.

·       Low Impact: Reducing waste and environmental impact.

·       Circular Economy: Developing strategies for a circular economy.

·       Recovery: Promoting sustainable development in marginal areas.

·       Traceability: Promoting safety, traceability, and distinctiveness in agrifood supply chains.

These objectives outline the focus of the Agritech Center and its mission of innovation and sustainability in the agricultural and food sectors.

Topic of the workshops are (not limited to):

·       Development of AI methodologies to be used for traceability and food safety

·       Creation of benchmarks and datasets to be used within the agriculture and Artificial intelligence method developments

·       Computer Vision for Food Traceability

·       Artificial Intelligence methods for precision agriculture

·       Artificial Intelligence and Integration with IOT sensors

·       Developments of Artificial Intelligent based approaches for farming and agriculture production

·       Use of AI for the analysis of complex and simple agroecosystem

·       Application of Artificial Intelligence in different steps of the production chain

·       Use of Artificial Intelligence for optimization and rescheduling of the food production chain