# Food Passports and Intelligent Food Recipes: The Data-Oriented Way of Producing Food
###### Abstract
To the best of the authors' knowledge, the work discussed in this paper is most likely the first MAS Architecture dedicated to food-processing industrial systems. MASs are highly relevant for the F&B for several reasons:  
* As a concept, MAS provides a framework for articulating, from a modeling and implementation perspective: resources, their representation and actions. Existing technical MAS software platforms provide support for structured and scalable agent-to-agent interactions, agent representation and actions [16]. This is relevant for the digitalization of the F&B industry because, as discussed before, food production systems require the seamless integration of many different models both for the food produced, in its different stages of production, as well as for the production system and its resources. * MAS-based systems can scale gracefully and organically, allowing the quick and easy integration of additional agents abstracting new concerns, stakeholders, representations, algorithms, etc. The previous means that the MAS in the F&B industry can provide an elegant solution for creating and transforming data flows, as well as composing such flows through the addition/removal of agents without disrupting the behavior of the system. Data collection and processing in today's food production system occurs in a rather monolithic way that makes it difficult to progressively and on demand add new data transformations, analysis, or even data-based decision-making algorithms. * MASs have been discussed as the base for implementing DTs (which are an emerging digital representation of assets in the F&B sector). This means that many of the innovative ideas currently under discussion within the sector could be seamlessly integrated under a MAS framework. With the discussion above in mind, this paper describes what the authors believe is one of the first MAS-based architectures and solutions for food systems, henceforward designated by the AROMA platform. Within the scope just discussed, this paper concentrates on deploying MAS-based solutions to solve specific industry problems. In particular, the proposed work addresses the following:  
* There is a need to more formally describe industrial food production recipes, ingredients and raw materials with the purpose of creating a data-link between the ingredients of an industrial recipe and the ingredients available in the market at any point in time. By doing so, it is possible to use autonomous agents to select the most appropriate ingredients, including replacement ingredients, for a specific recipe, including a variety of metric (cost, environmental impact, consumer preferences, etc.). * There is a need to manage recipes and food descriptions autonomously. Food products are perishable, and their properties change as a function of their handling. Today, food products are documented textually, in paper or digital format, but their state is not dynamically updated. By using autonomous agents in such a representation, the proposed solution opens the door for active food information management. * There is a need to increasingly incorporate secondary production flows into high-value products. The F&B industry generates today a lot of waste in side flows with a very high potential for incorporation in high-value products. Solving such a problem simultaneously eliminates waste and generates value. The work, therefore, reports on the preliminary findings of the AROMA Project Consortium [17], which combines a multidisciplinary team of academic and industrial experts currently working on the development of the platform introduced in this paper. The authors stress that, at this stage, and given the novelty of the approach, the findings are reported at the proof-of-concept level. On a Technology Readiness Level (TRL) scale, the authors position the maturity of the work described in between levels 3 and 4, to be progressively increased throughout the project.