Small and medium-sized food enterprises (SMEs) in the Arctic Aurora region face increasing challenges in meeting legal and consumer demands for food quality and safety. Due to their limited size and resources, most SMEs cannot afford advanced quality control systems, restricting their competitiveness regionally and globally.
The Interreg Aurora funded project InAFQual addresses these challenges by developing affordable, innovative solutions for food quality monitoring and documentation. Integrating spectral and hyper-spectral imaging, Artificial Intelligence (AI) and Tiny Machine Learning (TinyML), the project will create (1) a smart, low-cost system for product and process quality monitoring, and (2) a structured documentation method for food products, making quality control easier, smarter, safer, and more sustainable.
Pilots with local Arctic food SMEs will demonstrate the applicability of the developed solutions, fostering stronger cooperation between academia and industry. In the short term, InAFQual will raise awareness, support education and promote adoption of modern technology among SMEs. In the long term, the project will support the preservation and promotion of Arctic food heritage, boost and strengthen global competitiveness, expand markets for Arctic food products, and encourage sustainable growth in the regional food industry.
Project Webpage: https://inafqual.eu/
Contact Person: Dina Shona Laila, Project Leader, Luleå University of Technology, dina.shona.laila@ltu.se
