Descripción del proyecto
La digitalización del control de calidad en los alimentos a fin de evitar el desperdicio
La mitad de las frutas y hortalizas cultivadas cada año nunca se llegan a comer; de hecho, las frutas y hortalizas tienen el mayor índice de desperdicio de todos los productos alimentarios. Hay una manera de cambiar esta tendencia. El proyecto ImpactVision, financiado con fondos europeos, llevará a cabo un estudio de viabilidad con una tecnología de obtención de imágenes hiperespectrales para la cadena de suministro alimentaria. Esta tecnología se ha diseñado para las empresas elaboradoras de productos alimenticios, los fabricantes, los distribuidores y los minoristas, y se puede emplear para mejorar la calidad de la comida, generar productos uniformes y reducir el desperdicio. Por ejemplo, es capaz de determinar si el pescado es fresco, si el aguacate está maduro o si hay elementos extraños; todo ello, de un modo inmediato y no invasivo. Algo especialmente interesante es que esta técnica de obtención de imágenes puede captar datos sobre la calidad del alimento en tiempo real, algo imperceptible a la vista humana.
Objetivo
ImpactVision is a machine learning company, applying advanced imaging technology to food supply chains in order to improve food quality, generate consistent products and reduce waste. Our software provides insights about the quality of foods and is aimed at food processors, manufacturers, distributors and retailers. For example, our system is able to determine the freshness of fish, the ripeness of avocados or the presence of foreign objects rapidly, non-invasively and at production grade speeds.
Hyperspectral imaging technology captures information our eyes cannot, in other parts of the electromagnetic spectrum. Our goal is to provide objective, real-time food quality data to the 30,000+ food processing facilities across the USA and improve efficiency of the global food supply chain. Currently, a third of all food produced is wasted. To illustrate the environmental impact at scale, managing food waste sustainably could reduce greenhouse gas emissions by over 500 million tonnes - the equivalent of taking all the cars off the road in the European Union. By digitizing food quality control, we improve yields and prevent waste, whilst increasing food companies’ revenues, which is particularly prescient considering the industry has razor thin profit margins.
ImpactVision combines a hyperspectral sensor installed above a conveyor belt with software that analyzes images and provides real time insights about quality.
By pursuing the present feasibility study, the management team aims to improve its understanding of international market conditions and the associated risks that need to be considered as the company develops a deeper business plan for rolling out, and scaling up ImpactVision as a marketable innovative solution. SME Instrument Phase-1 and Phase-2 will be extremely beneficial in helping the company to accelerate development and market penetration of the solution in target segments, boosting the company’s growth to 94 employees and $109M revenues by 2024.
Ámbito científico
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- engineering and technologyother engineering and technologiesfood technologyfood safety
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsmobile phones
- natural scienceschemical sciencescatalysis
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-SMEInst-2018-2020-1
Régimen de financiación
SME-1 - SME instrument phase 1Coordinador
NG18 1BL MANSFIELD
Reino Unido
Organización definida por ella misma como pequeña y mediana empresa (pyme) en el momento de la firma del acuerdo de subvención.