AO Sensor

Who is the project aimed at?

The AOSensor project targets the food processing industry, helping companies ensure product quality and consistency, optimise production processes and reduce waste. Through artificial intelligence and advanced sensing, companies can adapt industrial processes in real time, improving the efficiency and sustainability of their products. It also benefits end consumers by ensuring better quality in fresh products.

Project objective

The main objective of the project is to apply infrared technology combined with artificial intelligence to automatically analyse and classify fruit and vegetables according to their organoleptic quality (sweetness, ripeness, acidity, etc.), with the aim of ensuring products are suitable for consumption, reducing food waste and improving production process efficiency.

Project description

At the UPC, we are collaborating with Ametller Origen and IRTA on AOSensor, a pioneering project that applies artificial intelligence and advanced sensing to improve food quality and optimise agri-food production processes. It has a dual objective: to integrate digital technologies into the agro-industrial sector and ensure consistency and quality in products such as gazpacho.

This system makes it possible to obtain physicochemical data —such as sweetness, acidity and water content— using a non-destructive method. These data are used to generate mathematical models capable of predicting whether a product is suitable for consumption. Initially, this technology is being applied to gazpacho production, one of the company's flagship products, to ensure consistent quality, prevent reprocessing and reduce waste and energy consumption.

Using non-invasive sensors and cloud data transmission, the AI model can adapt the industrial process in real time, improving efficiency and sustainability. Funded under the AGROSMED Agri-Food PERTE through Next Generation EU funds, AOSensor is an example of how technology and collaborative innovation can transform the food industry towards a more efficient, resilient and sustainable system.

Project funded by the Recovery, Transformation and Resilience Plan (Next Generation)