The Orbem Genus: AI-powered imaging technology for fast, accurate, and contactless object classification & analytics

Información del proyecto

Orbem Genus

Identificador del acuerdo de subvención: 190152213

DOI

10.3030/190152213

Proyecto cerrado

Fecha de la firma de la CE 20 Mayo 2022

Fecha de inicio 1 Junio 2022

Fecha de finalización 30 Noviembre 2023

Financiado con arreglo a

• The European Innovation Council (EIC)

Coste total

€ 3 513 751,25

Aportación de la UE

€ 2 450 876,00

Coordinado por

ORBEM GMBH
Germany

Periodic Reporting for period 2 - Orbem Genus (The Orbem Genus: AI-powered imaging technology for fast, accurate, and contactless object classification & analytics)

Período documentado: 2023-03-01 hasta 2023-11-30

Resumen del contexto y de los objetivos generales del proyecto

Poultry is humanity's most important source of animal protein. Yet, it is extremely difficult to optimize the eggs in - chicks out process, resulting in the waste of billions of eggs, incubation hours, and lives of male chicks. At Orbem we are developing the Genus: AI-powered imaging technology that enables poultry companies to solve their toughest challenges. We use MRI to collect data from inside eggs and process the data with AI to provide access to hidden sources of knowledge. At the pedigree level, breeding companies use the data to develop the next generation of poultry with better quality. At the commercial level, we automatically classify eggs according to different criteria, including fertilization status, inner quality, and the sex of the developing embryos. We can prevent the waste of billions of eggs, dramatically increase hatchability, and stop the culling of male layers - transforming poultry into an efficient, sustainable, and animal-friendly industry.

Trabajo realizado desde el comienzo del proyecto hasta el final del período abarcado por el informe y los principales resultados hasta la fecha

Our innovation is called the Orbem Genus: AI-powered imaging technology that enables fast, accurate and contactless object classification and analytics. Our breakthrough technological innovation combines accelerated magnetic resonance imaging (MRI) with advanced deep learning to make poultry production more sustainable and efficient.

We are world-first to build patented, end-to-end AI-powered MRI applications, transforming MRI from slow, expensive, and complicated, to fast, accessible, and simple. By taking MRI out of hospitals and bringing it into hatcheries, we offer poultry producers a world of possibilities.

These possibilities are created with imaging technology that is harmless and contactless, allowing us to provide the intelligence of a laboratory at the speed and scale of industrial mass production. This way, we provide unique information from inside eggs without being invasive. Thereby Orbem is the only company globally offering MRI-based solutions for egg analytics.

We scanned and classified more than 25 Million eggs over the course of the project.

Avances que van más allá del estado de la técnica e impacto potencial esperado (incluida la repercusión socioeconómica y las implicaciones sociales más amplias del proyecto hasta la fecha)

Due to the legislative change in France and Germany regarding the culling of male chicks, we had the opportunity to install our technology in three hatcheries over the course of the project. Since the start of operation we classified more than 25 Million eggs, saving more than 10 Million of male chicks from being culled on the first day after hatch.

An EU-wide ban on male chick culling, aiming to stop the cruel practice in the layer business and to standardise the framework accross EU-states, is needed to ensure further uptake and success of our technology.

Snapshot of our new website for in-ovo sexing

Schematic of the Genus system, the first ever fully automated, industrial MRI.

Render of the Genus system for in-ovo sexing with two modules in parallel to achieve a throughput of

New branding of our solution for in-ovo sexing

Image of the Genus system for in-ovo sexing in a hatchery with four modules in parallel to achieve a