Wageningen University, based in the Netherlands, is organizing the 4th edition of the Autonomous Greenhouse Challenge: the challenge for sustainable vegetable production with AI. This year’s focus is dwarf tomatoes.

Earlier editions from 2018-2022 have encouraged teams growing cucumbers, cherry tomatoes, and lettuce crops autonomously. It has been demonstrated that computer algorithms can increase greenhouse crop production, save energy, and yield higher net profits. Artificial intelligence can be superior to human intelligence, and can potentially control indoor farming in the future.

Wageningen University & Research works on autonomous greenhouses, climate control, crop modelling, use of sensors, data, artificial intelligence, computer vision, and robotics. Working with industry, the university’s technologies facilitate growers to produce higher quality, healthy crops in a sustainable way and using less resources.

The Autonomous Greenhouse Challenge is sponsored by Tencent and David Wallerstein (CXO Tencent). The Challenge is open to national and international teams.

The first phase of the event – online challenge and hackathon -- takes place from April to June 2024. The goal is to recruit international teams and scout talent, winnowing the entrants to the top five teams for a greenhouse growing experiment. For those participating in the online competition, they will demonstrate machine learning algorithms and how their crop models will grow dwarf tomatoes virtually. Teams will show their computer vision skills using image analysis algorithms on provided plant pictures.

Next the top five teams will compete in an International Autonomous Greenhouse Event from August 2024 to January 2025.

The selected top five teams compete against each other and a group of growers who will operate a reference greenhouse compartment. Each team gets their own compartment at WUR’s greenhouse facility in Bleiswijk, the Netherlands. The university provides the plants, greenhouse, data platform, standard sensors, and cameras. The teams develop the machine learning and computer vision algorithms needed to grow the dwarf tomatoes remotely and autonomously.

Source:  Wageningin University