In order to boost the participation of the AI community, an Online Challenge will be organized. The goal will be to invite the AI community interested in AI for horticulture and to motivate them in participating in the Hackathon and Greenhouse Growing Challenge.
Recruitment of AI teams and scouting of talents
We believe the following expertise from AI community is needed towards fully autonomous crop control: Machine learning skills and Computer vision skills. Machine learning skills will be tested in the interaction with a lettuce growing simulator. The simulator will consist of a simple greenhouse climate and crop production model that will be provided. Computer Vision skills will be tested on real lettuce images. A series of annotated images will be provided as training dataset.
Online Challenge for AI experts
The first part of the 3rd edition of the Autonomous Greenhouse Challenge takes place from 1 June to 14 July as open Online Challenge, aiming at testing machine learning and computer vision skills of participants of the AI community.
In Part A - the computer vision challenge - teams will get access to a series of lettuce plants. Images are taken with a RealSense camera under defined conditions and contain images of individual lettuce plants of different varieties in different growth stages and grown in different growing conditions. Each image is connected with information on the ground truth plant traits, such as plant diameter, plant height, plant fresh weight, plant dry weight, and leaf area. Teams use ca. 300 images provided in batches to develop a computer vision algorithm during the preparation phase. This algorithm will have to be able to estimate the plant traits of a series of ca. 50 unseen lettuce plant images provided during the Online Challenge under limited time and memory constraints. The computer vision algorithms have to detect the plant parameters described above.
In Part B – the machine learning challenge - teams will get access to a virtual simple greenhouse climate and lettuce production model (simple simulator). The simple simulator consists of a given set of outside climate conditions, a given greenhouse type and given greenhouse actuators (ventilation, heating, lighting, screening). It needs to be provided with a series of climate setpoints (ventilation strategy, heating strategy, lighting strategy, screening strategy per timestep) as inputs. The input climate setpoints will activate the available virtual actuators, which will control the inside greenhouse climate. The realised inside climate parameters will be provided as a feed back value.
Since the crop growth in the simulator is determined by the realised greenhouse climate, also the crop growth parameters (fresh weight, height, diameter) over time will be provided as output. Teams will have to develop machine learning algorithms to feed the simple simulator with the optimised control parameters in order to maximise net profit. During the preparation phase teams can interact with the simple simulator for algorithm development. During the Online Challenge this algorithm should be suitable to control the growth of a virtual crop in a virtual greenhouse under changed conditions (e.g. other weather conditions, different greenhouse type, different lettuce type) and limited time constraints.
Who can join?
The Online Challenge is targeting AI experts with skills in machine learning and computer vision. Teams consist of a minimum of 2 members. The maximum number of teams admitted will be 200. A participant can only be part of one team and subscribe once. We encourage teams from different countries and continents to participate. We encourage cooperation between different experts from different start-ups/companies with students and researchers from universities/research centres. We encourage engaging with experts in the field of horticulture but this is not mandatory.
It is not necessary to participate in the Online Challenge before participating in the other phases of the 3rd Autonomous Greenhouse Challenge later this year. However, it is advisable since we scout talents, the winner gets a wild card directly for the Greenhouse Challenge and there will be a prize to win for the Online Challenge.