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.
It will not be necessary to participate in the Online Challenge to be eligible for participation in the Hackthon. However, it is advisable, since we will use the Online Challenge for scouting of talents. Participating teams will not only have a chance for a price and a wild card for the Greenhouse Growing Experiment, but also the possibility to exercise for the Hackathon.
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.
Eligibility of teams
- The Online Challenge is open to students and researchers from universities and research centres and experts, from companiesand start-ups.
- Teams of at least 2 real persons are eligible to subscribe.
- Team membersmust have the following expertise: 1. Machine learning 2. Computer vision. This expertise has to be demonstrated by professional or academic engagement.
- Each team will appoint a team-captain who acts as contact person.
- Each participantis only allowed to participate in oneteam and tosubscribe to the Online Challenge once.
- Participants must subscribe via the official site with their professional or educational email account, thus company/start-upor university/research centre account.
- Names of participants and emailaddresseswill not be disclosed by the organisers, only team names and number of teams will be public. If teams reach the top 5 ranking at the endof the Online Challenge, they automatically agree that the names of participants will be disclosedto honour them.
- We encourage teams from different countries and continents to participate. We encourage cooperation of different experts from different start-ups/companieswith students and researchers form universitites/research centres. We encourage to engage with experts in the field of horticulture but this is not mandatory.
- Good English language skills are required.
- The maximum number of teams acceptedin the Online Challenge will be 200. In case of a highernumber of subscriptions the organizers and jury will rank the subscriptions andselect basedon the criteriastated above. The jury’s decision will be final and will not be subject to debate.
- To register, teams are required to submit the completed registration form available on the website from 15 April 2021 onwards.
- The submission must include detailed information on all individual team members.
- The team should meet all eligibility criteria (stated above).
- The registration form must be completed and submitted before 20 May 2021 0:00 h CET.
Online Challenge procedure
Part A : 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.
Part B : 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 feedback 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.
Comparable to the first and second edition of the Autonomous Greenhouse Challenge, a selection process (24-hours Hackathon, physical gathering @WUR Bleiswijk, if possible) will be organized. The aim of the 24-hours Hackathon event is to select up to 5 teams for the real Greenhouse Growing Experiment.
Other aims are, to connect participants form AI and horticulture and different cultural backgrounds, to exchange knowledge and stimulate interaction. AI skills will be tested by producing a greenhouse lettuce crop virtually.
During the Hackathon teams will be scored based on pre-defined criteria (e.g. goal could be maximum net profit). Next to that, teams will have to present themselves and pitch their AI approach in front of an international jury. The jury will consist of international experts well-known in horticulture and AI. Teams will have to develop their own AI to fulfil the goal of the Hackathon and for evaluation by the jury. The 5 teams with the highest scores will win access to the Greenhouse Growing Experiment.
In a practical greenhouse growing experiment, the 5 best scoring teams will grow a lettuce crop in two crop cycles of 6-8 weeks in 5 greenhouse compartments at WUR Bleiswijk fully autonomously.
Wageningen University & Research (WUR Bleiswijk) has a unique high-tech greenhouse facility with identical small (96 m2) compartments. All compartments have different actuators to control the inside growing conditions. Main actuators are: ventilation windows, 2 heating systems, 2 shading systems, artificial lighting, fogging for humidification, water input, nutrient mixture, CO2 input. All compartments are equipped with standard sensors to control the actuators through a standard greenhouse climate computer. Main sensors are: temperature, humidity, CO2, PAR light, pH and EC of fertigation water and simple RGB camera’s. All data measured and all control actions taken are available through a data interface.
Each team will have access to one compartment with its standard sensors installed (see above). Each team will be allowed to install additional sensors high resolution RGB, hyperspectral or thermal camera’s to monitor crop growth or any other sensors which they consider useful, before the experiment starts. No human measurements of crop parameters will be provided by the organizers, apart from measuring final harvest. The teams will have access to all relevant data via a data interface from their own compartment. The teams will have to develop fully autonomous algorithms and submit them to the organizers before the start of the second crop cycle experiment. These algorithms should be able to make choices with respect to the control settings, to remotely control crop growth. Each team will be able to extract necessary data from the greenhouse compartment and couple it to their own fully autonomous algorithms in order to decide on the control settings for the next period. The control settings will have to be sent back automatically to the system (the greenhouse climate computer) in order to control the actuators automatically. Only the second crop cycle will count. The winner will be the team with the highest net profit at the end.