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EYE ON CHINA
Artificial Intelligence to Tackle Agricultural Challenges
Tencent AI lab and Wageningen University & Research (WUR) announce winners of the second Autonomous Greenhouse Challenge.

Five teams battled against each other in the challenge to grow cherry tomatoes remotely by leveraging on AI and IoT technologies. The team, Automatoes, emerged victorious after achieving a perfect score and improved resource efficiency by 16 percent and net profit by 121 percent. All of which while demonstrating the massive potential of AI in assisting farmers to optimize agricultural decision-making in the future.

“The goal of the Challenge is to find the best intelligent planting solution for cherry tomatoes in an autonomous greenhouse within 6 months. And the best solution should meet five standards: high quality, high yield, low energy consumption, automation, and technology transferability,” said Dr. Silke Hemming, head of the WUR Greenhouse technology research team and coordinator of the competition.

¬¬¬As one of the main greenhouse crops across the globe, the cultivation and environmental variables of planting tomatoes must be monitored and controlled. This year's competition had higher standards for AI and IoT technical solutions and an advanced greenhouse simulator.

"The simulator allows the participating teams to obtain simulated results more conveniently and quickly so they can have sufficient data to improve the algorithm and strategy of their AI." said Dr. Luo Dijun, one of the judges of the Challenge and the head of the "AI + Agriculture" team at Tencent AI Lab.

The simulator offers broader spectrum of control variables, such as fertilizer concentration, crop management (including topping strategy and fruit-keeping strategy), and the various types of screens used on the greenhouse roofs, allowing more room and challenges for decision-making and optimization.

DeePC, developed by the champion team Automatoes, is an advanced data-driven algorithm which ensures optimal and safer control compared to the conventional model predictive control algorithm, in both cases of linear and nonlinear stochastic systems.

"Working with WUR and other partners on a multi-year journey, we have decisively demonstrated that in greenhouses AI can be a superior manager of all of the environmental factors important to the growth of cucumbers and tomatoes,” said David Wallerstein, Tencent's Chief eXploration Officer. "AI can clearly deliver dividends to humanity in terms of boosting food productivity, while actually decreasing resource usage and growing profits. We seek to continuously foster the development of these types of AI applications that can help humanity tackle the myriad global challenges that we face.”

Data shortage in the agriculture industry, caused by various factors such as long production cycles, non-standard data format, and high data collection costs demonstrates the need for capacity of current simulators to be improved, for better scalability and transferability of AI solutions in real world.

Tencent will continue to work with WUR to explore the possibilities of agricultural AI, including research into crop modelling, full-cycle crop management and data-efficient reinforcement learning.

 

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