Collaborating Authors

AI being used to grow tomatoes


Five teams from the Netherlands, South Korea and China have advanced to the final stage of a competition to see who can grow fresh tomatoes in greenhouses remotely using artificial intelligence. The second Autonomous Greenhouse Challenge, which is organised by Dutch academic powerhouse Wageningen University & Research (WUR) and Chinese multinational conglomerate Tencent, began in September with a 24-hour hackathon involving 21 international teams and more than 200 participants from 26 countries. The five winning teams – Netherlands-based AiCU, The Automators and Automatoes, Korea's IUA.CAAS and China's Digilog – will each be given six months' access to a real greenhouse in the Dutch town of Bleiswijk, where from December onwards they will attempt to control and produce a tomato crop from afar by employing AI algorithms to keep inputs like water, nutrients and energy at sustainable levels. September's hackathon, held at WUR, saw an international jury award points to each team based on their composition and competence, their application of AI technology and the net profit they made during a virtual tomato production game. During their pitches, the teams were given access to a climate model and a tomato crop growth model previously developed by researchers at WUR.

Can artificial intelligence grow a lettuce crop completely autonomously?


Growing lettuce with artificial intelligence (AI) in autonomous greenhouses, by algorithms developed in different parts of the world: today the young lettuce plants of the five international teams that compete in the two final rounds of the Autonomous Greenhouse Challenge were planted in the experimental greenhouses of Wageningen University & Research in Bleiswijk. The goal is to grow these lettuces fully autonomously with an AI algorithm on a cloud platform with good quality and little resource and energy use and without any human interference. The competition and teams' performance can be followed live on an online dashboard. Will the computer be able to complete a fully autonomous growing cycle? Five international teams located around the world will produce a lettuce crop using a fully autonomous algorithm during two growing cycles.

IGrow: A Smart Agriculture Solution to Autonomous Greenhouse Control Artificial Intelligence

Agriculture is the foundation of human civilization. However, the rapid increase and aging of the global population pose challenges on this cornerstone by demanding more healthy and fresh food. Internet of Things (IoT) technology makes modern autonomous greenhouse a viable and reliable engine of food production. However, the educated and skilled labor capable of overseeing high-tech greenhouses is scarce. Artificial intelligence (AI) and cloud computing technologies are promising solutions for precision control and high-efficiency production in such controlled environments. In this paper, we propose a smart agriculture solution, namely iGrow: (1) we use IoT and cloud computing technologies to measure, collect, and manage growing data, to support iteration of our decision-making AI module, which consists of an incremental model and an optimization algorithm; (2) we propose a three-stage incremental model based on accumulating data, enabling growers/central computers to schedule control strategies conveniently and at low cost; (3) we propose a model-based iterative optimization algorithm, which can dynamically optimize the greenhouse control strategy in real-time production. In the simulated experiment, evaluation results show the accuracy of our incremental model is comparable to an advanced tomato simulator, while our optimization algorithms can beat the champion of the 2nd Autonomous Greenhouse Challenge. Compelling results from the A/B test in real greenhouses demonstrate that our solution significantly increases production (commercially sellable fruits) (+ 10.15%) and net profit (+ 87.07%) with statistical significance compared to planting experts.

When will human growers become obsolete?


Greenhouse automation has come a long way in the past two decades. Give it another two decades, and it may completely overshadow the human element in the greenhouse. At least, that's a conclusion you might draw when looking at the results of the Autonomous Greenhouse Challenge and the implications of it in horticultural practice. In a webinar hosted by one of the challenge's sponsors, Heliospectra, AI was discussed from three different perspectives: academia, tech suppliers, and the grower. Kicking off the webinar, Silke Hemming, head of the scientific research team Greenhouse Technology within Wageningen University & Research, shared some insights provided by the challenge.

Using Artificial Intelligence for Crop Production - Intel AI


Recently, the "Deep Greens" team, comprised of Intel AI data scientists and horticultural experts from the Universidad Nacional Autónoma de México (UNAM), competed in, and won, a 24-hour hackathon for the chance to win one of 5 slots to grow cucumbers in an autonomous greenhouse later this year. The competition is to designed to test which team can grow the most cucumbers while reducing the number of total resources needed. By succeeding in the hackathon we now have the chance to test our deep reinforcement learning algorithms in a very novel environment. In this post, we will talk more about the overall challenge, our strategy for the hackathon, and the strategy going forward. The competition is sponsored by the Wageningen University and Research (WUR) of the Netherlands, and the company Tencent*.