How to Improve Data Sharing in Greenhouse Artificial Intelligence

Artificial-Intelligence-in-GreenhouseControlled environment agriculture (CEA) is a data-driven scientific discipline. In CEA operations, all the environmental parameters are monitored and controlled to provide optimal conditions for crop growth. Recent technological advancements have made the use of sensors and controls more accessible to CEA growers, allowing them to precisely adjust these parameters. The use of machine learning and artificial intelligence (AI) techniques could provide CEA researchers and commercial growers an opportunity to optimize crop production efficiency and unveil new methods to improve production yield. However, there is a lack of a centralized repository and a standard methodology for data sharing.

Join GLASE Director Erico Mattos and Koidra CEO Kenneth Tran for a webinar on Aug. 4 to learn about the Controlled Environment Agriculture Open Data (CEAOD) project. This initiative aims to promote data sharing to accelerate CEA research through the establishment of a free centralized platform for the CEA community. Researcher and commercial growers are welcome to join and learn more about it.

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Kenneth Tran was part of the winner team at the first International Autonomous Greenhouse Challenge held at Wageningen University in 2018. The team defeated four other international teams, consisting of experts in the field of AI and horticulture. Erico Mattos is working with Cornell University and Rensselaer Polytechnic Institute Researchers to develop a guideline for data collection and upload to the CEAOD project.

Register for the webinar here.

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