AI helps control greenhouse automation systems

Indoor agriculture has seen a marked increase in the last few years and the category continues to grow. Vertical farms can be managed to maximize year-round production while using precise amounts of limited resources, such as water, preventing waste in the process.

To achieve an effective ROI for the cost of a vertical farm and its equipment, all inputs – water, chemicals, lighting, temperature, humidity and more – must be carefully controlled. Although the process variables for growing products indoors may seem simple, there are elements that need to work together to be successful.

To gain a thorough understanding of such a complex, slow-moving system with interdependent variables, it makes sense to use artificial intelligence (AI) and combine it with machine learning (ML). Kenneth Tran, PhD, founder and CEO of Koidra, a systems integration company specializing in applying artificial intelligence to practical operations such as greenhouses and production automation, is well versed in artificial intelligence. Prior to Koidra, Tran was a primary applied scientist in the Machine Learning Group, Microsoft Research (MSR).

Recently, the indoor manufacturer Soli Organic has entered into a partnership with Koidra to develop the systems for its controlled environmental agricultural facilities (CEA). “Two major problems with CEA facilities are data silos and lack of compatibility with standard data exchange protocols,” said Kenneth Tran, founder and CEO, Koidra.

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