AI will drive urban greenhouse expansion and the technology will enable greenhouses to locate in or close to urban environments.
The upward trend in the past decade has been the demand for locally grown and sustainable food. Ten years ago, the concept of a greenhouse on top of a Whole Foods store in Brooklyn or a greenhouse on a former parking lot in New Jersey was unheard of. Yet, food deserts remain and access to quality fresh produce remains elusive for many urban dwellers.
People want to know where their food comes from and who is growing it. If 80% of the population wants their food grown locally, the fact that it’s coming from Texas, Florida, and Mexico isn’t going to satisfy their needs. Combine the desire for locally grown food with the increase in public awareness of food safety issues, and you have two strong reasons why growing food in a CEA manner is expanding rapidly in urban areas.
Currently, the economies of scale that apply to outdoor farming don’t necessarily apply to indoor farming, especially in developing countries. Where AI comes into play is in making it economically viable to locate a greenhouse close enough to an urban area that food can be delivered in two or three hours.
Our computer vision and AI system allow a grower to predict what their yield will be with 91% accuracy. Think about the figures that the industry considers acceptable for shrinkage and then think about reducing that rate to 9%. When that happens, greenhouses can afford to locate in areas where operational expenses are higher. The intersection of increased demand and economic viability is what AI will help drive.
iUNU offers two avenues for funding. First, the combination of our AI robotics and computer vision is revolutionizing the cost structure and making it feasible for large scale greenhouses to operate in a higher cost urban area. Second, iUNU is working with a group of ten non-profits who use greenhouses to teach occupations to developmentally disabled adults.
We propose to expand the use of our technology in a manner that would be affordable to governments and localities on a proof of concept basis to encourage early adoption and improvements. Within that framework, we would look to include the developmentally disabled community as proof of the ease of use and as an example of innovation within a public/private partnership.
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