A network of sensors helps these Californian farmers to maximise yields.


Z-Farms is a large farming cooperative specializing in almond production. The cooperative consists of many acres of land at 5 farms throughout California.


Almonds have specific optimal ranges for soil moisture. Deviations outside acceptable ranges can result in crop loss, damage, poor yield, and ultimately – lost dollars for the cooperative.


ThingWorx Machine Learning delivers proactive information regarding land irrigation strategies to farm operators. To avoid potentially costly dry soil, the growth of root fungus in overly saturated soil, or violation of water regulations in the area, all members of the co-op utilize sophisticated irrigation systems and a network of sensors that monitor specific variables at the farms including soil moisture, ambient temperature, wind chill, wind speed, and solar radiation. The platform enables constant monitoring of predictive indicators such as soil moisture throughout their land. This information enables cost effective strategies for greater crop yield while conforming to water regulations in California.


ThingWorx Machine Learning was implemented to convert overwhelming, but limited sensor data into clear, actionable patterns that are constantly monitored to detect and improve the overall water efficiency and crop quality. Z-Farm is able to practice more sustainable farming in water-starved California, lower costs significantly, and produce more high quality almonds.