Poster: MICO: Model-Based Irrigation Control Optimization

Lawns, both public and private, make up the largest irrigated crop in North America by surface area. Although there have been improvements in sprinkler head technology and weather assimilation, state-of-the-art irrigation systems do nothing to adjust for heterogeneous terrain or varying lawn environments. In this work, a computationally lightweight soil moisture movement model is developed, which allows the computation of optimal irrigation valve scheduling using standard optimization techniques. A prototype sprinkler head is produced with the ability to sense local soil moisture conditions, wirelessly communicate, and independently actuate based on the optimal schedule centrally computed. This prototype is then deployed to control two parallel irrigation systems covering a total of more than 10,000 ft$^2$ for a duration of 5 weeks. It is shown that lawn health can be maintained by using the topography of the space to take advantage of runoff to provide improved coverage while using an average of 23.4\% less water. We also show that the initial capital and operating costs of our system could be amortized by our water savings in $~$13 months while maintaining and/or improving quality of irrigation and lawn health.