Smarter Watering with Image Processing and Evapotranspiration
Smart irrigation techniques are becoming more common in agricultural environments. Sensor technology has become powerful and efficient enough to allow a network of sensors to be embedded into self improving irrigation systems capable of adapting to weather changes and specific local conditions \cite{Winkler2018}. This addresses the issue of water consumption relative to the environment. These systems are susceptible to local factors that prevent perfect irrigation such as a malfunctioning mote, blocked sprinklers, or coarse data points. Plant health data incorporated into the current processing pipeline can address this problem, by telling the system which areas need more attention. The focus of this research is to implement a non-invasive way to measure plant health and incorporate it into existing irrigation systems, improving its robustness by providing finer granularity data points.
