There is increased demand for irrigation scheduling tools that support effective use of the limited supply of irrigation water. An efficient precision irrigation system requires water to be delivered based on crop needs by measuring or estimating plant water stress. Leaf temperature is a good indicator of water stress. In this study, a system was developed to monitor leaf temperature and microclimatic environmental variables to predict plant water stress. This system, called the leaf monitor, monitored plant water status by continuously measuring leaf temperature, air temperature, relative humidity, ambient light, and wind conditions in the vicinity of a shaded leaf. The system also included a leaf holder, a solar radiation diffuser dome, and a wind barrier for improved performance of the unit. Controlled wind speed and consistent light conditions were created around the leaf to reduce the effect of nuisance variables on leaf temperature. The leaf monitor was incorporated into a mesh network of wireless nodes for sensor data collection and remote valve control. The system was evaluated for remote data collection in commercial orchards. Experiments were conducted during the 2013 and 2014 growing seasons in walnut (Juglans regia) and almond (Prunus dulcis) orchards. The system was found to be reliable and capable of providing real-time visualization of the data remotely, with minimal technical problems. Leaf monitor data were used to develop modified crop water stress index (MCWSI) values for quantifying plant water stress levels.