With water resources constantly becoming scarcer, and 70% of freshwater used for the agriculture sector, there is a growing need for innovative methods to increase water use efficiency (WUE) of food production systems and provide nutrient-dense food to an increasing population. Sensor technology has recently been introduced to the horticulture industry to increase resource use efficiency and minimize the environmental impacts of excessive water use. Identifying the effects of irrigation levels on crop performance is crucial for the success of sensor-based water management. This research aimed to optimize WUE in a soilless microgreen production system through identification of an optimal irrigation level using a sensor that could facilitate the development of a more efficient, low-cost automated irrigation system. A dielectric moisture sensor was implemented to monitor water levels at five irrigation setpoints: 7.5, 17.5, 25, 30, and 35 percent of the effective volume of the container (EVC) during a 14-day growth cycle. To validate the sensor performance, the same irrigation levels were applied to a parallel trial, without sensor, and water levels were monitored gravimetrically. Plant water status and stress reaction were evaluated using infrared thermal imaging, and the accumulation of osmolytes (proline) was determined. Results showed that, proline concentration, canopy temperature (Tc), canopy temperature depression (CTD), and crop water stress index (CWSI) increased at 7.5% EVC in both sensor-based and gravimetric treatments, and infrared index (Ig) and fresh yield decreased. The dielectric moisture sensor was effective in increasing WUE. The irrigation level of 17.5% EVC was found to be optimal. It resulted in a WUE of 88 g/L, an improvement of 30% over the gravimetric method at the same irrigation level. Furthermore, fresh yield increased by 11.5%. The outcome of this study could contribute to the automation of precision irrigation in hydroponically grown microgreens.