The suitable light environment could promote the photosynthetic rate of plants, increase the dry matter quality and then increase the fruit yield. In order to meet the adaptive regulation of greenhouse tomato light environment, a greenhouse tomato selfadaptive dimming system based on random forest-glowworm swarm optimization algorithm (RF-GSO) model was designed to realize the realtime collection of temperature, CO2 concentration and light intensity in greenhouse. At the same time, the information was transmitted to the software platform of greenhouse tomato selfadaptive dimming system through wireless sensor network. The platform could dynamically display the realtime ring. The ambient parameters could also realize the remote control of supplementary light. The ideal illumination intensity oftomato in greenhouse was calculated dynamically by RF-GSO algorithm, and the difference between the ideal illumination intensity and the measured illumination intensity of the sensor was taken as the control parameter to realize the adaptive control of the light environment of tomato in greenhouse. The experimental results showed that the determination coefficient R2 between the illumination intensity detected by the system and the target value of greenhouse dimming was 0.955, the root mean square error was 2.168μmol/(m2·s), and the system packet loss rate was 0.417%. It was showed that the adaptive dimming system of greenhouse tomato based on RF-GSO could achieve stable and reliable operation.