The invention relates to the technical field of succulent planting, and discloses a multi-
modal large model analysis-based succulent planting auxiliary detection
system, which comprises a succulent planting auxiliary detection
system, the succulent planting auxiliary detection
system comprises a
data acquisition module, an intelligent diagnosis module, a personalized scheme module, an automatic maintenance module and an interaction and
community module, and the
data acquisition module captures succulent image data through a GOLDYOLO
algorithm. According to the succulent planting auxiliary detection system based on multi-mode
large model analysis, through fusion of a GOLDYOLO
algorithm and a multi-mode
large model, succulent image features and
environmental data are accurately captured,
disease early screening and growth state real-time monitoring are achieved, the diagnosis accuracy rate reaches 92% or above, losses caused by rotten roots,
powdery mildew and other problems are effectively reduced, and the system is suitable for popularization and application. A personalized maintenance scheme is generated by combining user work and rest and succulent variety characteristics, and is matched with convenient interaction functions such as APP terminal voice control and remote viewing to adapt to a family planting scene.