Abstract: The present disclosure relates to the technical field of growth environment control for plants, and provides a light regulation method, system, and apparatus for a growth environment of leafy vegetables. The method includes: obtaining a growth environment image and growth environment light parameters of leafy vegetables; inputting the growth environment image into an image segmentation model to obtain an initial pixel segmentation map; determining a leaf area of the leafy vegetables according to the initial pixel segmentation map by using a Class Activation Mapping (CAM)-K algorithm; inputting the leaf area and the growth environment light parameters of the leafy vegetables into a leafy vegetable growth index prediction model to obtain a growth index of the leafy vegetables; adjusting the growth environment light parameters according to the growth index of the leafy vegetables. This disclosure achieves automated and intelligent control of light conditions in the growth environment of leafy vegetables.

Abstract: The present disclosure relates to the technical field of aquafarm monitoring, and in particular to a method, system and apparatus for intelligently monitoring an aquafarm with multi-dimensional panoramic perception. The method includes: analyzing preprocessed multi-dimensional panoramic perception information with time series analysis to obtain a linear fitting model; constructing a water quality forecasting-alarming model according to the linear fitting model; inputting fused data to a convolutional neural network (CNN) for training to obtain an electrical device fault diagnosis model; and monitoring an aquafarm with the water quality forecasting-alarming model and the electrical device fault diagnosis model.