The coffee crop monitoring system based on dense sensory information is a research project consisting of several low-cost lidar sensors which are used to perform 3D space reconstructions from obtaining points and lines detected by the sensors. Regarding the configuration of the system, 2D sensors were used to capture the data due to their low cost compared to 3D, however, as data was required in the third dimension, a series of motors was configured that allowed the movement of the sensor and the capture of data in space.
After the configuration of the system begins the spatial perceptual simulation process of the human being, which is the registration of internal places such as corners or centers in a laboratory, then next to classification networks and the aforementioned identification is made of the most relevant places in the environment in order to send relevant information to mobile robots or people.
With respect to the above and recalling the objective of the research which is to create a system that provides geographic information on coffee crops, a map will be generated that will provide farmers with information on the amount of harvest expected and characteristics such as health. of the crop in terms of minerals in real time.
