2019
Authors
Moura, P; Ribeiro, D; dos Santos, FN; Gomes, A; Baptista, R; Cunha, M;
Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract
Viticulturists need to obtain the estimation of productivity map during the grape vine harvesting, to understand in detail the vineyard variability. An accurate productivity map will support the farmer to take more informed and accurate intervention in the vineyard in line with the precision viticulture concept. This work presents a novel solution to measure the productivity during vineyard harvesting operation realized by a grape harvesting machine. We propose 2D LIDAR sensor attached to low cost IoT module located inside the harvesting machine, to estimate the volume of grapes. Besides, it is proposed data methodology to process data collected and productivity map, considering GIS software, expecting to support the winemakers decisions. A PCD map is also used to validate the method developed by comparison. © Springer Nature Switzerland AG 2019.
The access to the final selection minute is only available to applicants.
Please check the confirmation e-mail of your application to obtain the access code.
