Estimation of Vineyard Productivity Map Considering a Cost-Effective LIDAR-Based Sensor

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

Pedro Moura (Author) Other; Daniela Ribeiro (Author) Other; Filipe Neves dos Santos (Author) FEUP; António Alberto Gomes (Author) FLUP; Ricardo Baptista (Author) Other; Mário Cunha (Author) Other

Conference proceedings International

Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Pages: 121-133

19th EPIA Conference on Artificial Intelligence, EPIA 2019

3 September 2019 through 6 September 2019

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 3 Citations

Scientific classification

CORDIS: Social sciences > Geography

Other information

Authenticus ID: P-00R-039

DOI: 10.1007/978-3-030-30241-2_11

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13