Map-matching methods in agriculture

• Tipo: Artigo em Revista Científica Internacional
• Data: 2024

Autores

Silva, A (Autor) Outra; João Mendes-Moreira (Autor) FEUP; Ferreira, C (Autor) Outra; Costa, N (Autor) Outra; Dias, D (Autor) Outra

Revista

Título: Computers and Electronics in Agriculture

Vol. 216

ISSN: 0168-1699

Editora: Elsevier

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00Z-E9P

DOI: 10.1016/j.compag.2023.108529

Abstract (EN): In this paper, a solution to monitor the location of humans during their activity in the agriculture sector with the aim to boost productivity and efficiency is provided. Our solution is based on map-matching methods, that are used to track the path spanned by a worker along a specific activity in an agriculture culture. Two different cultures are taken into consideration in this study olives and vines. We leverage the symmetry of the geometry of these cultures into our solution and divide the problem three-fold initially, we estimate a path of a worker along the fields, then we apply the map-matching to such path and finally, a post-processing method is applied to ensure local continuity of the sequence obtained from map-matching. The proposed methods are experimentally evaluated using synthetic and real data in the region of Mirandela, Portugal. Evaluation metrics show that results for synthetic data are robust under several sampling periods, while for real-world data, results for the vine culture are on par with synthetic, and for the olive culture performance is reduced.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 13