| Título |
Stereo-vision solution for measuring Plant Area Index in high tunnel crops |
| Autores |
TAPIA CÓRDOBA, ALEJANDRO, ORIHUELA ESPINA, DIEGO LUIS, ROMAINE, JAMES BRIAN, SALVADOR ORTIZ, JOSÉ RAMÓN |
| Publicación externa |
No |
| Medio |
IFAC PAPERSONLINE |
| Alcance |
Proceedings Paper |
| Naturaleza |
Científica |
| Impacto SJR |
0.354 |
| Web |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144823622&doi=10.1016%2fj.ifacol.2022.11.133&partnerID=40&md5=f9b31177bce835860b52e3dfbbd13197 |
| Fecha de publicacion |
22/11/2022 |
| ISI |
000889052400029 |
| Scopus Id |
2-s2.0-85144823622 |
| DOI |
10.1016/j.ifacol.2022.11.133 |
| Abstract |
In this work, a cost-effective prototype is designed to automate the determination of the Plant Area Index (PAI) and its transmission to the cloud in high tunnel crops. In these installations, the impossibility of using satellite or aerial drones imagery constitute a limitation for the application of traditional orthogonal imagery analysis, and thus image capture routines are required to be manually assisted for scaling and perspective correction. As an alternative to this laborious procedure, the proposed solution makes use of stereo-image analysis to gather depth information to assist the calculation of PAI. To this end, an ad-hoc node has been fully designed, exploiting the computational capabilities of a single board computer and the low energy consumption of a microcontroller. The performance of the device is validated experimentally in a preliminary deployment in the gardens of Universidad Loyola Andalucia. Copyright (C) 2022 The Authors. |
| Palabras clave |
Image analysis in agriculture; Stero-vision; Crop monitoring; Hardware/software co-design; Internet of things |
| Miembros de la Universidad Loyola |
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