Proceedings
Authors
| Filter results6 paper(s) found. |
|---|
1. Sound Based Detection Of Moths In Open FieldsIntroduction Open field farming of tomatoes suffers from the presence of harmful moths whose larvas are devastating. Detecting automatically the presence of moths allows regulating the use of pesticides, according to the actual population present in the field. Up to now, sex pheromone traps have been used, the number of captured insects giving some indication about the population. However, proper inspection of the traps is... F. Rossant, J. Orensanz, D. Boisgontier, N. Bouhlel, M. Lagarrigue |
2. How Digital is Agriculture in South America? Adoption and LimitationsA rapidly growing population in a context of land and water scarcity, and climate change has driven an increase in healthy, nutritious, and affordable food demand while maintaining the current cropping area. Digital agriculture (DA) can contribute solutions to meet the demands in an efficient and sustainable way. South America (SA) is one of the main grain and protein producers in the world but the status of DA in the region is unknown. This article presents the results from a systematic review... G. Balboa, L. Puntel, R. Melchiori, R. Ortega, G. Tiscornia, E. Bolfe, A. Roel, F. Scaramuzza, S. Best, A. Berger, D. Hansel, D. Palacios |
3. Securing Agricultural Data with Encryption Algorithms on Embedded GPU Based Edge Computing DevicesSmart Agriculture (SA) has captured the interest of both the agricultural business and the scientific community in recent years. Overall, SA aims to help the agricultural and food industry to avoid crop failures, loss of revenues as well as help farmers use inputs (such as fertilizers and pesticides) more efficiently by utilizing Internet of Things (IoT) devices and computing systems. However, rapid digitization and reliance on data-driven technologies create new security threats that can defeat... M. Alahe, J.O. Kemeshi, Y. Chang, K. Won, X. Yang, M. Sher |
4. Agronomist-in-the-Loop Semantic 3D Reconstruction of Cotton Boll Morphology from UAV Imagery for Precision AgricultureStandard aerial photogrammetry is failing precision agriculture in one specific area: the detailed morphological assessment of complex, cluttered canopies. While creating a field-level map is trivial, recovering the geometry of a single cotton boll from a drone altitude of 30 meters is often mathematically intractable for standard Structure-from-Motion (SfM) solvers. These traditional pipelines depend on pixel-perfect consistency, which breaks down amidst... P. Sundaravadivel, H. Manjunatha, S. Borah, A. Anand, A. Price, H. Torbert, L. Tamil, T. Stroud |
5. A Multimodal Spectral-Robustness-LLM Pipeline for Non-Destructive Identification of Loropetalum chinense CultivarsProprietary cultivars of ornamental shrub Loropetalum chinense, particularly the visually and spectrally similar ‘Cerise Charm’, ‘Purple Daybreak’, and ‘Red Diamond’, derive their market value from the intensity and stability of anthocyanin pigmentation, a trait that degrades subtly under abiotic stress. Reliance on manual (visual) grading makes the industry vulnerable to these latent, pre-manifestation pigment losses, which are often detected only... P. Sundaravadivel, S. Borah, H. Manjunatha, S.P. Kumpatla, L. Tamil, P. Knight, T. Stroud |
6. Smart Resource Use in Precision Agriculture: A Conceptual Framework for Digital Sustainability DevelopmentDigital and precision agriculture are expected to play a central role in shaping future sustainable food production systems by enabling more intelligent, adaptive, and resource-efficient practices. This study adopted a forward-looking literature review, composed of bibliometric and systematic aspects, to propose Smart Resource Use as an emerging paradigm for sustainable development in digitally enabled precision agriculture, extending the concept of smart consumption beyond its traditional origins... B.B. Gallo, L. Visintainer Lerman, R.F. Da Silva, E. Bolfe, M.M. Da Silva, T. Alves, C.E. Pereira, T.M. Porcino |