The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Scientific development of smart farming technologies and their application in Brazil
Open accessAbstract
Smart farming (SF) involves the incorporation of information and communication technologies into machinery, equipment, and sensors for use in agricultural production systems. New technologies such as the internet of things and cloud computing are expected to advance this development, introducing more robots and artificial intelligence into farming. Therefore, the aims of this paper are twofold: (i) to characterize the scientific knowledge about SF that is available in the worldwide scientific literature based on the main factors of development by country and over time and (ii) to describe current SF prospects in Brazil from the perspective of experts in this field. The research involved conducting semi-structured interviews with market and researcher experts in Brazil and using a bibliometric survey by means of data mining software. Integration between the different available systems on the market was identified as one of the main limiting factors to SF evolution. Another limiting factor is the education, ability, and skills of farmers to understand and handle SF tools. These limitations revealed a market opportunity for enterprises to explore and help solve these problems, and science can contribute to this process. China, the United States, South Korea, Germany, and Japan contribute the largest number of scientific studies to the field. Countries that invest more in R&D generate the most publications; this could indicate which countries will be leaders in smart farming. The use of both research methods in a complementary manner allowed to understand how science frame the SF and the mains barriers to adopt it in Brazil.
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Cited by
MITRA, D., MONDAL, R., KHOSHRU, B., SENAPATI, A., RADHA, T. K., MAHAKUR, B., UNIYAL, N., MYO, E. M., BOUTAJ, H., SIERRA, B. E. G., et al. (2022) · Pedosphere · doi:10.1016/s1002-0160(21)60042-5 · Cited by 281
A Systematic Survey on the Role of Cloud, Fog, and Edge Computing Combination in Smart Agriculture
Kalyani, Y., & Collier, R. (2021) · Sensors · doi:10.3390/s21175922 · Cited by 228
Fernandes, T., Magalhães, J. P., & Alves, W. (2025) · Green Energy and Intelligent Transportation · doi:10.1016/j.geits.2025.100305 · Cited by 23
Metadata
- Authors
- Pivoto, D., Waquil, P. D., Talamini, E., Finocchio, C. P. S., Dalla Corte, V. F., & de Vargas Mores, G.
- Venue
- Information Processing in Agriculture
- Publisher
- Elsevier BV
- Published
- 2018-03
- Volume
- 5
- Issue
- 1
- Pages
- 21-32
- ISSN
- 2214-3173 (ISSN-L)
- OpenAlex
- W2775040805
- Cited by
- 384
- References
- 30
- FWCI
- 22.20
- Type
- journal article
- Language
- en
- Open access
- gold
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- Pivoto, D., Waquil, P. D., Talamini, E., Finocchio, C. P. S., Dalla Corte, V. F., & de Vargas Mores, G. (2018). Scientific development of smart farming technologies and their application in Brazil. Information Processing in Agriculture. https://doi.org/10.1016/j.inpa.2017.12.002
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.