DEVELOPMENT OF NEW SENSORS AND TECHNOLOGIES FOR PRECISION AGRICULTURE

Vesna Radojčić ,
Vesna Radojčić
Contact Vesna Radojčić

University Sinergija , Bijeljina , Bosnia and Herzegovina

Aleksandar Sandro Cvetković
Aleksandar Sandro Cvetković

University Sinergija , Bijeljina , Bosnia and Herzegovina

Received: 15.03.2023.

Accepted: 17.04.2023. >>

Published: 29.05.2023.

Volume 5, Issue 1 (2023)

pp. 44-49;

https://doi.org/10.7251/STED2305044R

Abstract

Precision agriculture is becoming increasingly important in modern agriculture as it allows farmers to optimize production and increase yields. This includes the use of sensors and technologies to collect and analyze data on soil, crops, weather, and other relevant factors. However, existing technology still has limitations such as accuracy and coverage over large areas. In order to solve this, new sensors and technologies are being developed, especially those based on artificial intelligence and machine learning, which allow for greater accuracy in data collection. In addition, new technologies such as drones and satellite imagery are being used to map crops and optimize agricultural production. This paper analyzes some of the latest developments in precision agriculture, providing insight into the future development and application of this technology. This work is particularly relevant to farmers, researchers, and companies involved in the development of sensors and technologies for precision agriculture.

Keywords

References

Agriculture, G. (2022). What types of sensors are used in precision agriculture?
Agro, D. (2022). Revolucija poljoprivrede precizna poljoprivreda.
Elashmawy, R., & Uysal, I. (2023). Precision Agriculture Using Soil Sensor Driven Machine Learning for Smart Strawberry Production. *Sensors*, 23(4), 2247. https://doi.org/10.3390/s23042247.
Kumar, S. A., & Ilango, P. (2018). The impact of wireless sensor network in the field of precision agriculture: A review. *Wireless Personal Communications*, 98, 685–698. https://doi.org/10.1007/s11277-017-4890-z.
Liaghat, S., & Balasundram, S. K. (2010). A review: The role of remote sensing in precision agriculture. *American Journal of Agricultural and Biological Sciences*, 5(1), 50–55. https://doi.org/10.3844/ajabssp.2010.50.55.
Murugamani, C., Shitharth, S., Hemalatha, S., Kshirsagar, P. R., Riyazuddin, K., Naveed, Q. N., Islam, S., Ali, S. P. M., & Batu, A. (2022). Machine learning technique for precision agriculture applications in 5G-based internet of things. *Wireless Communications and Mobile Computing*, 2022(6534238). https://doi.org/10.1155/2022/6534238.
Qiao, Y., Valente, J., Zhang, Z., Su, D., & He. (2022). *AI, sensors and robotics in plant phenotyping and precision agriculture* (Vol. 16648714). https://doi.org/10.3389/fpls.2022.1064219.
Rehman, A., Abbasi, A. Z., Islam, N., & Shaikh, Z. A. (2014). A review of wireless sensors and networks’ applications in agriculture. *Computer Standards & Interfaces*, 36(2), 263–270. https://doi.org/10.1016/j.csi.2011.03.004.
Sela, G. (2022). Precision Agriculture what is it and what’s out there.
Shaikh, T. A., Rasool, T., & Lone, F. R. (2022). Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming. *Computers and Electronics in Agriculture*, 198, 107119. https://doi.org/10.1016/j.compag.2022.107119.
Sharma, A., Jain, A., Gupta, P., & Chowdary, V. (2020). Machine learning applications for precision agriculture: A comprehensive review. *IEEE Access*, 9, 4843–4873. https://doi.org/10.1109/ACCESS.2020.3048415.

Citation

Copyright

All papers are licensed under a Creative Commons Attribution 4.0 International License

Article metrics

Google scholar: See link

The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Most read articles

Abstracting, Indexing & Archiving

Partners