Open Access
| Issue |
BIO Web Conf.
Volume 199, 2025
2nd International Graduate Conference on Smart Agriculture and Green Renewable Energy (SAGE-Grace 2025)
|
|
|---|---|---|
| Article Number | 01002 | |
| Number of page(s) | 12 | |
| Section | Agricultural Technology and Smart Farming | |
| DOI | https://doi.org/10.1051/bioconf/202519901002 | |
| Published online | 05 December 2025 | |
- F. Zito,N.I. Giannoccaro, S. Strazzella, Analysis and development of an IoT system for an agrivoltaics plant, Technol. 12, 106 (2024). https://doi.org/10.3390/technologies12070106 [Google Scholar]
- Vallejo-Gómez, D.; Osorio, M.; Hincapié, C.A. Smart Irrigation Systems in Agriculture: A Systematic Review. Agronomy 2023, 13, 342. https://doi.org/10.3390/agronomy13020342 [CrossRef] [Google Scholar]
- H.M. Panhwar, Md K. Mia, A. Brohi, T. Brohi, Md N. Hossain, Integration of renewable energy into present and future energy systems, Energy Rep. 8, 1391–1401 (2022). https://doi.org/10.1016/j.egyr.2021.12.067 [Google Scholar]
- MASE – Ministero dell’Ambiente e della Sicurezza Energetica, Linee guida in materia di impianti agrivoltaici, (2022). https://www.mase.gov.it [Google Scholar]
- M. Trommsdorff, P.E. Campana, J. Macknick, Á. Fernández Solas, S. Gorjian, I. Tsanakas, Dual Land Use for Agriculture and Solar Power Production: Overview and Performance of Agrivoltaic Systems, IEA PVPS Task 13 Report T13-29:2025 (2025). https://doi.org/10.69766/XAEU5008 [Google Scholar]
- E. Symeonaki, K. Arvanitis, D. Piromalis, A Context-Aware Middleware Cloud Approach for Integrating Precision Farming Facilities into the IoT toward Agriculture 4.0, Appl. Sci. 10(3), 813 (2020). https://doi.org/10.3390/app10030813 [Google Scholar]
- A. Samsudin, N.M. Saad, A.R. Abdullah, K. Jaffar, N.A. Hamid, S.S. Ramli, I. Irianto, Solar Powered Automated Fertigation System (I-SIRAM), Int. J. Electr. Eng. Appl. Sci. 6(1) (2023). https://doi.org/10.54554/ijeeas.2023.6.01.002 [Google Scholar]
- Amazon Web Services, AWS Overview. Available online: https://aws.amazon.com/what-is-aws (accessed June 2025). [Google Scholar]
- LoRa Alliance™, “LoRaWAN® 1.0.4 Specification,” July 2020. Available online: https://lora-alliance.org/resource_hub/lorawan-specification-v1-0-4/ [Google Scholar]
- FAO, Irrigation techniques for small-scale farmers, FAO (2000). https://www.fao.org/4/a1336e/a1336e16.pdf [Google Scholar]
- A. Sivasankari, E. Eniya, D.B. Shanmugam, Implementation of automated organic fertigation system by measuring the plant parameters. Int. Res. J. Eng. Technol. 6, 2 (2019). https://www.irjet.net/archives/V6/i2/IRJET-V6I2160.pdf [Google Scholar]
- S. Shekhar, M. Durgam, S. Khose, C. Pohshna, D. Bhalekar, Advancement and Challenges of Implementing Artificial Intelligence of Things in Precision Agriculture. In: M. Kumar, A. Manogaran, R. Chilamkurti (eds.), Artificial Intelligence Techniques in Smart Agriculture, Springer, Singapore (2024), pp. 217–236. https://doi.org/10.1007/978-981-97-5878-4_13J [Google Scholar]
- T.S.T. Tanaka, G.B.M. Heuvelink, T. Mieno, D.S. Bullock, Can machine learning models provide accurate fertilizer recommendations? Precis. Agric. 25, 1839–1856 (2024). https://doi.org/10.1007/s11119-024-10136-x [Google Scholar]
- J. Deone, K.R. Afreen, R. Mangrule, Machine learning approaches for crop prediction and fertilizer recommendation based on soil nutrients. J. Environ. Sci. 12, 45–58 (2024). [Google Scholar]
- S. G. Shashidar, T. Sri Rekha, Y. S. Sundram, S. Vijayanand, SAF: Microirrigation and fertigation for precision agriculture. Int. J. Creat. Res. Thoughts 12, 45–58 (2024) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

