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All issues Volume 430 (2023) E3S Web Conf., 430 (2023) 01165 References
Open Access
Issue
E3S Web Conf.
Volume 430, 2023
15th International Conference on Materials Processing and Characterization (ICMPC 2023)
Article Number 01165
Number of page(s) 12
DOI https://doi.org/10.1051/e3sconf/202343001165
Published online 06 October 2023
  1. S. Vashisht, Swati, Praveen Kumar, and Munesh Chandra Trivedi. “Design of a predictive measure to enhance neural network architecture for plant disease detection.” Proceedings of International Conference on Big Data, Machine Learning and their Applications: ICBMA 2019. Springer Singapore, 2021. [Google Scholar]
  2. S. Vashisht, P. Kumar and M. C. Trivedi, “Improvised Extreme Learning Machine for Crop Yield Prediction,” 2022 3rd International Conference on Intelligent Engineering and Management (ICIEM), London, United Kingdom, 2022, pp. 754-757, doi: 10.1109/ICIEM54221.2022.9853054. [Google Scholar]
  3. M. Kalimuthu, P. Vaishnavi and M. Kishore, “Crop Prediction using Machine Learning,” 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT), Tirunelveli, India, 2020, pp. 926-932, doi: 10.1109/ICSSIT48917.2020.9214190. [CrossRef] [Google Scholar]
  4. Bhojwani, Yash, et al. “Crop selection and IoT based monitoring system for precision agriculture.” 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE). IEEE, 2020. [Google Scholar]
  5. Yoon, C., Huh, M., Kang, S. G., Park, J., & Lee, C. (2018, February). Implement smart farm with IoT technology. In 2018 20th International Conference on Advanced Communication Technology (ICACT) (pp. 749-752). IEEE. [Google Scholar]
  6. Aliar, Ahamed Ali Samsu, et al. “A comprehensive analysis on IoT based smart farming solutions using machine learning algorithms.” Bulletin of Electrical Engineering and Informatics 11.3 (2022): 1550-1557. [CrossRef] [Google Scholar]
  7. K. S. P Reddy, Y. M. Roopa, K. Rajeev L. N. and N. S. Nandan, “IoT based Smart Agriculture using Machine Learning,” 2020 Second I [Google Scholar]
  8. nternational Conference on Inventive Research in Computing Applications (ICIRCA), 2020pp.130-134 doi: 10.1109/ICIRCA48905.2020.9183373. [Google Scholar]
  9. M. Roopaei, P. Rad and K. R. Choo, “Cloud of Things in Smart Agriculture: Intelligent Irrigation Monitoring by Thermal Imaging,” IEEE Cloud Computing, vol. 4, no. 1, pp. 10-15, Jan.-Feb. 2017, doi: 10.1109/MCC.2017.5. [CrossRef] [Google Scholar]
  10. Gaikwad, Sandeep V., et al. “An innovative IoT-based system for precision farming.” Computers and Electronics in Agriculture 187 (2021): 106291. [CrossRef] [Google Scholar]
  11. Ghandar, Adam, et al. “A decision support system for urban agriculture using digital twin: A case study with aquaponics.” Ieee Access 9 (2021): 35691-35708. [11] Codeluppi, Gaia, et al. “LoRaFarM: A LoRaWAN-based smart farming modular IoT architecture.” Sensors 20.7 (2020): 2028. [CrossRef] [Google Scholar]
  12. Jain, Aman, and Abhay Kumar. “Smart agriculture monitoring system using IoT.” International Journal for Research in Applied Science & Engineering Technology (2020). [Google Scholar]
  13. Lavanya, G., Chellasamy Rani, and Pugalendhi GaneshKumar. “An automated low-cost IoT based Fertilizer Intimation System for smart agriculture.” Sustainable Computing: Informatics and Systems 28 (2020): 100300. [CrossRef] [Google Scholar]
  14. Cicioğlu, Murtaza, and Ali Çalhan. “Smart agriculture with the Internet of things in cornfields.” Computers & Electrical Engineering 90 (2021): 106982. [CrossRef] [Google Scholar]
  15. Marwa, Chandoul, Soufiene Ben Othman, and Hedi Sakli. “IoT-based low-cost weather station and monitoring system for smart agriculture.” 2020 20th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA). IEEE, 2020. [Google Scholar]
  16. Rajesh, T., Y. Thrinayana, and D. Srinivasulu. “IoT-based smart agriculture monitoring system.” International Journal of Scientific Engineering and Research (IJSER) (2020). [Google Scholar]
  17. Karthikeyan, P. R., et al. “IoT-based moisture control and temperature monitoring in smart farming.” Journal of Physics: Conference Series. Vol. 1964. No. 6. IOP Publishing, 2021. [Google Scholar]
  18. Rehman, Abdul, et al. “Machine learning prediction analysis using IoT for smart farming.” Int J 8.9 (2020). [Google Scholar]

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