Smart Water Irrigation for Rice Farming through the Internet of Things
<|reference_start|>Smart Water Irrigation for Rice Farming through the Internet of Things: This study intends to build smart water irrigation for rice farming using IoT and microcontroller devices with solar panel support. The system demonstrates the capabilities of automated irrigation by reducing physical labor through smart monitoring of the temperature, soil moisture, and humidity using multiple sensors. This study uses an agile methodology as it is suitable for reiterative operation for the development of the prototype. The mean result for the interpretation of data gathered for the systems' adaptability and flexibility is 4.32. The researchers were able to develop smart water irrigation for rice farming using IoT and microcontroller devices with solar panel support and the respondents also agreed that Smart water irrigation for rice farming using IoT and microcontroller devices with solar panel support is practical and valuable. A decision support system is recommended that can analyze data collected from IoT sensors and provide further recommendations. Based on the results, it is also suggested that future researchers use drip irrigation, instead of flood irrigation. Smart water irrigation has the potential to revolutionize agriculture, enhance environmental sustainability, and address pressing global challenges related to water resources and food security. These implications highlight the importance of continued research and innovation in this field.<|reference_end|>
@article{binayao2024smart,
    title={Smart Water Irrigation for Rice Farming through the Internet of Things},
    author={Regie Porras Binayao, Paul Vincent Lagapa Mantua, Holy Rose May
  Pardillo Namocatcat, Jade Kachel Klient Bocboc Seroy, Phoebe Ruth Alithea
  Bacotot Sudaria, Kenn Migan Vincent Casicas Gumonan, Shiela Mae Malbas Orozco},
    journal={International Journal of Computing Sciences Research, 8, 2550-2563
  (2024)},
    year={2024},
    doi={10.25147/ijcsr.2017.001.1.172},
    archivePrefix={arXiv},
    eprint={2402.07917},
    primaryClass={cs.HC}
}