Weather Monitoring Station For Farms And Agriculture

This dataset includes the 3-day record (December 6 to December 8, 2020) of a plantation in the city of Guayaquil - Ecuador. This dataset includes the recording of the following variables: Relative Humidity, Environment Temperature, Soil moisture, Light intensity, and Rain Occurrence. An arduino uno module was used to record data, connected to the following sensors:DHT11, FC28, LDR and FC-37.The sampling frequency of one data every thirty seconds and with a resolution of 8 bits (UTF-8).⭐ When using this resource, please cite the original publication:V. Asanza, R. E. Pico, D. Torres, S. Santillan and J. Cadena, "FPGA Based Meteorological Monitoring Station," 2021 IEEE Sensors Applications Symposium (SAS), 2021, pp. 1-6, doi: 10.1109/SAS51076.2021.9530151.Read paper presentation:https://vasanza.blogspot.com/2021/10/fpga-based-meteorological-monitoring.html Source code repository:https://github.com/vasanza/Weather-Monitoring-StationReferences:Asanza V., Sanchez G., Cajo R., Peláez E. (2021) Behavioral Signal Processing with Machine Learning Based on FPGA. In: Botto-Tobar M., Zamora W., Larrea Plúa J., Bazurto Roldan J., Santamaría Philco A. (eds) Systems and Information Sciences. ICCIS 2020. Advances in Intelligent Systems and Computing, vol 1273. Springer, Cham. https://doi.org/10.1007/978-3-030-59194-6_17V. A. Armijos, N. S. Chan, R. Saquicela and L. M. Lopez, "Monitoring of system memory usage embedded in FPGA," 2020 International Conference on Applied Electronics (AE), Pilsen, Czech Republic, 2020, pp. 1-4, doi: 10.23919/AE49394.2020.9232863Cordova, R., Garcia, I. M., Munoz-Arcentales, A., Asanza, V., & Vargas, W. A. V. (2018). Modelo de red de comunicación que soporta un sistema de detección basado en criterios de robustez. IEEE Latin America Transactions, 16(10), 2600-2608

本数据集收录了位于厄瓜多尔瓜亚基尔市的种植园于2020年12月6日至12月8日三天的记录。数据集涵盖了以下变量：相对湿度、环境温度、土壤湿度、光照强度以及降雨发生情况。数据采集采用Arduino Uno模块，连接至DHT11、FC28、LDR及FC-37等传感器。采样频率为每三十秒一次，数据分辨率达到8位（UTF-8）。在使用本资源时，请引用原始出版物：V. Asanza, R. E. Pico, D. Torres, S. Santillan, J. Cadena, "基于FPGA的气象监测站," 2021 IEEE Sensors Applications Symposium (SAS), 2021, 第1-6页，doi: 10.1109/SAS51076.2021.9530151.阅读论文演示：https://vasanza.blogspot.com/2021/10/fpga-based-meteorological-monitoring.html 源代码仓库：https://github.com/vasanza/Weather-Monitoring-Station参考文献：Asanza V., Sanchez G., Cajo R., Peláez E. (2021) Behavioral Signal Processing with Machine Learning Based on FPGA. In: Botto-Tobar M., Zamora W., Larrea Plúa J., Bazurto Roldan J., Santamaría Philco A. (eds) Systems and Information Sciences. ICCIS 2020. Advances in Intelligent Systems and Computing, vol 1273. Springer, Cham. https://doi.org/10.1007/978-3-030-59194-6_17V. A. Armijos, N. S. Chan, R. Saquicela and L. M. Lopez, "Monitoring of system memory usage embedded in FPGA," 2020 International Conference on Applied Electronics (AE), Pilsen, Czech Republic, 2020, 第1-4页，doi: 10.23919/AE49394.2020.9232863Cordova, R., Garcia, I. M., Munoz-Arcentales, A., Asanza, V., & Vargas, W. A. V. (2018). Modelo de red de comunicación que soporta un sistema de detección basado en criterios de robustez. IEEE Latin America Transactions, 16(10), 2600-2608