H. Nurwarsito, D. Suprayogo, S. P. Sakti, Cahyo Prayogo, Simon Oakley, A. Wibawa, Resnu Wahyu Adaby
{"title":"利用 LoRaWAN 和物联网技术开发咖啡-松树农林业小气候数据记录仪","authors":"H. Nurwarsito, D. Suprayogo, S. P. Sakti, Cahyo Prayogo, Simon Oakley, A. Wibawa, Resnu Wahyu Adaby","doi":"10.18196/jrc.v5i1.20991","DOIUrl":null,"url":null,"abstract":"Microclimate monitoring in agroforestry is very important to understand the complex interactions between vegetation, soil, and the environment. Microclimate parameters include air and soil temperature, air humidity, soil moisture, and light intensity. This research aims to develop a new microclimate data recording system for coffee-pine agroforestry, utilizing LoRaWAN and IoT technology to capture real-time microclimate parameters. Unlike traditional data loggers that require manual download on-site, this innovative system enables instant data download from IoT servers, thereby increasing data efficiency and accessibility. The system proved effective, significantly improving the precision of air temperature and humidity, as well as soil temperature measurements, with an average accuracy of 100%. However, soil moisture and light intensity recorded lower accuracies of 81.23% and 82.56%, respectively, indicating potential areas for future research and system refinement. The system maintains a 15-minute sampling period, aligning with conventional datalogger intervals. This represents an advancement in precision agriculture for microclimate monitoring, enabling the data to be utilized in decision-making for agroforestry management, which involves complex interactions between the local microclimate and the broader ecological system. It underscores the significance of sustainable land use as a response to global climate change.","PeriodicalId":443428,"journal":{"name":"Journal of Robotics and Control (JRC)","volume":"25 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of Microclimate Data Recorder on Coffee-Pine Agroforestry Using LoRaWAN and IoT Technology\",\"authors\":\"H. Nurwarsito, D. Suprayogo, S. P. Sakti, Cahyo Prayogo, Simon Oakley, A. Wibawa, Resnu Wahyu Adaby\",\"doi\":\"10.18196/jrc.v5i1.20991\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Microclimate monitoring in agroforestry is very important to understand the complex interactions between vegetation, soil, and the environment. Microclimate parameters include air and soil temperature, air humidity, soil moisture, and light intensity. This research aims to develop a new microclimate data recording system for coffee-pine agroforestry, utilizing LoRaWAN and IoT technology to capture real-time microclimate parameters. Unlike traditional data loggers that require manual download on-site, this innovative system enables instant data download from IoT servers, thereby increasing data efficiency and accessibility. The system proved effective, significantly improving the precision of air temperature and humidity, as well as soil temperature measurements, with an average accuracy of 100%. However, soil moisture and light intensity recorded lower accuracies of 81.23% and 82.56%, respectively, indicating potential areas for future research and system refinement. The system maintains a 15-minute sampling period, aligning with conventional datalogger intervals. This represents an advancement in precision agriculture for microclimate monitoring, enabling the data to be utilized in decision-making for agroforestry management, which involves complex interactions between the local microclimate and the broader ecological system. It underscores the significance of sustainable land use as a response to global climate change.\",\"PeriodicalId\":443428,\"journal\":{\"name\":\"Journal of Robotics and Control (JRC)\",\"volume\":\"25 2\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Robotics and Control (JRC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18196/jrc.v5i1.20991\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Robotics and Control (JRC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18196/jrc.v5i1.20991","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development of Microclimate Data Recorder on Coffee-Pine Agroforestry Using LoRaWAN and IoT Technology
Microclimate monitoring in agroforestry is very important to understand the complex interactions between vegetation, soil, and the environment. Microclimate parameters include air and soil temperature, air humidity, soil moisture, and light intensity. This research aims to develop a new microclimate data recording system for coffee-pine agroforestry, utilizing LoRaWAN and IoT technology to capture real-time microclimate parameters. Unlike traditional data loggers that require manual download on-site, this innovative system enables instant data download from IoT servers, thereby increasing data efficiency and accessibility. The system proved effective, significantly improving the precision of air temperature and humidity, as well as soil temperature measurements, with an average accuracy of 100%. However, soil moisture and light intensity recorded lower accuracies of 81.23% and 82.56%, respectively, indicating potential areas for future research and system refinement. The system maintains a 15-minute sampling period, aligning with conventional datalogger intervals. This represents an advancement in precision agriculture for microclimate monitoring, enabling the data to be utilized in decision-making for agroforestry management, which involves complex interactions between the local microclimate and the broader ecological system. It underscores the significance of sustainable land use as a response to global climate change.