{"title":"基于物联网和LoRa的海洋监测的TRITON-Open遥测和位置估计","authors":"Marko Radeta;João Pestana;Pedro Abreu;Rúben Freitas;Francisco Silva;Dinarte Vieira;Rui Prieto;Marc Fernandez;Filipe Alves;Thomas Dellinger;Silvana Neves;Eric Delory","doi":"10.1109/JOE.2024.3441819","DOIUrl":null,"url":null,"abstract":"Biologging and biotelemetry are essential tools to better understand marine species and consequently contribute to increasing our knowledge of marine ecosystems as a whole. Assessing marine megafauna trajectories is traditionally performed with significantly high cost and labor, without guaranteeing the equipment recapture, where quick georeferencing techniques remain proprietary and power intensive. The Internet of Things (IoT) and open radio communication protocols, such as long range (LoRa), provide opportunities for the creation of robust and low-cost sensor networks, which still need to be further tested in the harsh oceanic environment and on marine species. With a vision on having their real-life application on marine species, this study provides a fourfold contribution with LoRa and IoT. First, we review current biotelemetry and biologging, outlining opportunities. Second, we present TRITON, an open telemetry sensor for marine megafauna monitoring. Third, we provide a novel location estimation pipeline based on assisted GPS and simplified pseudorange multilateration using raw satellite data. Fourth, we validate the location estimation pipeline with four in-the-wild studies, mimicking the behavior of marine species, obtaining <inline-formula><tex-math>$\\text{500}\\;\\text{m}$</tex-math></inline-formula> grand average error, using seven satellites. We discuss how the TRITON system may be leveraged for long- and short-term marine megafauna monitoring, paving the road for more LoRa and IoT biotelemetry applications.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"50 2","pages":"1244-1258"},"PeriodicalIF":3.8000,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10807074","citationCount":"0","resultStr":"{\"title\":\"TRITON—Open Telemetry and Location Estimation for Marine Monitoring Based on IoT and LoRa\",\"authors\":\"Marko Radeta;João Pestana;Pedro Abreu;Rúben Freitas;Francisco Silva;Dinarte Vieira;Rui Prieto;Marc Fernandez;Filipe Alves;Thomas Dellinger;Silvana Neves;Eric Delory\",\"doi\":\"10.1109/JOE.2024.3441819\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Biologging and biotelemetry are essential tools to better understand marine species and consequently contribute to increasing our knowledge of marine ecosystems as a whole. Assessing marine megafauna trajectories is traditionally performed with significantly high cost and labor, without guaranteeing the equipment recapture, where quick georeferencing techniques remain proprietary and power intensive. The Internet of Things (IoT) and open radio communication protocols, such as long range (LoRa), provide opportunities for the creation of robust and low-cost sensor networks, which still need to be further tested in the harsh oceanic environment and on marine species. With a vision on having their real-life application on marine species, this study provides a fourfold contribution with LoRa and IoT. First, we review current biotelemetry and biologging, outlining opportunities. Second, we present TRITON, an open telemetry sensor for marine megafauna monitoring. Third, we provide a novel location estimation pipeline based on assisted GPS and simplified pseudorange multilateration using raw satellite data. Fourth, we validate the location estimation pipeline with four in-the-wild studies, mimicking the behavior of marine species, obtaining <inline-formula><tex-math>$\\\\text{500}\\\\;\\\\text{m}$</tex-math></inline-formula> grand average error, using seven satellites. We discuss how the TRITON system may be leveraged for long- and short-term marine megafauna monitoring, paving the road for more LoRa and IoT biotelemetry applications.\",\"PeriodicalId\":13191,\"journal\":{\"name\":\"IEEE Journal of Oceanic Engineering\",\"volume\":\"50 2\",\"pages\":\"1244-1258\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10807074\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Journal of Oceanic Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10807074/\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Oceanic Engineering","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10807074/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
TRITON—Open Telemetry and Location Estimation for Marine Monitoring Based on IoT and LoRa
Biologging and biotelemetry are essential tools to better understand marine species and consequently contribute to increasing our knowledge of marine ecosystems as a whole. Assessing marine megafauna trajectories is traditionally performed with significantly high cost and labor, without guaranteeing the equipment recapture, where quick georeferencing techniques remain proprietary and power intensive. The Internet of Things (IoT) and open radio communication protocols, such as long range (LoRa), provide opportunities for the creation of robust and low-cost sensor networks, which still need to be further tested in the harsh oceanic environment and on marine species. With a vision on having their real-life application on marine species, this study provides a fourfold contribution with LoRa and IoT. First, we review current biotelemetry and biologging, outlining opportunities. Second, we present TRITON, an open telemetry sensor for marine megafauna monitoring. Third, we provide a novel location estimation pipeline based on assisted GPS and simplified pseudorange multilateration using raw satellite data. Fourth, we validate the location estimation pipeline with four in-the-wild studies, mimicking the behavior of marine species, obtaining $\text{500}\;\text{m}$ grand average error, using seven satellites. We discuss how the TRITON system may be leveraged for long- and short-term marine megafauna monitoring, paving the road for more LoRa and IoT biotelemetry applications.
期刊介绍:
The IEEE Journal of Oceanic Engineering (ISSN 0364-9059) is the online-only quarterly publication of the IEEE Oceanic Engineering Society (IEEE OES). The scope of the Journal is the field of interest of the IEEE OES, which encompasses all aspects of science, engineering, and technology that address research, development, and operations pertaining to all bodies of water. This includes the creation of new capabilities and technologies from concept design through prototypes, testing, and operational systems to sense, explore, understand, develop, use, and responsibly manage natural resources.