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    The “IoT system "Cocal" is a real-time and low-cost water quality vehicle sensor network that covers the entire path from data collection to data access and web mapping. Cocal consists of a series of low-cost crowdsensing IoT devices installed on volunteer mobile platforms, such as a private sailboat. Each platform collects geolocalized environmental measurements (pH, temperature, conductivity, dissolved oxygen, redox potential), which are transmitted via GSM and LoRaWAN to an IT infrastructure capable of reconstructing in near real-time a web-based interactive geographic map of the quality of the surface layer of the water column. The entire system uses open source software and hardware, and all data collected is fully open and accessible within a FAIR perspective.

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    "NoiXApp" is a crowdsourcing solution developed by the National Institute of Oceanography and Applied Geophysics - OGS to measure acoustic pollution in urban areas using the microphones of mobile phones. The solution is based on a mobile (Android and iOS) software application in which it is possible to acquire urban noise data performing the recording and calculation of the levels of the sound pressure. Georeferenced data are transmitted to the OGS infrastructure, the data are anonymized, integrated, validated and mapped onto an open-data web portal.

  • On February 15, 2023 an acquisition test with an Ocean Seven 310 multiparameter CTD was conduct in the Panzano Bay. This acquisition was carried out as part of a joint project between the University of Udine - Uniud and the National Institute of Oceanography and Applied Geophysics - OGS. The purpose of this acquisition was to test the tools that will be used on an Autonomous Surface Vehicles (ASV). The ASV will collect, process and communicate biochemical data about coastal transitional waters and ecosystem, focusing on the northern Adriatic Sea, with a particular regard to seagrass meadows detection.

  • The MBES NZ-water dataset was collected during the XXXVIII PNRA Italian Antarctic Expedition aboard R/V Laura Bassi in direct response to a request from New Zealand to acquire bathymetric data during transits within their waters. The acquisition of this valuable dataset was carried out by the ISOBatA Project team, utilizing a state-of-the-art multibeam EM304 system installed on the R/V Laura Bassi. The genesis of the MBES NZ-water dataset is deeply linked to the international collaborative effort aimed at mapping unexplored regions, exemplified by the Seabed 2030 Project. By aligning with New Zealand's research objectives, both the ISOBatA project and the Italian Antarctic Expedition epitomize their commitment to knowledge exchange and the advancement of scientific understanding on a global scale. The dataset not only serves as a fundamental resource for future research endeavors but also unveils new opportunities for scientists and researchers to delve into the profound depths of Southern Ocean knowledge. In its essence, the MBES NZ-water dataset stands as a milestone in IT-NZ scientific cooperation, driving Italian efforts in bathymetric data acquisition along transits

  • The MBES NZ-water dataset was collected during the XXXVIII PNRA Italian Antarctic Expedition aboard R/V Laura Bassi in direct response to a request from New Zealand to acquire bathymetric data during transits within their waters. The acquisition of this valuable dataset was carried out by the ISOBatA Project team, utilizing a state-of-the-art multibeam EM304 system installed on the R/V Laura Bassi. The genesis of the MBES NZ-water dataset is deeply linked to the international collaborative effort aimed at mapping unexplored regions, exemplified by the Seabed 2030 Project. By aligning with New Zealand's research objectives, both the ISOBatA project and the Italian Antarctic Expedition epitomize their commitment to knowledge exchange and the advancement of scientific understanding on a global scale. The dataset not only serves as a fundamental resource for future research endeavors but also unveils new opportunities for scientists and researchers to delve into the profound depths of Southern Ocean knowledge. In its essence, the MBES NZ-water dataset stands as a milestone in IT-NZ scientific cooperation, driving Italian efforts in bathymetric data acquisition along transits

  • Categories  

    The “IoT system "Cocal" is a real-time and low-cost water quality vehicle sensor network that covers the entire path from data collection to data access and web mapping. Cocal consists of a series of low-cost crowdsensing IoT devices installed on volunteer mobile platforms, such as a private sailboat. Each platform collects geolocalized environmental measurements (pH, temperature, conductivity, dissolved oxygen, redox potential), which are transmitted via GSM and LoRaWAN to an IT infrastructure capable of reconstructing in near real-time a web-based interactive geographic map of the quality of the surface layer of the water column. The entire system uses open source software and hardware, and all data collected is fully open and accessible within a FAIR perspective.

  • Categories  

    The “IoT system "Cocal" is a real-time and low-cost water quality vehicle sensor network that covers the entire path from data collection to data access and web mapping. Cocal consists of a series of low-cost crowdsensing IoT devices installed on volunteer mobile platforms, such as a private sailboat. Each platform collects geolocalized environmental measurements (pH, temperature, conductivity, dissolved oxygen, redox potential), which are transmitted via GSM and LoRaWAN to an IT infrastructure capable of reconstructing in near real-time a web-based interactive geographic map of the quality of the surface layer of the water column. The entire system uses open source software and hardware, and all data collected is fully open and accessible within a FAIR perspective.

  • Categories  

    The “IoT system "Cocal" is a real-time and low-cost water quality vehicle sensor network that covers the entire path from data collection to data access and web mapping. Cocal consists of a series of low-cost crowdsensing IoT devices installed on volunteer mobile platforms, such as a private sailboat. Each platform collects geolocalized environmental measurements (pH, temperature, conductivity, dissolved oxygen, redox potential), which are transmitted via GSM and LoRaWAN to an IT infrastructure capable of reconstructing in near real-time a web-based interactive geographic map of the quality of the surface layer of the water column. The entire system uses open source software and hardware, and all data collected is fully open and accessible within a FAIR perspective.