"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 April 5 and 6, air quality data was collected in the Maniago area. The area was selected with the aim of assessing the potential impact of wood/pallet stoves on air quality. For the data collection was used the "Cocal" system. The “Cocal” IoT system is a real-time and low-cost air quality Vehicle Sensor Network that covers the whole path from data acquisition to data access and web-mapping. Cocal consists of a set of crowdsensing low-cost IoT devices installed on voluntary mobile platforms, such as private cars and buses from the local transportation authority Trieste Trasporti. Each platform acquires geolocated environmental measurements (PM10, PM2.5, temperature, pressure, relative humidity...) which are transmitted via GSM and LoRaWAN to an IT infrastructure able to reconstruct in real time a web based interactive geographic map of the distribution of pollutants. The entire system uses open source software and hardware and all the data that has been collected is completely open and accessible within a FAIR perspective.

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.

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.

The “Cocal” IoT system is a real-time and low-cost air quality Vehicle Sensor Network that covers the whole path from data acquisition to data access and web-mapping. Cocal consists of a set of crowdsensing low-cost IoT devices installed on voluntary mobile platforms, such as private cars and buses from the local transportation authority Trieste Trasporti. Each platform acquires geolocated environmental measurements (PM10, PM2.5, temperature, pressure, relative humidity...) which are transmitted via GSM and LoRaWAN to an IT infrastructure able to reconstruct in real time a web based interactive geographic map of the distribution of pollutants. The entire system uses open source software and hardware and all the data that has been collected is completely open and accessible within a FAIR perspective.

On April 5 and 6, air quality data was collected in the Maniago area. The area was selected with the aim of assessing the potential impact of wood/pallet stoves on air quality. For the data collection was used the "Cocal" system. The “Cocal” IoT system is a real-time and low-cost air quality Vehicle Sensor Network that covers the whole path from data acquisition to data access and web-mapping. Cocal consists of a set of crowdsensing low-cost IoT devices installed on voluntary mobile platforms, such as private cars and buses from the local transportation authority Trieste Trasporti. Each platform acquires geolocated environmental measurements (PM10, PM2.5, temperature, pressure, relative humidity...) which are transmitted via GSM and LoRaWAN to an IT infrastructure able to reconstruct in real time a web based interactive geographic map of the distribution of pollutants. The entire system uses open source software and hardware and all the data that has been collected is completely open and accessible within a FAIR perspective.

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.

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.