A Network Infrastructure for Monitoring Coastal Environments and Study Climate Changes in Marine Systems

Abstract

Climate changes have a tremendous impact on coastal and littoral areas, strongly affected by seaquakes and floods. Moreover, global warming causes a drastic change on the biodiversity of rivers, seas, lakes, including in biodiversity hotspots and protected areas, such as the Venice Lagoon in Italy. A similar impact is caused by pollutants: this called for a largescale long-term action that aims to monitor aquatic environmental parameters in order to predict, manage and mitigate these effects. Yet, coastal systems are highly heterogeneous in space and variable over short (daily), medium and long (seasonal, interannual) timescales, making reliable but affordable monitoring a challenging task. This paper proposes to automate this process with the use of a low-power sustainable integrated underwater and above water Internet of Things sensor network, able to collect water measurements in a cloud database and make them available to researchers to monitor the status of a certain area and develop their predictions models. Simulation results highlight how Low-Power Wide-Area Networks can support the data collection from a dense sensor deployment.

LoRaWAN Transmissions in Salt Water for Superficial Marine Sensor Networking: Laboratory and Field Tests

“…Considering that the seawater salinity ranges between 31 g/L and 39 g/L, the results for configurations #7–#10 can be assumed representative of realistic deployments in marine water demonstrating that the transmission is feasible only with the receiver submerged by a few cm of water. This limits the use of this technology to almost superficial monitoring applications such as the monitoring of water sport athletes or tides warning systems, or in combination with other techniques with the aim of implementing hybrid networking [ 44 ].…”

IoT Innovations in Sustainable Water and Wastewater Management and Water Quality Monitoring: A Comprehensive Review of Advancements, Implications, and Future Directions

“…The literature reviewed on IoT-based water quality monitoring is categorized into two main categories. The first category comprises studies detailing developing and fabricating sensors explicitly designed to monitor water quality [55], [128]. For instance, Blanco-Gómez et al [129] designed a low-cost prototype device capable of continuously measuring electrical conductivity (EC) and temperature, while Abbas et al [130] developed a suite of sensors, including a water flow sensor, a waterproof ultrasonic sensor, and two temperature sensors, designed for the measurement of both water and ambient temperatures.…”

“…24, most of the reviewed studies utilized multiple sensors, with pH, temperature, and turbidity sensors being the most commonly used in combination with other types of sensors [32], [136], [137], [138]. For instance, Campagnaro et al [128] employed six different sensors, including temperature, pressure, pH, turbidity, dissolved oxygen, and EC sensors, while Kumar et al [135] utilized five different types of sensors, including temperature, pH, conductivity, dissolved oxygen, and Eh potential sensors, to measure different water quality parameters. Other frequently used sensor combinations include dissolved oxygen, conductivity, and water level sensors [128], [139].…”

“…For instance, Campagnaro et al [128] employed six different sensors, including temperature, pressure, pH, turbidity, dissolved oxygen, and EC sensors, while Kumar et al [135] utilized five different types of sensors, including temperature, pH, conductivity, dissolved oxygen, and Eh potential sensors, to measure different water quality parameters. Other frequently used sensor combinations include dissolved oxygen, conductivity, and water level sensors [128], [139]. However, the choice of sensors used in these studies varies depending on the specific application and variables being monitored.…”

“…25, a noteworthy trend among the reviewed studies is the use of cloud-based platforms for data storage and management. Several researchers, such as Al-Khashab et al [143] and Campagnaro et al [128], have emphasized the benefits of utilizing cloud-based platforms for collecting and analyzing sensor data. Additionally, various IoT platforms have been employed for data acquisition and transmission.…”