Monitoring the Venice Lagoon: An IoT Cloud-Based Sensor Network Approach

The impact of global warming is felt worldwide, but coastal regions are particularly vulnerable, and face rising sea levels, increased seaquakes, and floods. In addition, the ecosystems of rivers, seas and lakes undergo significant changes due to climate change and pollutants. Thus, monitoring coastal areas, such as the Venice Lagoon (Italy), is of significant importance. This article presents a novel floating wireless sensor system for measuring water-related parameters. The core of the system is the SENSWICH platform, which integrates sensors to measure pH, electrical conductivity, turbidity, dissolved oxygen, and water level. The platform uses long range wide area network (LoRaWAN) connectivity for long-range data collection, which is then aggregated in the Amazon Web Service cloud and visualized using Grafana. While the proposed architecture can be applied to any large-scale coastal, lakeside or riverine monitoring context, it is specifically designed for the Venice Lagoon. This article presents results from two SENSWICH platforms: one in the Piovego river, Padova, which is a tributary of the Venice Lagoon, and one in Chioggia, in the lagoon itself. Together with these results, an analysis for a full-scale deployment in the whole Venice Lagoon is proposed. The results show that SENSWICH, despite being a low-cost platform compared to similar technologies available on the market, enables pervasive monitoring of large water surfaces. It provides reliable datasets over prolonged periods and significantly reduces human resource requirements. The proposed software framework for data aggregation is effective for managing large quantities of data acquired using a LoRaWAN network and is user-friendly through the graphic tool.

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Publication Details

Journal
IEEE Journal of Oceanic Engineering
Published
2024-11-05
DOI
https://doi.org/10.1109/joe.2024.3459483
Citations
3
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.60
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article

Monitoring the Venice Lagoon: An IoT Cloud-Based Sensor Network Approach

Michele Zorzi, Alessandro Pozzebon, M. Grandé, Roberto Francescon et al.
3 citations
IEEE Journal of Oceanic Engineering
Water Quality Monitoring Technologies
0.60
article

Monitoring the Venice Lagoon: An IoT Cloud-Based Sensor Network Approach

Michele Zorzi, Alessandro Pozzebon, M. Grandé, Roberto Francescon, Davide De Battisti, Filippo Campagnaro, Riccardo Tumiati, Matin Ghalkhani, Federico Marin
article en
3 citations

Abstract

The impact of global warming is felt worldwide, but coastal regions are particularly vulnerable, and face rising sea levels, increased seaquakes, and floods. In addition, the ecosystems of rivers, seas and lakes undergo significant changes due to climate change and pollutants. Thus, monitoring coastal areas, such as the Venice Lagoon (Italy), is of significant importance. This article presents a novel floating wireless sensor system for measuring water-related parameters. The core of the system is the SENSWICH platform, which integrates sensors to measure pH, electrical conductivity, turbidity, dissolved oxygen, and water level. The platform uses long range wide area network (LoRaWAN) connectivity for long-range data collection, which is then aggregated in the Amazon Web Service cloud and visualized using Grafana. While the proposed architecture can be applied to any large-scale coastal, lakeside or riverine monitoring context, it is specifically designed for the Venice Lagoon. This article presents results from two SENSWICH platforms: one in the Piovego river, Padova, which is a tributary of the Venice Lagoon, and one in Chioggia, in the lagoon itself. Together with these results, an analysis for a full-scale deployment in the whole Venice Lagoon is proposed. The results show that SENSWICH, despite being a low-cost platform compared to similar technologies available on the market, enables pervasive monitoring of large water surfaces. It provides reliable datasets over prolonged periods and significantly reduces human resource requirements. The proposed software framework for data aggregation is effective for managing large quantities of data acquired using a LoRaWAN network and is user-friendly through the graphic tool.

IEEE Journal of Oceanic EngineeringVol. 50(2)
University of Padua (IT)
Life below water
Openalex Percentile: Top 33%
Water Quality Monitoring Technologies
0.60
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