Project Description
The CALLISTO project is rapidly moving towards its final stages; the technologies produced within the project will be tested in 4 different Use Cases, among them one dedicated to water quality monitoring.
The lagoon basin of La Loggia, used by SMAT as a water reservoir (see blog post “FROM IN-SITU SENSING TO REMOTE SENSING – THE ROLE OF EARTH OBSERVATION IN WATER QUALITY MONITORING”), is one of the 2 basins where the technologies produced within the project have been tested.
But what are they? Let’s see them together!
- Water Quality Products (KR4 – KR16)
within the project, our partner RBINS was responsible for creating an automated processing data chain to process Sentinel-2 satellite data in order to obtain thematic maps of water quality. Satellite data are acquired with a temporal resolution of less than 5 days; the parameters that have been derived are Total Chlorophyll, Turbidity and Suspended Particulate Matter (SPM). The algorithm was optimized thanks to numerous monitoring campaigns carried out on the basin between spring 2022 and summer 2023. Overall 8 monitoring campaigns were undertaken; samples were mostly collected on the basin surface (these data were acquired in order to validate the algorithm) and, in part, at different depths, in order to evaluate the variability of the acquired parameters. For each sample, different parameters were analyzed: Total chlorophyll, Blue-Green Algae, Diatoms, Green algae, Planktothrix, Turbidity, Conductivity, Dissolved Oxygen, Temperature, pH, etc. All these data have been made available to the scientific community through the CALLISTO data repository;
Figure 1 – Comparison between the water quality maps derived from Sentinel-2 data (acquisition date: 21/5/2022) and samples acquired on the basin surface on 24/5/2022 and analyzed into Lab
- CALLISTO data repository (KR02)
The aim of this KR is to make available to the Scientific Community different datasets that can be used to train Machine Learning and Artificial Intelligence algorithms. Datasets that have been created/generated within the project and dataset that have been collected from the User inside the projects have been made available through GitHub (https://github.com/Agri-Hub/Callisto-Dataset-Collection). Data collected by SMAT during the monitoring campaigns have been included in this repository. - Algae bloom forecasting (Product 4)
For our case study, an algorithm for predicting algal blooms has been implemented. The algorithm considers as input 2 sequential Sentinel-2 images, applies on them algae monitoring using an existing SOTA method and then produces a 3rd image that is dated 5 days (forecast image) after the last sentinel-2 image; - Augmented Reality App (KR7-KR20)
Augmented Reality allows the user to add computer generated objects layered into the experience of the real word: in AR the things that you see in the environment are real, and this is enhanced (Augmented) with virtual objects. In the Callisto project, an App has been developed in order to visualize AR application through the camera of the mobile phone. In relation to our use case, it allows the visualization of water quality maps, developed in KR4-KR16, directly on the basin surface. The app could be used by an operator who is moving with a boat on the basin and needs to select the most appropriate location for taking water samples to be later analyzed into laboratory, based on the information derived from satellite.
Figure 2 – AR App for Water Quality Monitoring
- Social media Analytics Suite (SMAS – KR13-KR17)
The application, developed by CERTH, enables the end user to retrieve and visualize the social media (Twitter and Instagram) data that meet the requirements established by each Pilot Use Case. For Water Quality Monitoring, we defined 2 lists of keywords (related to water quality) that allow us to find user-generated posts that could help to identify events that compromise water quality in supply sources. Thanks to different widgets made available by the application, the user can quickly see the posts based on their geographical location or based on the most recurring words and select them again in order to identify only the posts that may be of interest.
Figure 3 – Test of SMAS application in the Water Quality Monitoring Use Case. The tool detected an increase of tweet during the flood that hit Emilia Romagna in May 2023
- The CALLISTO Platform (KR19)
The CALLISTO platform will allow the technical partner to create contents and to the end user to benefit from all the technologies produced within the project.
Project Details
- DateSeptember 28, 2023
- WriterSMAT - Società Metropolitana Acque Torino S.p.A.
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