Tools

Tools

photrack – Discharge platform

In order to measure the level, velocity, and consequently, the discharge value, photrack developed a platform called “Discharge”, able to non-intrusive, optical flow measurement for natural water streams, irrigation, and wastewater channels.

The platform is developed as a cloud-based platform for the large-scale acquisition of hydrometric and meteorological data and comprises:

• A mobile Android app, called DischargeApp, freely available on the google play store. LINK: Google Play
• A web platform, called DischargeWeb, to show the collected data. LINK: https://discharge.ch/

Geoserver map-based interactive interface

The collected information set has been uploaded to a proprietary mapping server for the SMARTLAGOON project created through GeoServer, an open-source server written in Java – allowing users to share and edit geospatial data. Designed for interoperability, it publishes data from all major spatial data sources using open standards.

GeoServer is an ideal system for sharing spatial information with stakeholders as it has numerous advantages:

• By implementing the Web Map Service (WMS) standard, GeoServer can create maps in a variety of output formats.
• OpenLayers, a free mapping library, makes map generation fast and easy.
• It is based on GeoTools, an open-source Java GIS toolkit.
• GeoServer conforms to the Web Feature Service (WFS) and Web Coverage Service (WCS) standards, which allow sharing and editing of the data used to generate maps.
• It uses the Web Map Tile Service standard to tile published maps for easy use by mobile and web mapping applications.
• It is a modular application to which additional functions are added through extensions.
• It allows for the future incorporation of open data into websites and applications, freeing it for the public and allowing for greater transparency.

The referred mapping services are available at https://vielca-ingenieros.com/smartlagoon-map/

Social Sensing Tools

To collect data from the public in a massive way and to extract topics of interest and the citizens’ moods associated with such a topic, UPV developed a social sensing platform. Such a platform allows performing different tasks. The first stage consists of defining the important topics for the problem to be addressed. The definition of the problem begins by describing the semantic spaces of a given topic category.

People can freely and easily select categories or topics of interest and navigate the interactive interface. The dashboard presents data crawled by social media tools (Twitter, Telegram, RSS), and also data from the sensing infrastructure developed around the Mar Menor area.

Technically speaking, the platform is structured as follows: the front-end communicates with the web API, based on Google’s Firebase, where different micro-services are available. The Apache Kafka cluster, which is a distributed streaming platform not only to publish and subscribe to streams of records but also to store and process these streams in real-time, distributes the information received from social media sources. Finally, the data is persisted in an Elastic Search database.

LINK: Social sensing tool

WaterITech – ASAP Platform for real-time sensor data and short-term forecasting

The ASAP Platform by WaterITech & WaterWebTools is a multi-source integration platform that overlay with modeling, IoT, and weather data, and enables highly advanced forecasting and analysis. The ASAP platform operationalizes the SWAT+ catchment model and the GOTM-WET lake and lagoon model. By coupling to local weather forecasts, the platform can produce 9-day hydrological forecasts for the catchment runoff as well as forecasts for the lagoon water quality dynamics. By allowing real-time sensor data to be assimilated into the model forecasts, the ASAP Platform can comprise a digital twin of a coupled catchment-lagoon/lake system.

In SMARTLAGOON, WaterITech aims to significantly improve the portal through a series of innovations that will allow:

• fully dynamic coupling of the catchment and lagoon dynamics, whereby forecasted catchment runoff is used in the lagoon forecast
• the ability to acquire real-time sensor data from a buoy installed in the Mar Menor, and assimilate the sensor data into the model forecasts by a hotstart functionality, thereby potentially improving forecast skill
• both process-based (SWAT+ model) and machine learning based (e.g. LOADEST) forecasted inputs of nutrients to the lagoon
• the ability to produce sub-daily (e.g. hourly) in contrast to daily timesteps in the forecasted outputs

Forecast projects currently running in the ASAP Platform can be accessed via: https://asap-forecast.com/