D1.1 Technology survey: Prospective and challenges - Revised version (2018)
8 Priority areas, challenges and research directions in FP7 and H2020 projects
8.4 Other projects
EOMORES project Copernicus platform
Earth Observation-Based Services for Monitoring And Reporting Of Ecological Status (EOMORES) and is a water quality monitoring project initiated in 2017 by a group of researchers who were previously involved in different smaller initiatives of water quality data gathering such as FRESHMON (FP7, 2010-2013), GLaSS (FP7, 2013-2016), CoBiOS (FP7, 2011-2013), GLoboLakes (UK NERC,
2012-2018), INFORM (FP7, 2014-2017). Many of these projects were funded by the European Unions Seventh Framework Programme for Research and Technological Development (FP7) and dealt with satelite data analysis in the monitoring of quality requirements imposed by the EU directives. The purpose of EOMORES project is different scale monitoring on water bodies, combining a series of techniques in order to obtain comprehensive results which can pe further used in an efficient manner.
The first technique is based on satellite monitoring and is providing a set of data from Copernicus Sentinels every few days, depending on the availability of the Sentinels, or the weather conditions. The data provided is then converted into information by one or several algorithms which have been previously tested against a wide range of factor (location, type of water, sensor technical characteristics). For the project research, EOMORES is collaborating with six countries (Italy, France, The Netherlands, the UK, Estonia, Lithuania and Finland), having different latitude coordinates for their location and also belonging to very different climates/ecoregions.
The main focus of the observations was the comparison of different approaches to atmospheric correction (the process of removing the effects of the atmosphere on the reflectance values of images taken by satellite or airborne sensors [COPERNICUS Homepage, 2018]). Satellite data has the advantage of covering large areas, but the drawback is that they have limited levels of detail achievement and measurement frequency. EOMORES uses Sentinel-1, Sentinel-2 and Sentinel-3 from Copernicus programme which offers free and open data. The first launch of Earth Observation satellites for Copernicus happened in 2014 and one year after, they have improved their assets by launching Sentinel-2A which was aimed to provide color vision data for changes on the surface of the Earth [COPERNICUS Homepage, 2018]. This mean that its optical system included three spectral bands in the electromagnetic spectrum area also called red-edge in which the difference is plant reflectance (visible light absorbed by plants versus radiation scattered in the photosynthesis).
The second technique consists of in situ observations or in situ monitoring which provides continuous measurements of a specific location in an assigned period of time (e.g 24 hours). This is information collected directly on site and is meant to be complementary or validating of the satellite data. As this kind of observations is not influenced so much of the weather state, the level of control over the frequency of measurement is higher. EOMORES researchers use hand-held devices for in situ data collecting, but an autonomous fixed-position optical instrument is in development as an improvement of the current Water Insight Spectrometer (WISP). This instrument is used for measuring Chlorophyll, Phycocyanin and Suspended sediments which are measures of algal biomass/cyanobacterial biomass/total suspended matter (TSM) [EOMORES-H2020 Homepage, 2018]. The measured values appear on the display in 30-90 seconds. The raw information can be uploaded from the WISP to a cloud-platform for further analysis, model generation and further computation. The WISP has incorporated three cameras which are able to break light into its spectral components. By comparing the three sources which measure light coming straight into the WISP and the light reflected from the surface of the water, a derivation of the parameters wanted is being done through band-ratio algorithms.
The third technique is modelling which combines the results obtained through the two techniques previously presented in order to generate prediction data, forecast information on the specified area.
All the reliable quality water datasets are to be transformed in sustainable commercial services offered to international or national/regional authorities which are in charge of monitoring water quality or are responsible with water management and environmental reporting. Private entities that deal with the same monitoring issues can benefit from the data collected and mined by the EUMORES researchers.
AquaWatch project (2017-2019) is part of the GEO (Group on Earth Observation) Water Quality Initiative whose aim is to build a global water quality information service. The implementation of the project, currently in progress, is based on activity distribution across working groups, each with a specific focus element.
AquaWatch has a targeted public which consists of science and industrial communities, Non-Governmental Organizations, policy maker, environmental organization managers, non-profit organizations. Also, access to information will be promoted to simple recreational users too. These potential end-users are to be attracted and involved as volunteers in the working groups or for gathering data. In the beginning of 2018, a first group of products should be finished. This group would contain products which support turbidity measurement using different techniques:
a Secchi disk [Preisendorfer, 1986] depth product which is a plain, circular disk 30 cm diameter for measurement of water transparency or turbidity in bodies in water;
a diffuse attenuation coefficient product;
a Nephelometric Turbidity Unit product;
a surface reflectance product.
Smart Water For Europe is a demonstration project that is being created to produce business cases for Smart Water Networks (SWN). Founded by the European Union, the project will try to demonstrate optimal water networks and will look at the potential to integrate new smart water technologies across Europe. European organizations are taking part in the project and four demonstration sites are available -Vitens (the Netherlands), Acciona (Spain), Thames (UK), Lille (France).
The project will help to understand how small technologies can deliver costeffective performance and improve the water supply service given to customers. Smart water technologies and hi-tech informatics will allow the early detection of leaks on a 24/7 basis leading towards Smart Networks through data capture, analysis and reporting. As well as leakage detection, service excellence will be supported with best practices as energy monitoring, water quality and customer engagement. The main idea of the project is to implement small projects, receive recommendations based on the implementation and then go on with another small project in a different location, across Europe and beyond.
Vitens Inovation Playground (The Netherlands) is a demonstration site which consists of 2300 km of distribution network, serving around 200.000 households. Conductivity, temperature, chlornation level are measured using hi-tech sensors. Pipe burst detection and water hammer detection is tested through Syrinix sensors. Using an integral ICT solution, all the dynamic data from sensors, but also static data formats such as area photos, distribution network plans or soil maps, are stored and made available for water companies participating in the project and for researchers. The Vitens Inovation Playground serves also as a training facility in which operators learn how to respond to high risk incidents like contamination or massive leakages.
Smart Water Innovation Network in the city of BurGos (Spain) is working with three different hydraulic sectors (one industrial, one urban and one residential) which have been converted into one Smart Water Network. To create it, a network of quality sensors and conventional water meters with electronic versions equipped with communication devices have been installed. The information provided by the sector flow meters is integrated into the end-to-end management system, the so-called Business Intelligence Platform. This platform, hosted in the Big Data Center manages and processes the data gathered from common management systems, integrating also the algorithms developed in order to automatically detect leaks, predict consumption levels and check the quality of the water at any moment. The platform information is also used for continuously improving the overall service. The ultimate objective is to find the key parameters of the smart supply network so that the service could be implemented in any location, regardless of its characteristics. Among the benefits of such projects is the chance of savings of millions of dollars all over the world.
Thames Water Demo Site (The Netherlands) focuses on trunk mains leak detection by being aware of transients or rapid changes in pipe pressure and taking proactive action about the specific incidents. In addition, a first attempt has been made to distinguish between customer side leakage and wastage through a scalable algorithm which has been trained on smart meter data. In order to promote good practices, customers have been given incentives to save money and earn discounts by using water more carefully. An energy visualization tool was built in order to show where the energy on the network is being distributed. This graphic tool helps users better understand the dependency between demand, pressure and energy. All the solutions are concentrated in a single interface in order to display relevant information for operators to act or to discover causeeffect connections.
OPC UA with MEGA model architecture
The authors of [Robles, 2015] identify the problem of interoperability in water management initiatives, caused by the lack of support and lack of standardization in the monitoring processes, as well as the control equipment. They propose a smart water management model which combines Internet of Things technologies and business coordination for having better outcomes in decision support systems. Their model is based on the OPC US (Object Linking and Embedding for Process Control Unified Architecture) which is an independent platform that offers service-oriented possibilities of architecture schemes for controlling processes which are part of the manufacturing or logistic fields. The platform is based on web service technologies, therefore being more flexible to scenarios of usage.
The proposed model is MEGA model which takes into consideration functional decoupled architectures in order to achieve the goal of increased interoperability between the water management solutions on which companies and organizations are currently working. This would also solve the problem of SME (Small and Medium-sized Enterprise) companies locally oriented which provide good local solutions for water management, but which have difficulties in expanding to other countries, regions, or to maintain their funding on a long-term.
The MEGA architecture consists of several layers, the main ones being the following:
Management and Exploitation layer hosts the main applications and services (can be executed in cloud, on local hosts) and supports the management definitions of the processes;
Coordination layer defines and can associate, if necessary, entities to physical objects, collects the procedures defined by the ME layer and delivers them to the Subsystem layer after associating sequence of activities to them (recipes);
Subsystem layer contains the subsystems that execute, independently or not, the procedures and recipes defined in the Coordination layer;
Administration layer provides a user interface for administration and monitoring, enables configuration of entities defined in previous layers.
The water management model proposed includes a Physical Model and a Process Model which contain several Process Cells, Units, Units Procedures, Control Modules, Equipment Modules and Operations which can be handled differently, according to the business requirements. The big steps of the whole Mega Model process are as follows:
Identifiers Mapping map recipe identifier to subsystem identifier (if the recipe is already provided, if not, translate the instructions into a standard recipe first);
Recipe validation check if the subsystem is able to execute the process
contained in the recipe;
Process transfer to the suitable subsystem each subsystem receives its sequence of activities to be executed;
Control and monitoring of the process execution information about the ongoing processes can be monitored in real-time.
WATER-M project is an international initiative of representatives from four countries (Finland, France, Romania and Turkey), part of the Smart City challenge. The project is meant to contribute to a major upgrade of the water industry by helping with the introduction and integration of novel concepts such as GIS (Geographic Information System) usage, ICT with IoT applications or real-time data management or monitoring. The final purpose is to build a unified water business model targeted at European Union water stakeholders. Through operational control and monitoring real-time data, the WATER-M project is currently developing a service-oriented approach and event driven mechanisms for dealing with the water sustainability problem.
As the project was started in 2017, the plans and results are made public once progress is made. The use cases defined for this initiative are stated below [ITEA3 Homepage, 2018]:
Development of Water Management and Flood Risk Prevention Platform;
Performance monitoring of water distribution network;
Control and optimization of the water distribution network;
Coordinated management of networks and sanitation structures;
New redox monitoring;
Energy cost reduction and compatibility with European directives on water for allowing new business models for water management to emerge on the basic structure of the WATER-M are taken into consideration. Critical challenges, as well as options for various communication protocols such as LTE-M or LoRa, or AMR (Automatic Meter Reading) technologies with benefits and drawbacks were discussed in a state-of-the art [Berhane, 2015] aimed at evaluating the previous proposals in the areas of water management. A new model has not yet been proposed, it is still work in progress.