Satellite remote sensing has been evolved into a powerful tool for global monitoring of surface waters. Earth Observations (EO) and remote sensing are widely used for quantifying the physical parameters of reservoirs as well as for retrieving selected water constituents concentrations. Space-O aims at the integration of state of the art (EO) and in situ monitoring with advanced hydrological, water quality models and ICT tools into a powerful decision support system (DSS) for generating real time, short to medium term forecasting water flows and quality data in reservoirs which will be used for the optimization of water treatment plants (WTPs) operations, establishing a complete service line from EO to water business sector. An operational service platform will be designed to facilitate increased interoperability among EO and modeled services. Data acquisition and integration of almost real time EO data in the hydrological and water quality models will be implemented in order to provide improved real-time, short to medium term water quantity and quality forecasting in reservoirs. A risk-based DSS will be developed in order to enable cost-effective and environmental sustainable Water Treatment Plants (WTPs) operation, based on the water quality parameters forecasts at the reservoir, the in situ monitoring data and the data collected through supervisory control and data acquisition (SCADA) systems used in WTPs for operation control. Additionally, developing Copernicus Services (C3S) will be jointly assessed with site-specific data sets generated through the satellite, modeling, in situ and citizens monitoring services, to produce continuous monitored indicators for enabling water quality Risk Assessment analysis on a catchment level.

BENEFFICE’s strategic objective is to reduce wasted energy by incentivising various consumer types in the wide energy consumer market. A novel ecosystem will be developed which enables and incentivises long-term energy consumption savings. BENEFFICE ecosystem leverages novel IoT enabled, low-cost, “plug-and-play-and-forget” devices, energy disaggregation and an innovative empowerment and rewards approach based on an alternative monetary currency so as to change consumers’ energy consumption behaviour. The “plug-and-play-and-forget” devices will accurately capture energy use patterns at the level of each electrical appliance and at the level of each individual user. An energy behaviour model will be used to correlate these patterns with optimal, personalised comfort levels, social profiles and characteristics (including social, economic, geographic and energy use contexts) in order to determine optimal energy use behaviour to reduce wastage of energy and to increase the use of renewable resources in the energy mix. BENEFICE will design personalized, real-time motivational paths to deliver sustained reductions in energy consumption. Customers will be incentivized to follow these paths voluntarily, through the application of novel business models that provide monetary rewards in return for progress along each personalized pathway and help build an online community of like-minded actors. These business models will be based on an innovative digital CO2 currency - CO2 Credits are awarded to actors for proven, sustained reduction in fossil fuel use. Business models that stimulate the supply of, and demand for, CO2 Credits, will be designed, tested and validated. These business models will leverage partnerships with established businesses -third party market catalysts- that recognize the potential offered by CO2 Credits both to promote reduced consumption of fossil fuels and to extend their market share by offering a new service to their clients with clear social added value.

ChArGED addresses the energy consumption in public buildings and proposes a framework that aims to facilitate achieving greater energy efficiency and reductions of wasted energy in public buildings. The framework leverages IoT enabled, low-cost devices (NFC or iBeacons) to improve energy disaggregation mechanisms that provide energy use and (consequently) wastages at the device, area and end user level. These wastages will be targeted by a gamified application that feeds personalized real-time recommendations to each individual end user. The design of the game will follow a cleanweb approach and implement a novel social innovation process that will be designed based on human inceptives factors and will help users to understand the environmental implications of their actions and adopt a more green, active and responsible behaviour. The blend of social interaction and competitions with its personalized character are expected to eventually contribute to the user engagement and commitment to generate savings in the long term leading to tackle energy efficiency targets in public buildings while emphasizing on cost effectiveness. Furthermore, users will become more educated on energy efficiency actions and their impacts which has an impact beyond the actual public building. Efficient energy use will render its consumption predictable and this will be exploited by the ChArGED gamified application to optimize use of the micro-generated energy. Users will be motived to reduce energy consumption when power comes from the grid. Predictable energy consumption will also support more informed decisions of micro-generation sources to match the use patterns. The ChArGED solution will be developed with iterative end users representatives’ engagement during analysis, design and development. Further users at least 150 real building occupants in three (3) countries (50 in each building- validation country) will be engaged for deployment and validation.

In the last years irregular migration has dramatically increased, and is no longer manageable with existing systems. Improved methods for border surveillance are necessary to ensure an effective and efficient EU border management. FOLDOUT focus is on through foliage detection in the inner and outermost regions of the EU. Foliage penetration is an unsolved important part of border surveillance. By solving the problem of unreliable detections in such harsh environments border guards’ workloads are reduced, costs are reduced and, last but not least, lives can be saved. Detecting people through dense foliage in extreme climates with only a penetration technology is prone to high fault rates. FOLDOUT will build a system that combines various sensors and technologies and intelligently fuses these into an effective and robust intelligent detection platform. Fusing several sensor signals increases the effectiveness of detection. Further, sensors will be influenced (i.e. detection parameters adapted) by events detected by other sensors in the vicinity. By integrating data, such as vehicle traffic, from outside the immediate border area pre-events can be detected and learned. The events will be analysed with machine learning tools to continuously increase the systems detection and tracking capability. FOLDOUT will make the tasks of Border Guards simpler and faster by combining events from various sensors to give a complete situation threat assessment combined with suggested reaction scenarios. A two year pilot in Bulgaria and demonstrators in Greece, Finland and French Guiana FOLDOUT will provide fundamental enhancements in the domain of border surveillance and improved search & rescue scenarios.

With regards to modalities, TRESSPASS project includes air, maritime and land (including car and train) border crossing points, and specifically also travel routes that combine different modalities. It excludes border crossings outside of border crossing points, such as happens with boats of refugees on the Mediterranean. With regards to threats, this includes smuggling, irregular immigration, cross border crime, and terrorism, including threats to the transport itself (so, including e.g. aviation security – per the topic text). It excludes other threats such as posed by state-actors. This proposal includes all tiers of the four-tier access model: (1) measures undertaken in, or jointly with third countries or service providers; (2) cooperation with neighbouring countries; (3) border control and counter-smuggling measures, and (4) control measures within the area of free movement. TRESSPASS will (1) develop a single cohesive risk-based border management concept (2) develop three pivoting pilot demonstrators (3) demonstrate the validity of the single cohesive risk-based border management concept by using red teaming and simulations (4) prepare for the further development of this concept beyond this project by linking to other known risk-based border management projects (in- and outside EU, within EU research frameworks and on national levels), and describe how their results contribute to a single cohesive risk-based border management concept