Agency: European Commission | Branch: FP7 | Program: JTI-CP-ARTEMIS | Phase: SP1-JTI-ARTEMIS-2011-7 | Award Amount: 6.70M | Year: 2012
The main objective of project e-GOTHAM is to implement a new aggregated energy demand model (based on the microgrid concept) in order to effectively integrate renewable energies sources, increase management efficiency by dynamically matching demand and supply, reduce carbon emissions by giving priority to green energy sources, raise energy consumption awareness by monitoring products and services and stimulate the development of a leading-edge market for energy-efficient technologies with new business models. e-GOTHAM will define a complete solution for microgrids in the residential, tertiary and industrial sectors that include different configurations of loads, distributed generators and energy storage components. To carry out the e-GOTHAM concept, the project will design an open architecture and develop a middleware that enables the needed communications for management and results optimisation. The challenge of the middleware produced in e-GOTHAM is to assemble a system which can ensure enough scalability, security, reliability, real time measurements and interoperability so as to lead to the development of a large-scale embedded systems network, a smart data management model, a set of models and algorithms that dynamically correlate energy-related, pollution-related, cost-related and behaviour-related patterns and a just-in-time adaptive communication model that interoperates different protocols to support seamless connectivity across the microgrid. e-GOTHAM is a market-oriented project that seeks to meet the needs of the involved market partners, especially power producers and microgrid owners, and to have an influence on consumers and on the authorities who define regulations. Finally, e-GOTHAM aims at creating an ecosystem meant to attract those relevant stakeholders who are willing to elaborate on project results so as to generate new products and services and to support the looked-for new aggregated energy demand model even beyond the project lifetime. This TA was approved by the ECSEL Joint Undertaking on 22/04/2015.
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: DRS-07-2014 | Award Amount: 3.85M | Year: 2015
Increasing Europes resilience to crises and disasters is a topic of highest political concern in the EU and its Member States and Associated Countries. Regarding the specific case of transport systems, it can be said that those have developed a prominent safety and business critical nature, in view of which current management practices have shown evidence of important limitations in terms of resilience management. Furthermore, enhancing resilience in transport systems is considered imperative for two main reasons: such systems provide critical support to every socio-economic activity and are currently themselves one of the most important economic sectors and secondly, the paths that convey people, goods and information, are the same through which risks are propagated. RESOLUTE is answering those needs, by proposing to conduct a systematic review and assessment of the state of the art of the resilience assessment and management concepts, as a basis for the deployment of an European Resilience Management Guide (ERMG), taking into account that resilience is not about the performance of individual system elements but rather the emerging behaviour associated to intra and inter system interactions. The final goal of RESOLUTE is to adapt and adopt the identified concepts and methods from the defined guidelines for their operationalization and evaluation when addressing Critical Infrastructure (CI) of the Urban Transport System (UTS), through the implementation of the RESOLUTE Collaborative Resilience Assessment and Management Support System (CRAMSS), that adopts a highly synergic approach towards the definition of a resilience model for the next-generation of collaborative emergency services and decision making process.
Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2007.4.2 | Award Amount: 3.70M | Year: 2008
Public administrations represent the largest information bound professional communities: among them the judicial sector is one of the largest, where the needs of cooperation are critical creating an exceedingly large improvement potential through adoption of novel content management techniques and development of new solutions for its specific needs of retrieval and semantic analysis. This potential is even larger considering the growing trans-national cooperation also among several national law systems, highlight the need to adapt the technological profiles of new member states. In this context JUMAS is the leverage able to converge to an actionable knowledge starting from the content revolution. In particular, JUMAS envisages a system for the embedded semantic extraction from multimedia data that join into an advanced knowledge management system. Moreover JUMAS is tailored at managing situations in which multiple cameras and audio-source are used to record assemblies in which people debates and event sequences need to semantically reconstructed for future consultation. The project has several objectives:\n1.\tKnowledge Models and Spaces: Search directly in the audio and video source without a verbatim transcription of the proceedings.\n2.\tKnowledge and Content Management: Exploit hidden semantics in audiovisual digital libraries in order to facilitate search and retrieval, intelligent processing and effective presentation of multimedia information.\n3.\tSensor and Multimedia Integration: Information fusion deriving from multimodal sources in order to improve accuracy in automatic transcription and annotation phases.\n4.\tEffective Information Management: Streamline and Optimize the document workflow allowing the analysis of (un)structured information for document search and evidence base assessment.\n5.\tICT Infrastructure: Service Oriented Architecture supporting a large scale audio/video retrieval system focusing on scalability, interoperability and modularity.
Agency: European Commission | Branch: FP7 | Program: CP-FP | Phase: SEC-2011.1.2-1 | Award Amount: 4.68M | Year: 2012
The main goal of PROACTIVE is to research a holistic citizen-friendly multi sensor fusion and intelligent reasoning framework enabling the prediction, detection, understanding and efficient response to terrorist interests, goals and courses of actions in an urban environment. To this end, PROACTIVE will rely on the fusion of both static knowledge (i.e. intelligence information) and dynamic information (i.e. data observed from sensors deployed in the urban environment). The framework will be user-driven, given that the project is supported by a rich set of end-users, which are either members of the consortium or members of a special end-user advisory board. From a technological perspective, PROACTIVE will integrate a host of novel technologies enabling the fusion of multi-sensor data with contextual information (notably 3D digital terrain data), while also resolving the ambiguities of the fusion process. Moreover, the PROACTIVE framework will incorporate advanced reasoning techniques (such as adversarial reasoning) in order to intelligently process and derive high level terroristic semantics from a multitude of source streams. The later techniques will be adapted to the terrorist domain, in order to facilitate prediction and anticipation of actions and goals of the terroristic entities. Overall, PROACTIVE will leverage cutting-edge technologies such as the Net-centric Enable Capability (NEC) approach and the emerging Internet-of-Things concept, which are key enablers of new capabilities associated with real-time awareness of the physical environment, as well as with tracking and analyzing human behaviour. PROACTIVE will address the technological challenges that inhibit the wider deployment of NEC/ IoT in anti-terrorist applications. Following the deployment and evaluation of the framework, PROACTIVE will produce a set of best practices and blueprints, which will contribute to a common EU approach to terrorist prevention in an urban environments.
Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2007.6.3 | Award Amount: 3.13M | Year: 2008
The main goal of the LENVIS project is to develop an innovative collaborative decision support network for exchange of location-based environmental and health services between all stakeholders, for enhanced capacity to assess population exposure and health risks and better management of the concerned ecosystems. LENVIS will include health indicators as integral part of the environmental management.There is a growing demand for real time and integrated environmental and health risk information. Provision of such location-based services linked to the state of the environment at particular geographical locations (addresses) is necessary for improving the quality of life of all people. This is essential for mitigation of environmental-related health threats associated to water quantity and quality, and outdoor air pollutions.LENVIS project aims to fill the existing gap between environmental management and the health management systems. This will be done by developing a generic ICT solution that combines service-oriented-architecture (SOA) and user-centric approach (peer-to-peer network, P2P) by fusion of location-based environmental and health data, information and modelling services. This novel collaborative peer-to-peer network, as an integral part of the Single Information Space for the Environment in Europe, will be validated through test cases on fresh surface water and outdoor air quality in the Netherlands, Portugal and Italy.LENVIS project will facilitate collaboration between different stakeholders, such as environmental protection agencies, health institutions and service providers, policy makers, citizens in general and environmental communities in Europe.
Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2011.6.3 | Award Amount: 4.67M | Year: 2012
ICeWater will increase the stability of freshwater supply to citizens in urban areas by adjusting the water supply to the actual consumption, while minimizing energy consumption through smart-grid integration and water spillage through leak detection.\n\nICeWater uses wireless sensor networks for water flow monitoring and it provides a decision support system for the water utilities so that supply and demand patterns can be matched in real-time. As an additional benefit, leakage can be predicted with statistical methods so that water network damages can be mended even before they occur (fix-before-break).\n\nICeWater uses wireless sensors of various types to provide real-time monitoring of water supply and demand. Based on the sensor data, decision support systems facilitate optimization of the water grid network operation (pumping schedules, pressure etc.). The demand management and consumption information is accessible online to the relevant actors in the water supply chain (including consumers) and allows dynamic pricing schemes with nudge-pricing to motivate behavioural change in customers causing critical consumption patterns. Services for asset management, such as predicting deterioration, leakage detection and leakage localization functionalities, will reduce water waste. New networking concepts (protocols, management of virtualized network resources) are required for better information flow, network resources management and sharing in a service oriented architecture (SOA). The information gathered with these services allows a better understanding of the consumers and to improve the effectiveness of the water resource management together with new metering and pricing schemes.
Toscani D.,Consorzio Milan Ricerche |
Giordani I.,Consorzio Milan Ricerche |
Cislaghi M.,Consorzio Milan Ricerche |
Quarenghi L.,University of Milan Bicocca
International Journal of Sensor Networks | Year: 2011
Data sources are increasing in number and distribution on the territory: sensor networks and individual devices are not any more atomic devices, but they are transforming data providers and consumers, paving the way to new personalised services. In this context, the paper presents a new software infrastructure for the integration of heterogeneous data (web services and sensors' API for streaming data, databases and files for historical data) and any type of data analysis and inference algorithms (e.g. forecast, statistical analysis, data cleaning, anomaly detection and optimisation). This infrastructure, named SUSHI (Supporting Unified access for Streaming and Historical data), provides explicit representation of domain objects, queries over heterogeneous data sources, online access to different sources, inclusion of processing components such as forecasting and simulation modules. The paper describes the SUSHI concept and architecture, a case study in environmental management and possible future developments for new services. Copyright © 2011 Inderscience Enterprises Ltd.
Candelieri A.,Consorzio Milan Ricerche |
Soldi D.,University of Milan Bicocca |
Archetti F.,Consorzio Milan Ricerche |
Archetti F.,University of Milan Bicocca
Journal of Water Supply: Research and Technology - AQUA | Year: 2015
This paper extends previous research to analytically identify leaks within a water distribution network (WDN), by combining hydraulic simulation and network science based data analysis techniques. The WDNmodel is used to run several 'leakage scenarios', by varying leak location (pipe) and severity, and to build a datasetwith corresponding variations in pressure and flow, induced by the leak. All junctions and pipes are considered for potential pressure and flow sensors deployment; a clustering procedure on these locations identifies the most relevant nodes and pipes, and cost-effectiveness was considered. A graph is then generated from the dataset, having scenarios as nodes and edges weighted by the similarity between each pair of nodes (scenarios), in terms of pressure and flowvariation due to the leak. Spectral clustering groups together similar scenarios in the eigen-space spanned by the most relevant eigen-vectors of the Laplacian matrix of the graph. This method uses superior traditional techniques. Finally, support vectormachines classification learning is used to learn the relation between variations in pressure and flow at the deployed meters and the most probable set of pipes affected by the leak. © IWA Publishing 2015.
Fersini E.,University of Milan Bicocca |
Messina E.,University of Milan Bicocca |
Archetti F.,University of Milan Bicocca |
Cislaghi M.,Consorzio Milan Ricerche
Communications in Computer and Information Science | Year: 2013
The progressive deployment of ICT technologies in the courtroom, jointly with the requirement for paperless judicial folders pushed by e-justice plans, are quickly transforming the traditional judicial folder into an integrated multimedia folder, where documents, audio recordings and video recordings can be accessed via a web-based platform. Most of the available ICT toolesets are aimed at the deployment of case management systems and ICT equipment infrastructure at different organisational levels (court or district). In this paper we present the JUMAS system, stemmed from the homonymous EU project, that instead takes up the challenge of exploiting semantics and machine learning techniques towards a better usability of the multimedia judicial folders. JUMAS provides not only a streamlined content creation and management support for acquiring and sharing the knowledge embedded into judicial folders but also a semantic enrichment of multimedia data for advanced information retrieval tasks. © 2013 Springer-Verlag Berlin Heidelberg.
Candelieri A.,Consorzio Milan Ricerche |
Archetti F.,Consorzio Milan Ricerche |
Archetti F.,University of Milan Bicocca
WIT Transactions on the Built Environment | Year: 2014
This paper presents the approaches proposed in the Italian project TAM-TAM to support a smarter, personalized and sustainable urban mobility, by taking into the loop the users of the transportation services, in particular citizens, tourists and commuters in Milan. A computational module has been defined and developed in order to collect and analyze relevant tweets posted by users as well transport operator. The main goals are two: identifying events (e.g. accidents, sudden traffic jams, service interruptions, etc.) and evaluating the overall sentiment about the service as well as mobility options. Detected events are used by other computational modules of TAM-TAM in order to support a more effective travel planning; on the other hand, the perceived quality of service is provided both to users, enabling more personalized choices, and to transport company, supporting them in the management of mobility supply. © 2014 WIT Press.