Zoheir Sabeur

From Sensor to Observation Web with Environmental Enablers in the Future Internet

This paper outlines the grand challenges in global sustainability research and the objectives of the FP7 Future Internet PPP program within the Digital Agenda for Europe. Large user communities are generating significant amounts of valuable environmental observations at local and regional scales using the devices and services of the Future Internet. These communities’ environmental observations represent a wealth of information which is currently hardly used or used only in isolation and therefore in need of integration with other information sources. Indeed, this very integration will lead to a paradigm shift from a mere Sensor Web to an Observation Web with semantically enriched content emanating from sensors, environmental simulations and citizens. The paper also describes the research challenges to realize the Observation Web and the associated environmental enablers for the Future Internet. Such an environmental enabler could for instance be an electronic sensing device, a web-service application, or even a social networking group affording or facilitating the capability of the Future Internet applications to consume, produce, and use environmental observations in cross-domain applications. The term “envirofied” Future Internet is coined to describe this overall target that forms a cornerstone of work in the Environmental Usage Area within the Future Internet PPP program. Relevant trends described in the paper are the usage of ubiquitous sensors (anywhere), the provision and generation of information by citizens, and the convergence of real and virtual realities to convey understanding of environmental observations. The paper addresses the technical challenges in the Environmental Usage Area and the need for designing multi-style service oriented architecture. Key topics are the mapping of requirements to capabilities, providing scalability and robustness with implementing context aware information retrieval. Another essential research topic is handling data fusion and model based computation, and the related propagation of information uncertainty. Approaches to security, standardization and harmonization, all essential for sustainable solutions, are summarized from the perspective of the Environmental Usage Area. The paper concludes with an overview of emerging, high impact applications in the environmental areas concerning land ecosystems (biodiversity), air quality (atmospheric conditions) and water ecosystems (marine asset management).

Future Internet technologies for environmental applications

This paper investigates the usability of Future Internet technologies (aka “Generic Enablers of the Future Internet”) in the context of environmental applications. The paper incorporates the best aspects of the state-of-the-art in environmental informatics with geospatial solutions and scalable processing capabilities of Internet-based tools. It specifically targets the promotion of the “Environmental Observation Web” as an observation-centric paradigm for building the next generation of environmental applications. In the Environmental Observation Web, the great majority of data are considered as observations. These can be generated from sensors (hardware), numerical simulations (models), as well as by humans (human sensors). Independently from the observation provenance and application scope, data can be represented and processed in a standardised way in order to understand environmental processes and their interdependencies. The development of cross-domain applications is then leveraged by technologies such as Cloud Computing, Internet of Things, Big Data Processing and Analytics. For example, “the cloud” can satisfy the peak-performance needs of applications which may occasionally use large amounts of processing power at a fraction of the price of a dedicated server farm. The paper also addresses the need for Specific Enablers that connect mainstream Future Internet capabilities with sensor and geospatial technologies. Main categories of such Specific Enablers are described with an overall architectural approach for developing environmental applications and exemplar use cases.

Orchestra: developing a unified open architecture for risk management applications

Due to organizational and technological barriers, actors involved in the management of natural or man-made risks cannot cooperate efficiently. In an attempt to solve some of these problems, the European Commission has made “Improving risk management” one of its strategic objectives of the IST program. The integrated project Orchestra is one of the projects that recently started in this area. The main goal of Orchestra is to design and implement an open service oriented software architecture that will improve the interoperability among actors involved in multi-risk management. In 2 Alessandro Annoni, Lars Bernard, John Douglas, Joseph Greenwood et al this paper we will describe the goals of Orchestra and explain some of the key characteristics of the project. These are: The chosen design process of the Orchestra Architecture. How to further improve geospatial information and standards for dealing with risks How ontologies will be used to bring interoperability from a syntactical to a semantical level. The paper ends with two examples demonstrating the benefits of the Orchestra Architecture. One is in the area of coastal zone management, and the other is related with managing earthquake risks.

The Future Internet Enablement of the Environment Information Space

This paper motivates the enablement of the Future Internet to become a highly functional service platform supporting the design and the operation of software applications in the Environmental Information Space. It reports on the experience made by the European research project ENVIROFI as one of the usage area projects within the Future Internet Public-Private Partnership programme. It describes the software components (environmental and specific enablers) which are required to connect with the domain-independent capabilities (generic enablers) of the Future Internet core platform for geospatially and environmentally-driven applications.

Validation and application of the PROTEUS model for the physical dispersion, geochemistry and biological impacts of produced waters

Abstract The PROTEUS system has been developed to support environmental risk assessments of discharges of produced water and drilling wastes from offshore exploration and production activities. The new system is currently in widespread use within the European oil industry and will be used as a primary tool for the forthcoming regulation on offshore chemicals. This paper particularly describes the numerical development, experimental validation and application of the production discharges module within the PROTEUS system, carried out during the MIMIC research programme.

Multi-modal computer vision for the detection of multi-scale crowd physical motions and behavior in confined spaces

Crowd physical motion and behaviour detection during evacuation from confined spaces using computer vision is the main focus of research in the eVACUATE project. Its early foundations and development perspectives are discussed in this paper. Specifically, the main target in our development is to achieve good rates of correct detection and classification of crowd motion and behaviour in confined spaces respectively. However, the performance of the computer vision algorithms, which are put in place for the detection of crowd motion and behaviour, greatly depends on the quality, including causality, of the multi-modal observation data with ground truth. Furthermore, it is of paramount importance to take into account contextual information about the confined spaces concerned in order to confirm the type of detected behaviours. The pilot venues for crowd evacuation experimentations include: (1) Athens International Airport, Greece; (2) An underground train station in Bilbao, Spain; (3) A stadium in San Sebastian, Spain; and (4) A large cruise ship in St. Nazaire, France.

Knowledge-Based Service Architecture for Multi-risk Environmental Decision Support Applications

This paper describes our work to date on knowledge-based service architecture implementations for multi-risk environmental decision-support. The work described spans two research projects, SANY and TRIDEC, and covers application domains where very large, high report frequency real-time information sources must be processed in challenging timescales to support multi-risk decision support in evolving crises. We describe how OGC and W3C standards can be used to support semantic interoperability, and how context-ware information filtering can reduce the amount of processed data to manageable levels. We separate our data mining and data fusion processing into distinct pipelines, each supporting JDL inspired semantic levels of data processing. We conclude by outlining the challenges ahead and our vision for how knowledge-based service architectures can address these challenges.

Crime Open Data Aggregation and Management for the Design of Safer Spaces in Urban Environments

This paper describes the major research and development activities which have been achieved so far since the launch of the DESURBS project (www.desurbs.eu) in 2011. The project focuses on the development of a Decision-Support System Portal (DSSP) which integrates information, data and software modules representing city assets, hazards and processing models that simulate exposures to risks and potential compromise to safety and security. The use of the DSSP will aid the design of safer and more resilient urban spaces. Specifically, it provides security related scenarios with contextual information to support various types of users who specialise in urban spatial design and planning. The DSSP is a web enabled system which is also adapted to mobile devices usage. It is supported with geographic maps and visualised aggregated data from a number of heterogeneous sources. A responsive web design which adapts to the resolution of smart mobile devices has also been achieved. That is, low powered mobiles can still provide map oriented data in a responsive fashion, while using multiple platforms (Android and iOS currently). The first DSSP prototype employs the United Kingdom crime statistics feed of year 2012 and analyses crime trends in 13 English Cities (including Greater London) which are distributed into four major-regions. The DSSP displays raw crime data via a marker on a map, while they are aggregated under specific crime type threads and visualised as “heat maps”. The specific visualisations are aligned to the various administrative regions such as neighbourhoods, catchments and postcodes. It also allows users to explore historical crime trends for a region over time, where crime statistics are contrasted. The scalability of the DSSP was also tested under increasingly large datasets and numbers of users, with tested loads on the map server and the main Django user application. The difference in speed between the mobile and desktop interfaces for a defined set of tasks using the application shall also be performed and presented in the near future.

Advanced Data Analytics and Visualisation for the Management of Human Perception of Safety and Security in Urban Spaces

The genesis of this work began during the DESURBS project. The scope of the project was to help build a collaborative decision-support system portal where spatial planning professionals could learn about designing much more secure and safer spaces in urban areas. The portal achieved this via integrating a number of tools under a common, simple to use, interface. However, the deficiencies in the project became apparent with subsequent development. Many of the open data employed changed format while applications were increasingly custom built for a single dataset. In order to overcome this a system called KnowDS was redesigned. The essence of the new design includes decoupling acquisition, analysis and overall presentation of data components. The acquisition component was designed to snap-shot the “data providing methods” and query data provenance in a similar way to a source code repository. The analysis component is built under a number of modular tools with a common interface which allows analysis to build in a plugp and they clearly demonstrate the capacity of the new system while they actively generate new knowledge about safety in urban spaces.

Context Ontology Modelling for Improving Situation Awareness and Crowd Evacuation from Confined Spaces

Crowd evacuation management at large venues such as airports, stadiums, cruise ships or metro stations requires the deployment and access to a Common Operational Picture (COP) of the venue, with real-time intelligent contextual interpretation of crowd behaviour. Large CCTV and sensor network feeds all provide important but heterogeneous observations about crowd safety at the venue of interest. Hence, these observations must be critically analyzed and interpreted for supporting security managers of crowd safety at venues. Specifically, the large volume of the generated observations needs to be interpreted in context of the venue operational grounds, crowd-gathering event times and the knowledge on crowd expected behaviour. In this paper, a new context ontology modelling approach is introduced. It is based on knowledge about venue background information, expected crowd behaviours and their manifested features of observations. The aim is to improve situation awareness about crowd safety in crisis management and decision-support.