A Parameterized Algebra for Event Notification Services

Event notification services are used in various applications such as digital libraries, stock tickers, traffic control, or facility management. However, to our knowledge, a common semantics of events in event notification services has not been defined so far. In this paper, we propose a parameterized event algebra which describes the semantics of composite events for event notification systems. The parameters serve as a basis for flexible handling of duplicates in both primitive and composite events

Estimating and abstracting the 3D structure of feline bones using neural networks on X-ray (2D) images

Computing 3D bone models using traditional Computed Tomography (CT) requires a high-radiation dose, cost and time. We present a fully automated, domain-agnostic method for estimating the 3D structure of a bone from a pair of 2D X-ray images. Our triplet loss-trained neural network extracts a 128-dimensional embedding of the 2D X-ray images. A classifier then finds the most closely matching 3D bone shape from a predefined set of shapes. Our predictions have an average root mean square (RMS) distance of 1.08 mm between the predicted and true shapes, making our approach more accurate than the average achieved by eight other examined 3D bone reconstruction approaches. Each embedding extracted from a 2D bone image is optimized to uniquely identify the 3D bone CT from which the 2D image originated and can serve as a kind of fingerprint of each bone; possible applications include faster, image content-based bone database searches for forensic purposes

Privacy-Preserving Crowd Incident Detection: A Holistic Experimental Approach

International audienceDetecting dangerous situations is crucial for emergency management. Surveillance systems detect dangerous situations by analyzing crowd dynamics. This paper presents a holis-tic video-based approach for privacy-preserving crowd density estimation. Our experimental approach leverages distributed , on-board pre-processing, allowing privacy as well as the use of low-power, low-throughput wireless communications to interconnect cameras. We developed a multi-camera grid-based people counting algorithm which provides the density per cell for an overall view on the monitored area. This view comes from a merger of infrared and Kinect camera data. We describe our approach using a layered model for data aggregation and abstraction together with a work-flow model for the involved software components, focusing on their functionality. The power of our approach is illustrated through the real-world experiment that we carried out at the Schönefeld airport in the city of Berlin

SAFEST: A Framework for Early Security Triggers in Public Spaces

International audiencePublic spaces such as airports, railway stations or stadiums bring together large numbers of people on a quite limited space to use a security-sensitive infrastructure. Electronic security systems may help to provide better and faster security, as well as safety for the general public. Application scenarios may include intrusion detection and monitoring of large crowds in order to provide guidance in case of unexpected events (e.g., a mass panic). However, current security systems used within the public infrastructure are typically expensive, non-trivial to deploy, difficult to operate and maintain, prone to malfunction due to individual component failures, and generally lack citizen privacy-friendliness. The advent of novel, large-scale distributed security systems based on wireless, lightweight sensors may enhance security and safety in public spaces. In this realm, SAFEST is a project aiming at analyzing the social context of area surveillance and developing a system that can fulfill this task, both in terms of technology as well as acceptance by the general public. The targeted system will operate in a distributed way, collect anonymized data, securely transfer this data to a central location for evaluation, and - if necessary - notify the operator or issue alerts directly to the general public. Work on the technical aspects of the system is accompanied by social studies investigating the individual perception of risk and the methods for reaching public acceptance of the technical solutions

How to turn the Fast-Track into a Fast-Track: Process integration for evaluation of the quality of Digital Health Applications (DiGAs) on the example of the German Fast-Track Process

In this paper, we address the research question of which integration points in the \textit{German Fast-Track process} are particularly well suited for the integration of evaluation platforms for digital health applications. For this purpose, possible integration points are first identified and then analyzed with the help of a utility analysis with regard to the posed research question. Finally, a recommendation for action is made based on the results of the conducted utility analysis

Multi-Camera Crowd Monitoring: The SAFEST Approach

International audienceThis paper presents the current state of people counting approach created for the SAFEST project. A video based surveillance system for monitoring crowd behaviour is developed. The system detects dangerous situations by analysing the dynamics of the crowd density. Therefore we developed a grid-based people counting algorithm which provides density per cell for the global view on the monitored area. Since multiple cameras may observe same parts of the monitored area, the challenge is not only to count people seen by single cameras , but also to merge the views. Therefore we first detect people seen by each camera separately and then sum the results to a global representation. In order to avoid multiple counting of same objects, the output of cameras in the overlapped regions are weighted

Area & Perimeter Surveillance in SAFEST using Sensors and the Internet of Things

International audienceSAFEST is a project aiming to provide a comprehensive solution to ensure the safety and security of the general public and critical infrastructures. The approach of the project is to design a lightweight, distributed system using heterogeneous, networked sensors, able to aggregate the input of a wide variety of signals (e.g. camera, PIR, radar, magnetic, seismic, acoustic). The project aims for a proof-of-concept demonstration focusing on a concrete scenario: crowd monitoring, area and perimeter surveillance in an airport, realized with a prototype of the system, which must be deployable and foldable overnight, and leverage autoconfiguration based on wireless communications and Internet of Things. This paper reviews the progress towards reaching this goal, which is planned for 2015

Towards a Toolbox for Geographic User Interfaces

User interfaces are a prominent part of applications that manipulate graphic data (geography, cartography, CAD/CAM, ...). Although some work has been done recently in this area, each system usually has its own ad hoc user interface built from scratch, and there is no user interface model general enough for customizing the presentation of a specific application which handles graphic data. This paper presents a conceptual model for describing user interfaces of systems manipulating maps in an object-oriented environment. The model proposed here is split into two levels: (i) the Interaction level and (ii) the External Spatial level. The Interaction level deals with high level interface objects, such as windows, as well as the interaction with the end user. In particular, we see the necessity of introducing a new kind of window devoted to map editing. The External Spatial level deals with objects which come from a mapping of the database objects onto objects manipulated by the end user. Th..

Open GIS: A Tool for Environmental Information Management

this paper, we concentrate on some recent GIS developments and we show that environmental data can easily be handled by a new generation of GIS called open GIS