KEYWORDS: Security technologies, Video surveillance, Information security, In vitro testing, System integration, Control systems, Information science, Telecommunications, In vivo imaging
Complementing the ACI/IATA efforts, the FLYSEC European H2020 Research and Innovation project (http://www.fly-sec.eu/) aims to develop and demonstrate an innovative, integrated and end-to-end airport security process for passengers, enabling a guided and streamlined procedure from the landside to airside and into the boarding gates, and offering for an operationally validated innovative concept for end-to-end aviation security. FLYSEC ambition turns through a well-structured work plan into: (i) innovative processes facilitating risk-based screening; (ii) deployment and integration of new technologies and repurposing existing solutions towards a risk-based Security paradigm shift; (iii) improvement of passenger facilitation and customer service, bringing security as a real service in the airport of tomorrow;(iv) achievement of measurable throughput improvement and a whole new level of Quality of Service; and (v) validation of the results through advanced “in-vitro” simulation and “in-vivo” pilots. On the technical side, FLYSEC achieves its ambitious goals by integrating new technologies on video surveillance, intelligent remote image processing and biometrics combined with big data analysis, open-source intelligence and crowdsourcing. Repurposing existing technologies is also in the FLYSEC objectives, such as mobile application technologies for improved passenger experience and positive boarding applications (i.e. services to facilitate boarding and landside/airside way finding) as well as RFID for carry-on luggage tracking and quick unattended luggage handling. In this paper, the authors will describe the risk based airport security management system which powers FLYSEC intelligence and serves as the backend on top of which FLYSEC’s front end technologies reside for security services management, behaviour and risk analysis.
KEYWORDS: Data modeling, Received signal strength, Error analysis, Statistical analysis, Systems modeling, Computer simulations, Detection and tracking algorithms, Data analysis, Non-line-of-sight propagation, Performance modeling
Obtaining location information can be of paramount importance in the context of pervasive and context-aware computing applications. Many systems have been proposed to date, e.g. GPS that has been proven to offer satisfying results in outdoor areas. The increased effect of large and small scale fading in indoor environments, however, makes localization a challenge. This is particularly reflected in the multitude of different systems that have been proposed in the context of indoor localization (e.g. RADAR, Cricket etc). The performance of such systems is often validated on vastly different test beds and conditions, making performance comparisons difficult and often irrelevant. The Locus analytical framework incorporates algorithms from multiple disciplines such as channel modeling, non-uniform random number generation, computational geometry, localization, tracking and probabilistic modeling etc. in order to provide: (a) fast and accurate signal propagation simulation, (b) fast experimentation with localization and tracking algorithms and (c) an in-depth analysis methodology for estimating the performance limits of any Received Signal Strength localization system. Simulation results for the well-known Fingerprinting and Trilateration algorithms are herein presented and validated with experimental data collected in real conditions using IEEE 802.15.4 ZigBee modules. The analysis shows that the Locus framework accurately predicts the underlying distribution of the localization error and produces further estimates of the system’s performance limitations (in a best-case/worst-case scenario basis).
KEYWORDS: Antennas, Multiplexers, Computer architecture, Multiplexing, Received signal strength, Control systems, Statistical analysis, Algorithm development, System identification, Electromagnetism
Radio frequency identification (RFID) systems based on passive tags are used successfully in a wide range of object
identification applications. However, the increasing needs to meet new demands on applications of localization and
tracking create a new field for evolution of the RFID technology. This paper presents the design, implementation, and
evaluation of a cost-effective localization system for in-building usage that is able to localize objects that carry passive
RFID tags. The RFID reading is performed by a single Reader and an array of directional antennas through multiplexing.
Evaluation and experimental results from three localization algorithms based on RSSI are presented.
Indoor localization is considered to be a key aspect of future context-aware, ubiquitous and pervasive systems, while
Wireless Sensor Networks (WSNs) are expected to constitute the critical infrastructure in order to sense and interact with
the environment surrounding them. In the context of developing ambient-assisted living and aftermath crisis mitigation
services, we are implementing WAX-ROOM, a WSN specially developed for indoor localization but at the same time
able to sense and interact with the environment. Currently, WAX-ROOM incorporates three different localization
techniques and an optimal fusion rule. The proposed WSN's architecture and advantages, as well as measurements
results regarding its performance in terms of localization accuracy are presented herein, demonstrating the eligibility of
the proposed platform for indoor localization.
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