Long-range, Seamless Traffic Density Monitoring using Fibre Optic Acoustic Sensing

Accurate real-time traffic sensing is of key importance, especially in the urban environment to be able to optimise traffic flow by intelligent traffic systems (ITS). Often the high density of traffic sensors, needed to achieve an accurate real-time monitoring of important arterial roads, is difficult to implement due to technical contraints or because of high installation cost. Furthermore, existing traffic sensing technology uses sensors that are only able to measure traffic flow on a cross-section of the road where they are installed (typically on a junction), giving no information on the situation in between. An alternative "seamless" measuring technology, is to use floating car data, with Google Maps being the most prominant example. This technology allows to derive traffic information over wide road sections, however it is unable to deliver real- time information, and it relies on the “cooperation” of the data providers (the fleet owner or the mobile phone users). Fiber optic acoustic sensing (FOAS) is a new alternative technology that allows a seamless, real-time monitoring of the road traffic situation over large distances of up to 50 km using the existing telecom fiber optic cable infrastructure. In our previous work we presented an algorithm and results for traffic flow and average speed computation from FOAS raw data at a specific location along a highway and compared it to reference traffic data [1],[2]. In this paper we demonstrate the potential of the seamless nature of the technique by evaluating the traffic density over a length of 25 km of the monitored highway for different days and times of the day

Fusion of heterogenous sensor data in border surveillance

Wide area surveillance has become of critical importance particularly for border control between countries where vast forested land border areas are to be monitored. In this paper we address the problem of the automatic detection of activity in forbidden areas, namely forested land border areas. In order to avoid false detections, often triggered in dense vegetation with single sensors such as radar, in this paper we present a multi sensor fusion and tracking system using passive infrared detectors in combination with automatic person detection from thermal and visual video camera images. The approach combines weighted maps with a rule engine that associates data from multiple weighted maps. The proposed approach is tested on real data collected by the EU FOLDOUT project in a location representative of a range of forested EU borders. The results show that the proposed approach can eliminate single-sensor false detections and enhance accuracy by up to 50%

The future of GPS-based electric power system measurements, operation and control

Much of modern society is powered by inexpensive and reliable electricity delivered by a complex and elaborate electric power network. Electrical utilities are currently using the Global Positioning System-NAVSTAR (GPS) timekeeping to improve the network`s reliability. Currently, GPS synchronizes the clocks on dynamic recorders and aids in post-mortem analysis of network disturbances. Two major projects have demonstrated the use of GPS-synchronized power system measurements. In 1992, the Electric Power Research Institute`s (EPRI) sponsored Phase Measurements Project used a commercially available Phasor Measurements Unit (PMU) to collect GPS-synchronized measurements for analyzing power system problems. In 1995, Bonneville Power Administration (BPA) and Western Area Power Administration (WAPA) under DOE`s and EPRI`s sponsorship launched the Wide Area Measurements (WAMS) project. WAMS demonstrated GPS-synchronized measurements over a large area of their power networks and demonstrated the networking of GPS-based measurement systems in BPA and WAPA. The phasor measurement technology has also been used to conduct dynamic power system tests. During these tests, a large dynamic resistor was inserted to simulate a small power system disturbance

Sektoralisierung als Planungsherausforderung im inklusiven Gemeinwesen

2. Hrsg.: Martin F. Reichstein Förderung durch: Forschungsinstitut für gesellschaftliche Weiterentwicklung (FGW)Seit September 2016 führt das Zentrum für Planung und Evaluation Sozialer Dienste (ZPE) der Universität Siegen das Forschungsprojekt „Koordinationspotenziale kommunaler Teilhabepolitik in der Pflege, Behindertenhilfe und Sozialpsychiatrie (KoKoP)“ durch. Das Projekt wird im Rahmen des Programms „Vorbeugende Sozialpolitik“ des nordrheinwestfä- lischen Forschungsinstituts für Gesellschaftliche Weiterentwicklung (FGW) finanziell gefördert. Ziel des Projektes ist es, anhand empirischer Untersuchungen Erkenntnisse darüber zu gewinnen, welche Möglichkeiten für Kommunen bestehen, durch Planung und Koordination die Wirkungen von Teilhabeleistungen in den Leistungsbereichen der Pflege, Behindertenhilfe und Sozialpsychiatrie zu optimieren. Zudem soll der Frage nachgegangen werden, wie professionelle Hilfen stärker mit informellen Ressourcen im Vor- und Umfeld des Leistungsgeschehens verknüpft werden können. Mögliche Problemquellen werden u.a. in einer ausgeprägten Sektoralisierung des Leistungsgeschehens, mangelnder Kooperation sowie in einer geringen Sozialraumorientierung vermutet. Im Rahmen eines eintägigen Expertenworkshops am 14. November 2017 wurden zum einen Zwischenergebnisse bisheriger Untersuchungen vorgestellt und diskutiert. Zum anderen wurden in drei Arbeitsgruppen zentrale Fragestellungen des Projekts erörtert. Der vorliegende Band ist eine Zusammenschau von Beiträgen einzelner Teilnehmer*innen dieses Workshops

Comparative genome structure, secondary metabolite, and effector coding capacity across Cochliobolus pathogens.

The genomes of five Cochliobolus heterostrophus strains, two Cochliobolus sativus strains, three additional Cochliobolus species (Cochliobolus victoriae, Cochliobolus carbonum, Cochliobolus miyabeanus), and closely related Setosphaeria turcica were sequenced at the Joint Genome Institute (JGI). The datasets were used to identify SNPs between strains and species, unique genomic regions, core secondary metabolism genes, and small secreted protein (SSP) candidate effector encoding genes with a view towards pinpointing structural elements and gene content associated with specificity of these closely related fungi to different cereal hosts. Whole-genome alignment shows that three to five percent of each genome differs between strains of the same species, while a quarter of each genome differs between species. On average, SNP counts among field isolates of the same C. heterostrophus species are more than 25× higher than those between inbred lines and 50× lower than SNPs between Cochliobolus species. The suites of nonribosomal peptide synthetase (NRPS), polyketide synthase (PKS), and SSP-encoding genes are astoundingly diverse among species but remarkably conserved among isolates of the same species, whether inbred or field strains, except for defining examples that map to unique genomic regions. Functional analysis of several strain-unique PKSs and NRPSs reveal a strong correlation with a role in virulence

ADOSE – Bio-Inspired In-Vehicle Sensor Technology for Active Safety

Reliable Advanced Driver Assistance Systems (ADAS) are intended to assist the driver under various traffic, weather and other environment conditions. The growing traffic requires sensors and systems which handle difficult urban and non-urban scenarios. For such systems new cost-efficient sensor technologies are developed and evaluated in the EU-FP7 project ADOSE (reliable Application-specific Detection of road users with vehicle On-board Sensors, providing the vehicle with a virtual safety belt by addressing complementary safety functions

Real-Time Train Tracking from Distributed Acoustic Sensing Data

In the context of railway safety, it is crucial to know the positions of all trains moving along the infrastructure. In this contribution, we present an algorithm that extracts the positions of moving trains for a given point in time from Distributed Acoustic Sensing (DAS) signals. These signals are obtained by injecting light pulses into an optical fiber close to the railway tracks and measuring the Rayleigh backscatter. We show that the vibrations of moving objects can be identified and tracked in real-time yielding train positions every second. To speed up the algorithm, we describe how the calculations can partly be based on graphical processing units. The tracking quality is assessed by counting the inaccurate and lost train tracks for two different types of cable installations

Seamless Distributed Traffic Monitoring by Distributed Acoustic Sensing (DAS) using existing Fiber Optic Cable Infrastructure

Accurate real-time traffic sensing is of key importance, especially in the urban environment to be able to optimize traffic flow by intelligent traffic systems (ITS). Often the high density of traffic sensors, needed to achieve an accurate real-time monitoring of important arterial roads, is difficult to implement due to technical contraints or because of installation cost. Furthermore, existing traffic sensing technology uses sensors that are only able to measure traffic flow on a cross-section of the road where they are installed (typically on a junction), giving no information on the situation in between. An alternative "seamless" measuring technology, is to use floating car data, with Google Maps being the most prominant example. This technology allows to derive traffic information over wide road sections, however it is unable to deliver real-time information, and it relies on the "cooperation" of the data providers (the fleet owner or the mobile phone users). Distributed acoustic sensing (DAS) is a relatively new technology that allows a seamless, real-time monitoring of the road traffic situation over large distances of up to 50 km using the existing telecom fiber optic cable infrastructure. We present first result of traffic speed estimation performed on a real highway with DAS, over a distance of 19 km and compare them to reference measurements from induction loops

An Assessment of VMS-Rerouting and Traffic Signal Planning with Emission Objectives in an Urban Network – A Case Study for the City of Graz

Kölbl R, Heilmann B, Bauer D, et al. An Assessment of VMS-Rerouting and Traffic Signal Planning with Emission Objectives in an Urban Network – A Case Study for the City of Graz. In: 2015 International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS). Piscataway, NJ: IEEE; 2015