On Eliminating Static Shadow False Alarms in Automatic Incident Detection Systems

2006 ◽  
Author(s):  
M. Shehata ◽  
M. Pervez ◽  
T. Burr ◽  
Jun Cai ◽  
W. Badawy ◽  
...  
Keyword(s):  
False Alarms ◽  
Incident Detection ◽  
Detection Systems ◽  
Automatic Incident Detection

scholarly journals Automatic incident detection in smart city using multiple traffic flow parameters via V2X communication

2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881584 ◽  
Author(s):  
Zafar Iqbal ◽  
Majid Iqbal Khan
Keyword(s):  
Data Collection ◽  
Smart City ◽  
Intelligent Transportation System ◽  
Formal Analysis ◽  
Traffic Density ◽  
False Alarms ◽  
Incident Detection ◽  
Lane Change ◽  
Detection Systems ◽  
Automatic Incident Detection

Recent research trends in intelligent transportation system are focused toward developing automatic incident detection systems to deal with on-road incidents including accidents, traffic congestion, and jamming which cause damage to precious human lives and financial losses. Most of the existing automatic incident detection systems use fixed detectors to detect traffic parameters like occupancy, speed, and lane change information. These systems are prone to delay, inaccuracy, and false alarms during data collection and processing due to line of sight and short-range communication, weather conditions, road repairing, and driver’s driving patterns. Moreover, these systems are designed for freeways/highways and are less compatible with city scenario due to its highly variable traffic density factor. To overcome these deficiencies, an effective and robust approach for automatic incident detection for smart city is developed using smart roads in association with roadside units for data collection and data processing, respectively. The incident confidence factor of the algorithm is based not only on speed and lane change parameters but also on acceleration, orientation, and deviation factors that are integrated to cope with peak/non-peak traffic hours. The integration of multiple parameters increases the incident belief factor and hence the accuracy of incident detection. The complete algorithm is mathematically described using the notions of set theory and then formal analysis assures that the algorithm would be less susceptible to runtime and logical errors during simulations.

Video-Based Automatic Incident Detection for Smart Roads: The Outdoor Environmental Challenges Regarding False Alarms

2008 ◽  
Vol 9 (2) ◽  
pp. 349-360 ◽  
Author(s):  
Mohamed S. Shehata ◽  
Jun Cai ◽  
Wael Maged Badawy ◽  
Tyson W. Burr ◽  
Muzamil S. Pervez ◽  
...  
Keyword(s):  
False Alarms ◽  
Incident Detection ◽  
Environmental Challenges ◽  
Automatic Incident Detection

DEVELOPING A REAL-WORLD TESTBED FOR AUTOMATIC INCIDENT DETECTION SYSTEMS

2006 ◽  
Vol 39 (12) ◽  
pp. 25-30 ◽  
Author(s):  
Roger Browne ◽  
Simon Foo ◽  
Baher Abdulhai ◽  
Fred Hall
Keyword(s):  
Real World ◽  
Incident Detection ◽  
Detection Systems ◽  
Automatic Incident Detection

scholarly journals DETECÇÃO DE INCIDENTES EM UM TÚNEL URBANO CONGESTIONADO: UM ESTUDO DE CASO SOBRE O TÚNEL REBOUÇAS NA CIDADE DO RIO DE JANEIRO

2017 ◽  
Vol 3 (3) ◽  
pp. 86-100
Author(s):  
Marina Leite de Barros Baltar ◽  
Paulo Cezar Martins Ribeiro
Keyword(s):  
Rio De Janeiro ◽  
Detection System ◽  
Theoretical Method ◽  
False Alarms ◽  
Incident Detection ◽  
Number Of False Alarms ◽  
Automatic Incident Detection ◽  
The Moment ◽  
Janeiro City

The objective of this research is to develop a theoretical method capable of eliminating the large number of false alarms resulted of traffic stopping on the automatic incident detection system installed in urban tunnels with large traffic flow. This method took in consideration the concept of shocks wave and have with the purpose of predicting the moment that this wave will reach a certain point in the tunnel. After the development of the method, a case study was conducted in the tunnel Rebouças, in Rio de Janeiro city, where there is an automatic incident detection system that generates a large number of false alarms during rush hours. With the suggested methodology, it was observed that it is possible to lower the number of false alarms by predicting the shock waves that hit the tunnel galleries.

scholarly journals A Feasibility Study of the Use of Smartwatches in Wearable Fall Detection Systems

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2254
Author(s):  
Francisco Javier González-Cañete ◽  
Eduardo Casilari
Keyword(s):  
Low Cost ◽  
Fall Detection ◽  
The Elderly ◽  
Point Of View ◽  
False Alarms ◽  
Battery Life ◽  
Area Network ◽  
Battery Lifetime ◽  
Detection Systems ◽  
Operational Aspects

Over the last few years, the use of smartwatches in automatic Fall Detection Systems (FDSs) has aroused great interest in the research of new wearable telemonitoring systems for the elderly. In contrast with other approaches to the problem of fall detection, smartwatch-based FDSs can benefit from the widespread acceptance, ergonomics, low cost, networking interfaces, and sensors that these devices provide. However, the scientific literature has shown that, due to the freedom of movement of the arms, the wrist is usually not the most appropriate position to unambiguously characterize the dynamics of the human body during falls, as many conventional activities of daily living that involve a vigorous motion of the hands may be easily misinterpreted as falls. As also stated by the literature, sensor-fusion and multi-point measurements are required to define a robust and reliable method for a wearable FDS. Thus, to avoid false alarms, it may be necessary to combine the analysis of the signals captured by the smartwatch with those collected by some other low-power sensor placed at a point closer to the body’s center of gravity (e.g., on the waist). Under this architecture of Body Area Network (BAN), these external sensing nodes must be wirelessly connected to the smartwatch to transmit their measurements. Nonetheless, the deployment of this networking solution, in which the smartwatch is in charge of processing the sensed data and generating the alarm in case of detecting a fall, may severely impact on the performance of the wearable. Unlike many other works (which often neglect the operational aspects of real fall detectors), this paper analyzes the actual feasibility of putting into effect a BAN intended for fall detection on present commercial smartwatches. In particular, the study is focused on evaluating the reduction of the battery life may cause in the watch that works as the core of the BAN. To this end, we thoroughly assess the energy drain in a prototype of an FDS consisting of a smartwatch and several external Bluetooth-enabled sensing units. In order to identify those scenarios in which the use of the smartwatch could be viable from a practical point of view, the testbed is studied with diverse commercial devices and under different configurations of those elements that may significantly hamper the battery lifetime.

A New Approach to Pipeline Leak Detection Using Electromagnetic Sensing

2016 ◽  
Author(s):  
Chris Dawson ◽  
Stuart Inkpen ◽  
Chris Nolan ◽  
David Bonnell
Keyword(s):  
Leak Detection ◽  
False Alarms ◽  
Detection Accuracy ◽  
Minimal Risk ◽  
Detection Systems ◽  
Acoustic Signatures ◽  
Cost System ◽  
Trade Offs ◽  
In Situ Sensors ◽  
Operational Range

Many different approaches have been adopted for identifying leaks in pipelines. Leak detection systems, however, generally suffer from a number of difficulties and limitations. For existing and new pipelines, these inevitably force significant trade-offs to be made between detection accuracy, operational range, responsiveness, deployment cost, system reliability, and overall effectiveness. Existing leak detection systems frequently rely on the measurement of secondary effects such as temperature changes, acoustic signatures or flow differences to infer the existence of a leak. This paper presents an alternative approach to leak detection employing electromagnetic measurements of the material in the vicinity of the pipeline that can potentially overcome some of the difficulties encountered with existing approaches. This sensing technique makes direct measurements of the material near the pipeline resulting in reliable detection and minimal risk of false alarms. The technology has been used successfully in other industries to make critical measurements of materials under challenging circumstances. A number of prototype sensors were constructed using this technology and they were tested by an independent research laboratory. The test results show that sensors based on this technique exhibit a strong capability to detect oil, and to distinguish oil from water (a key challenge with in-situ sensors).

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