A Practicable Method for Ferromagnetic Object Moving Direction Identification

Zhou, Qianwei; Tong, Guanjun; Li, Baoqing

doi:10.1109/tmag.2012.2191299

Cited by 30 publications

(10 citation statements)

References 21 publications

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“…Because the exact movement direction and value of magnetic moment are unknown, we set default m = (1, 1, 1) for simulation. [21], [22], [19], [23]. Fig.…”

Section: A Magnetic Dipole Modelmentioning

confidence: 99%

MagSpeed: A Novel Method of Vehicle Speed Estimation Through A Single Magnetic Sensor

Feng

Mao

Cheng

et al. 2019

2019 IEEE Intelligent Transportation Systems Conference (ITSC)

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Internet of Things (IoT) is playing an increasingly important role in Intelligent Transportation Systems (ITS) for real-time sensing and communication. In ITS, the velocity of vehicles provides important information for traffic management. However, the present methods for monitoring vehicle speed have many shortcomings. In this paper, we propose MagSpeed, a novel vehicle speed estimation method based on a small magnetic sensor. The developed magnetic sensor system is wireless, cost-effective, and environmental-friendly. Through modelling of local magnetic field perturbations caused by a moving vehicle, we extract the characteristics of magnetic waveforms for speed estimation. In addition, we compare the performance of the models with other speed estimation algorithms, which shows the superior accuracy of the proposed technique in speed estimation.

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“…Because the exact movement direction and value of magnetic moment are unknown, we set default m = (1, 1, 1) for simulation. [21], [22], [19], [23]. Fig.…”

Section: A Magnetic Dipole Modelmentioning

confidence: 99%

MagSpeed: A Novel Method of Vehicle Speed Estimation Through A Single Magnetic Sensor

Feng

Mao

Cheng

et al. 2019

2019 IEEE Intelligent Transportation Systems Conference (ITSC)

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“…Wireless sensor network (WSN) has been widely used to monitor wild fields events [1]- [6], since it can detect the activity of the intruding target through a large number of smart sensor nodes. In the monitoring system, the information of sensor nodes is fused to accurately detect the intrusion [7], identify the target type and estimate the moving direction [8].…”

Section: Introductionmentioning

confidence: 99%

Single-Mode Wild Area Surveillance Sensor With Ultra-Low Power Design Based on Microphone Array

et al. 2019

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Acoustic sensors are used as an important sensor component in wireless sensor networks (WSNs) for wild environmental monitoring, because of its small size, light weight, and low power consumption. To further utilize the superiorities of acoustic sensor, this paper aims to design a single-mode wild area surveillance sensor based on acoustic sensors, which have the advantages of practicality, low hardware power consumption, and low software complexity. The proposed algorithm can effectively suppress wind noise and improve the performance of target detection, classification and direction of arrival (DOA) estimation. The power consumption test results show that the designed micro-sensor node has low power consumption of about 13.8 mW in on-duty mode and long-term continuous monitoring capability of about 33 days. The field experiment results reveal that the node has favorable performance in detection (detection rate as high as 96% with false alarm rate under 5%), tracking (error is less than 7.6 degree), and target classification (accuracy is greater than 92.6%).

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“…But these threshold based algorithms are not valid to all situations and often leads to a high false alarm rate. In order to solve this problem, adaptive threshold algorithms are presented [8,9]. However, thresholdbased vehicle detection algorithms have congenital defects.…”

Section: Introductionmentioning

confidence: 99%

“…The acoustic sensor and infrared sensor are vulnerable to noise in deployed environments. Magnetic sensors based on magneto resistors have recently been proposed for vehicle detection [8,11] because they are quite sensitive, small and more immune to environmental factors such as rain, wind, snow or fog than sensing systems based on video cameras, ultrasound or infrared radiation.Many algorithms have been proposed for dynamic traffic information acquisition system based on wireless AMR sensor. The PATH program of the University of California, Berkeley [12,13] had first extensively explored of AMR sensor network based vehicle detection system.…”

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confidence: 99%

A Vehicle Speed Estimation Algorithm Based on Wireless AMR Sensors

Zhang

Zhao

Yuan

2015

Big Data Computing and Communications

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Abstract. This paper proposes an algorithm for vehicle speed estimation based on the use of anisotropic magnetoresistive (AMR) sensors. Speed estimation relies on matching vehicle magnetic signatures from wireless sensors. A scheme based on edit-distance is developed to automatically matching signatures for the vehicles. Experimental results are presented to show that the proposed speed estimation is viable. IntroductionReal time acquisition of traffic information plays a key role in intelligent transportation systems (ITSs). Wireless sensor networks have lots of potential toward providing an ideal solution for traffic information acquisition, such as their low power, small size, low cost, and high accuracy. At present, the sensors used in the traffic information acquisition include the following types: inductive loop detector [1], image (camera) sensor [2,3], acoustic sensor [4,5], infrared sensor [6], ultrasonic sensor [7], etc. The image sensor acquires an abundance of information, but it is vulnerable to bad weather and nighttime operation. The acoustic sensor and infrared sensor are vulnerable to noise in deployed environments. Magnetic sensors based on magneto resistors have recently been proposed for vehicle detection [8,11] because they are quite sensitive, small and more immune to environmental factors such as rain, wind, snow or fog than sensing systems based on video cameras, ultrasound or infrared radiation.Many algorithms have been proposed for dynamic traffic information acquisition system based on wireless AMR sensor. The PATH program of the University of California, Berkeley [12,13] had first extensively explored of AMR sensor network based vehicle detection system. S.Y. Cheung et al. [13] had explored the applications for vehicle detection, speed estimation, and classification. M. Kang et al. [14] proposed a vehicle detector with an AMR sensor and addresses experimental study carried out to show the detector's characteristics and performance. Experiment results show that the vehicle detection accuracy rate is more than 99%, and the accuracy rate to estimate

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A Practicable Method for Ferromagnetic Object Moving Direction Identification

Cited by 30 publications

References 21 publications

MagSpeed: A Novel Method of Vehicle Speed Estimation Through A Single Magnetic Sensor

MagSpeed: A Novel Method of Vehicle Speed Estimation Through A Single Magnetic Sensor

Single-Mode Wild Area Surveillance Sensor With Ultra-Low Power Design Based on Microphone Array

A Vehicle Speed Estimation Algorithm Based on Wireless AMR Sensors

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