A field experience for a vehicle recognition system using magnetic sensors

Burresi, Giovanni; Giorgi, Roberto

doi:10.1109/meco.2015.7181897

Cited by 17 publications

(12 citation statements)

References 3 publications

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“…Biometric recognition requires physical contact between recognition device, which has no application value in WPT [20], [21]. For magnetic recognition, the data of objects may be damaged in WPT, which affects the accuracy [22]. IC cards require contact to read and write data, only can be applied in situations with a certain transfer distance [23].…”

Section: Introductionmentioning

confidence: 99%

A Novel Method of Wireless Power Transfer Identification and Resonance Decoupling Based on Frequency Hopping Communication

Yang

Huo

et al. 2019

IEEE Access

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Aiming at the risk of electricity theft of wireless power transfer (WPT) technology due to its untargeted and non-directional characteristics, a novel method of identification and resonance decoupling based on frequency hopping communication is proposed. The basic principle of the identification method is to make the resonant frequency of transmitter coil and receiver coil jump synchronously and randomly according to the pseudo-random code sequence, which can identify the load in single-source single-user mode and single-source multiuser mode respectively by calculating energy consumption ratio. And if user is illegal, then the resonant frequency of system jumps randomly to cut off the power, which is named resonance decoupling. The experimental circuit is designed on the basis of theoretical analysis and the method is verified. The test results are consistent with theoretical analysis, which has proved the validity of the method. This paper not only provides a solution to the power management of WPT system, but also is a support for the measurement of electricity, moreover, it is conducive to the further application and promotion of WPT technology. INDEX TERMS Frequency hopping communication, identification and resonance decoupling, pseudorandom code, wireless power transfer.

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Section: Introductionmentioning

confidence: 99%

A Novel Method of Wireless Power Transfer Identification and Resonance Decoupling Based on Frequency Hopping Communication

Yang

Huo

et al. 2019

IEEE Access

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“…In this way, the system may determine automatically the manufacturer and the type of the captured vehicle images. The authors in [20] present a vehicle recognition system prototype using magnetic sensor techniques where more complex hardware and processing are utilized.…”

Section: Introductionmentioning

confidence: 99%

IoT-Driven Automated Object Detection Algorithm for Urban Surveillance Systems in Smart Cities

2018

IEEE Internet Things J.

120

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Automated object detection algorithm is an important research challenge in intelligent urban surveillance systems for IoT and smart cities applications. In particular, smart vehicle license plate recognition (VLPR) and vehicle detection are recognized as core research issues of these IoT-driven intelligent urban surveillance systems. They are key techniques in most of the traffic related IoT applications, such as road traffic real-time monitoring, security control of restricted areas, automatic parking access control, searching stolen vehicles, etc. In this paper, we propose a novel unified method of automated object detection for urban surveillance systems. We use this novel method to determine and pick out the highest energy frequency areas of the images from the digital camera imaging sensors, that is, either to pick the vehicle license plates or the vehicles out from the images. Our proposed method can not only help to detect object vehicles rapidly and accurately, but also can be used to reduce big data volume needed to be stored in urban surveillance systems.

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“…Magnetic sensors have several excellent advantages; they are low-cost, energy-efficient, small, wireless, and weather-independent sensors. Traffic surveillance by magnetic technology and corresponding wireless sensor networks have been proposed and implemented in related research areas, especially vehicle detection and counting [9,10,11,12,13,16,17,18,19,20], speed estimation [10,11,12], and vehicle classification [10,11,13,19,21,22,23,24]. …”

Section: Introductionmentioning

confidence: 99%

Traffic Vehicle Counting in Jam Flow Conditions Using Low-Cost and Energy-Efficient Wireless Magnetic Sensors

Bao

et al. 2016

Sensors

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The jam flow condition is one of the main traffic states in traffic flow theory and the most difficult state for sectional traffic information acquisition. Since traffic information acquisition is the basis for the application of an intelligent transportation system, research on traffic vehicle counting methods for the jam flow conditions has been worthwhile. A low-cost and energy-efficient type of multi-function wireless traffic magnetic sensor was designed and developed. Several advantages of the traffic magnetic sensor are that it is suitable for large-scale deployment and time-sustainable detection for traffic information acquisition. Based on the traffic magnetic sensor, a basic vehicle detection algorithm (DWVDA) with less computational complexity was introduced for vehicle counting in low traffic volume conditions. To improve the detection performance in jam flow conditions with a “tailgating effect” between front vehicles and rear vehicles, an improved vehicle detection algorithm (SA-DWVDA) was proposed and applied in field traffic environments. By deploying traffic magnetic sensor nodes in field traffic scenarios, two field experiments were conducted to test and verify the DWVDA and the SA-DWVDA algorithms. The experimental results have shown that both DWVDA and the SA-DWVDA algorithms yield a satisfactory performance in low traffic volume conditions (scenario I) and both of their mean absolute percent errors are less than 1% in this scenario. However, for jam flow conditions with heavy traffic volumes (scenario II), the SA-DWVDA was proven to achieve better results, and the mean absolute percent error of the SA-DWVDA is 2.54% with corresponding results of the DWVDA 7.07%. The results conclude that the proposed SA-DWVDA can implement efficient and accurate vehicle detection in jam flow conditions and can be employed in field traffic environments.

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A field experience for a vehicle recognition system using magnetic sensors

Cited by 17 publications

References 3 publications

A Novel Method of Wireless Power Transfer Identification and Resonance Decoupling Based on Frequency Hopping Communication

A Novel Method of Wireless Power Transfer Identification and Resonance Decoupling Based on Frequency Hopping Communication

IoT-Driven Automated Object Detection Algorithm for Urban Surveillance Systems in Smart Cities

Traffic Vehicle Counting in Jam Flow Conditions Using Low-Cost and Energy-Efficient Wireless Magnetic Sensors

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