Research of distorted vehicle magnetic signatures recognitions, for length estimation in real traffic conditions

Reliable cost-effective traffic monitoring stations are a key component of intelligent transportation systems (ITS). While modern surveillance camera systems provide a high amount of data, due to high installation price or invasion of drivers’ personal privacy, they are not the right technology. Therefore, in this paper we introduce a traffic flow parameterization system, using a built-in pavement sensing hub of a pair of AMR (anisotropic magneto resistance) magnetic field and MEMS (micro-electromechanical system) accelerometer sensors. In comparison with inductive loops, AMR magnetic sensors are significantly cheaper, have lower installation price and cause less intrusion to the road. The developed system uses magnetic signature to estimate vehicle speed and length. While speed is obtained from the cross-correlation method, a novel vehicle length estimation algorithm based on characterization of the derivative of magnetic signature is presented. The influence of signature filtering, derivative step and threshold parameter on estimated length is investigated. Further, accelerometer sensors are employed to detect when the wheel of vehicle passes directly over the sensor, which cause distorted magnetic signatures. Results show that even distorted signatures can be used for speed estimation, but it must be treated with a more robust method. The database during the real-word traffic and hazard environmental condition was collected over a 0.5-year period and used for method validation.Lietuvos Mokslo Taryba | Ref. S-MIP-21-3

Two thermocouples low power wireless sensors network

This paper presents technologies and experiments of a wireless sensors using two thermocouples network. It was established that the energy consumption during sensor measurements is usually up to 10 times lower compared to the energy consumption at the time of establishing wireless connection for most protocols. For this reason, new simplified wireless connection protocol was created. Extremely low energy wireless sensor hardware and software equipment was designed. The newly created universal measurement module allows the use not only thermocouples, but also various types of analogue sensors, thermocouples, pressure bridges, Resistance Temperature Detectors (RTD) and digital sensors communicating through SPI or I2C interface. The newly designed specific power supply scheme allows to supply the sensor and radio module with the voltage from 1.2 V to 3.6 V batteries. When conducting periodic measurements every second, the use of newly designed hardware and software equipment enables the wireless sensor to be operated for up to 3 years from two 1200 mAh capacity batteries.A grant (No. SEN-10/15) from the Research Council of Lithuania. Project acronym: “CaSpine”.http://www.journals.elsevier.com/locate/qeue2019-02-20hj2018Electrical, Electronic and Computer Engineerin

Dynamic Vehicle Detection via the Use of Magnetic Field Sensors

The vehicle detection process plays the key role in determining the success of intelligent transport management system solutions. The measurement of distortions of the Earth’s magnetic field using magnetic field sensors served as the basis for designing a solution aimed at vehicle detection. In accordance with the results obtained from research into process modeling and experimentally testing all the relevant hypotheses an algorithm for vehicle detection using the state criteria was proposed. Aiming to evaluate all of the possibilities, as well as pros and cons of the use of anisotropic magnetoresistance (AMR) sensors in the transport flow control process, we have performed a series of experiments with various vehicles (or different series) from several car manufacturers. A comparison of 12 selected methods, based on either the process of determining the peak signal values and their concurrence in time whilst calculating the delay, or by measuring the cross-correlation of these signals, was carried out. It was established that the relative error can be minimized via the Z component cross-correlation and Kz criterion cross-correlation methods. The average relative error of vehicle speed determination in the best case did not exceed 1.5% when the distance between sensors was set to 2 m

Passing Vehicle Road Occupancy Detection Using the Magnetic Sensor Array

The increasing presence of vehicles on roads necessitates intelligent traffic management solutions in areas where video cameras cannot be utilized. Currently, there are limited choices for depersonalized vehicle reidentification systems. This paper introduces a system that later will be used for vehicle reidentification. The system uses anisotropic magnetoresistive sensors and is based on the hypothesis that each vehicle leaves unique magnetic signatures which can be used for comparison and matching. Vehicle location on the road perpendicular to sensor array detection methodology is presented in this work. An array of magnetic sensors is installed in asphalt across the vehicle’s driving direction. The system continuously measures Earth’s natural magnetic field and detects distortions when vehicles pass an array of a sensors and then logs magnetic signatures. Useful parameters from raw sensor axes are calculated– modules and derivatives. Applying signal-to-noise ratio calculation for module derivatives between ambient noise and signal gives important features for neural network input. Different types of neural network architectures and output result interpretation techniques are investigated. Further, after evaluating network output it is possible to label sensor nodes that are directly beneath the vehicle. Experiment results show that implemented algorithm is highly sufficient for valid sensors under the vehicle selection. Correct sensor selection is important for further re-identification algorithms

Erroneous Vehicle Velocity Estimation Correction Using Anisotropic Magnetoresistive (AMR) Sensors

Magnetic field sensors installed in the road infrastructure can be used for autonomous traffic flow parametrization. Although the main goal of such a measuring system is the recognition of the class of vehicle and classification, velocity is the essential parameter for further calculation and it must be estimated with high reliability. In-field test campaigns, during actual traffic conditions, showed that commonly accepted velocity estimation methods occasionally produce highly erroneous results. For anomaly detection, we propose a criterion and two different correction algorithms. Non-linear signal rescaling and time-based segmentation algorithms are presented and compared for faulty result mitigation. The first one consists of suppressing the highly distorted signal peaks and looking for the best match with cross-correlation. The second approach relies on signals segmentation according to the feature points and multiple cross-correlation comparisons. The proposed two algorithms are evaluated with a dataset of over 300 magnetic signatures of a vehicle from unconstraint traffic conditions. Results show that the proposed criteria highlight all greatly faulty results and that the correction algorithms reduce the maximum error by twofold, but due to the increased mean error, mitigation technics shall be used explicitly with distorted signals

Feasibility research of non-invasive methods for interstitial fluid level measurement

This article explores a non-invasive method to determine interstitial fluid level and pressure in tissue. Interdigital electrodes were chosen by simulated results in software “Comsol multiphysis 4.3a”. Environment model similar to human body was created. Measurements were carried out at different situations which can occur during preoperative and afterwards surgery. Non-invasive method decreases possibility of infection and will improve recovery process in postoperative period

Two thermocouples low power wireless sensors network

This paper presents technologies and experiments of a wireless sensors using two thermocouples network. It was established that the energy consumption during sensor measurements is usually up to 10 times lower compared to the energy consumption at the time of establishing wireless connection for most protocols. For this reason, new simplified wireless connection protocol was created. Extremely low energy wireless sensor hardware and software equipment was designed. The newly created universal measurement module allows the use not only thermocouples, but also various types of analogue sensors, thermocouples, pressure bridges, Resistance Temperature Detectors (RTD) and digital sensors communicating through SPI or I2C interface. The newly designed specific power supply scheme allows to supply the sensor and radio module with the voltage from 1.2 V to 3.6 V batteries. When conducting periodic measurements every second, the use of newly designed hardware and software equipment enables the wireless sensor to be operated for up to 3 years from two 1200 mAh capacity batteries.A grant (No. SEN-10/15) from the Research Council of Lithuania. Project acronym: “CaSpine”.http://www.journals.elsevier.com/locate/qeue2019-02-20hj2018Electrical, Electronic and Computer Engineerin