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

A novel seismocardiogram mathematical model for simplified adjustment of adaptive filter

Nonclinical measurements of a seismocardiogram (SCG) can diagnose cardiovascular disease (CVD) at an early stage, when a critical condition has not been reached, and prevents unplanned hospitalization. However, researchers are restricted when it comes to investigating the benefits of SCG signals for moving patients, because the public database does not contain such SCG signals. The analysis of a mathematical model of the seismocardiogram allows the simulation of the heart with cardiovascular disease. Additionally, the developed mathematical model of SCG does not totally replace the real cardio mechanical vibration of the heart. As a result, a seismocardiogram signal of 60 beats per min (bpm) was generated based on the main values of the main artefacts, their duration and acceleration. The resulting signal was processed by finite impulse response (FIR), infinitive impulse response (IRR), and four adaptive filters to obtain optimal signal processing settings. Meanwhile, the optimal filter settings were used to manage the real SCG signals of slowly moving or resting. Therefore, it is possible to validate measured SCG signals and perform advanced scientific research of seismocardiogram. Furthermore, the proposed mathematical model could enable electronic systems to measure the seismocardiogram with more accurate and reliable signal processing, allowing the extraction of more useful artefacts from the SCG signal during any activity.Web of Science1115art. no. 244

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

New Approach for Fertiliser Size Assessment Using Contactless Scanning

The growing population and lack of change in resources of cultivated land have led to the search for more efficient farming solutions. The recovery of soil is facilitated by using chemicals designed for the enrichment of cultivated soil. Fertilisers are made of a combination of various substances that determine not only the chemical but also the shape characteristics of the fertiliser pellets. The effect of the quality of fertilisation on yield size is related to even distribution. Shape and size are closely related to the quality of the fertilisation process. The intense control of the production process would not be possible without automatised and quick measurements within the production line. Constant control is necessary to ensure that the products meet quality standards. The contactless assessment of pellet sizes allows a quick reaction to changes in production quality and reduces the costs arising from the reprocessing of defective pellets. The results of the assessment of pellet volume using their two-dimensional image are presented in this publication. Pellets must be analysed according to their most characteristic position, which can provide valuable information about their properties. The aim is to determine the placement positions of the equipment based on calculations and to compare the results with those of gold-standard equipment. Correctly calibrated equipment ensures that the measurement results match the results of the control equipment of fertiliser producers. Reliable non-contact measurements can reduce the reaction time to production changes

Research of the Operator's Advisory System Based on Fuzzy Logic for Pelletizing Equipment

Fertilizer manufacturing in the chemical industry is closely related with agricultural production. More than a half of raw materials for food products are grown by fertilizing plants. The demand of fertilizers has been constantly increasing along the growth of human population. Fertilizer manufacturers face millions of losses each year due to poor quality products. One of the most common reasons is wrong decisions in control of manufacturing processes. Operator’s experience has the highest influence on this. The paper analyzes the pellet measurement data, collected at the fertilizer plant by using indirect measurements. The results of these measurements are used to construct the model of equipment status control, based on the fuzzy logic. The proposed solution allows to respond to changes in production parameters in a 7-10 times faster manner. On average, the manufacturer with the production volumes of up to 80 tonnes/hour, could have lost about 8400 tonnes/year of high-quality production. The publication seeks symmetry between human and system decision making

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

Vehicle Speed and Length Estimation Using Data from Two Anisotropic Magneto-Resistive (AMR) Sensors

Methods for estimating a car’s length are presented in this paper, as well as the results achieved by using a self-designed system equipped with two anisotropic magneto-resistive (AMR) sensors, which were placed on a road lane. The purpose of the research was to compare the lengths of mid-size cars, i.e., family cars (hatchbacks), saloons (sedans), station wagons and SUVs. Four methods were used in the research: a simple threshold based method, a threshold method based on moving average and standard deviation, a two-extreme-peak detection method and a method based on the amplitude and time normalization using linear extrapolation (or interpolation). The results were achieved by analyzing changes in the magnitude and in the absolute z-component of the magnetic field as well. The tests, which were performed in four different Earth directions, show differences in the values of estimated lengths. The magnitude-based results in the case when cars drove from the South to the North direction were even up to 1.2 m higher than the other results achieved using the threshold methods. Smaller differences in lengths were observed when the distances were measured between two extreme peaks in the car magnetic signatures. The results were summarized in tables and the errors of estimated lengths were presented. The maximal errors, related to real lengths, were up to 22%

Practical Methods for Vehicle Speed Estimation Using a Microprocessor-Embedded System with AMR Sensors

The proper operation of computing resources in a microprocessor-embedded system plays a key role in reducing computing time. Processing the variable amount of collected data in real-time improves the performance of a microprocessor-embedded system. In this regard, a vehicle’s speed measurement system is no exception. The computing time for evaluating any speed value is expected to be reduced as much as possible. Four computational methods, including cross-correlation, are discussed. An exemplary pair of recorded signals presenting the change in magnetic field magnitude is analyzed. The sample delay values are compared. The results of the evaluated speed and the execution time of the program code are presented for each method based on a dataset of 200 randomly driven vehicles. The results of the performed tests confirm that the cross-correlation-based methods are not always reliable in situations when the sample size is small, i.e., it is a segment of the impulse response caused by a driving vehicle

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