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Poster Abstract : A Wireless Magnetoresistive Sensor Network for Real-Time Vehicle Detection
| Content Provider | Semantic Scholar |
|---|---|
| Author | Bemporad, Alessandro Gentile, Francesco Mecocci, Alessandro Molendi, Francesco Rossi, Flavio |
| Copyright Year | 2007 |
| Abstract | This works describes a prototype wireless sensor network for vehicle detection developed at the University of Siena in collaboration with the Italian highways society Autostrade S.p.A. Each wireless sensor node is composed by an in-house designed electronic board driving a 2-axis Honeywell HMC1002 magneto-resistive sensor interfaced to a Telos rev.b (Moteiv Corporation) mote, and by a Matlab/Simulink interface for collecting and processing sensor data in (soft) real-time. I. MAGNETO-RESISTIVE WIRELESS SENSOR Wireless magneto-resistive sensor networks are a cheap, easily deployable, and non-invasive alternative to inductive loops and cameras for real-time count, speed measurement, and occupancy of vehicles on roads, and, indirectly, of traffic parameters like density and flows [1], [2]. In our setup each wireless node provides samples of two components of the Earth magnetic field, perturbed by the vehicle, in a rather reliable way, thanks to a set-reset control circuit on the magneto-resistive sensor’s board. The board is physically connected on the ADC expansion pins of the Telos mote (see Figure 2). Though specially tailored NesC components for TinyOS, the mote samples the amplified analog signal from the sensor’s Wheatstone bridge at 64Hz and transmits the digital samples to the remote station located along the road at a distance of about 10m. The sampling frequency is high enough to recognize vehicle magnetic “signatures” on a wide spectrum of vehicle speeds (see Section 3). Two sensor nodes are employed for robustified vehicle detection and speed measurements. ∗Corresponding author, bemporad@dii.unisi.it. Fig. 2. Magneto-resistive wireless sensor node II. MAGNETIC SIGNATURE Every vehicle leaves its own characteristic magnetic signature when passing in the proximity of the sensor. For example two different vehicles provide a different perturbation of the Earth’s magnetic field because their ferrous parts (engine, chassis and body) have different dimensions and are placed in a different way. The passage of the same vehicle can be therefore identified by its signature. The shape of the magnetic signature is almost insensitive to vehicle speed, modulo deformations along the time axis due to non-uniform speed (that is, the magnetic signature signal m(t) = m(s(t)), where s(t) is the vehicle position at time t). Figure 3 shows the same signature identified at 30 and 80 km/h. In terms of number of samples of the signature, at the given sampling frequency 64 Hz around 50 samples are collected at 40 km/h, 32 samples at 70 km/h. Different vehicle signatures were observed by changing the orientation of the sensor, a very promising result pointing towards the possibility of reliable vehicle classification. III. DETECTION ALGORITHM Several detection algorithms running at the base station for noise filtering (like integrals, autoconvolutions, FFT, etc.) were tested. A very efficient solution in terms of both numerical burden, accuracy of detection, and robustness, is an algorithm that integrates the raw magnetic signal x(t) (y(t) or z(t)) on a moving window of M (typically M = 32) samples depurated by the average of the samples, and then compares the resulting signal with a given threshold ±L, therefore obtaining a {−1, 0, 1} signal ax(t) (ay(t) or az(t)). The logical “and” |ax(t)| ∧ |ay(t)| (or |ax(t)| ∧ |az(t)|) provides a binary signal b(t) that flags the passage of a vehicle. Fig. 3. Magnetic signature of the same vehicle detected on x axis (along the motion direction) at the speed of 30 and 80 km/h. Such a simple detection algorithm is described in more detail below: 1. Initialization: mx(0) = M−1 ∑ i=0 x(−i), my(0) = M−1 ∑ |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://cse.lab.imtlucca.it/~bemporad/publications/papers/ewsn07-vehicle.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Poster |
