Jatuporn Chinrungrueng

Smart Parking: An Application of Optical Wireless Sensor Network

Parking problems are commonplace in most major cities. The limited availability of parking results in traffic congestion, air pollution as well as driver frustration. The price for parking expansion is usually prohibitive or extremely high. Recently researchers turned to applying technologies for efficient parking management. In our previous work, we have developed an optical wireless sensor network (WSN) for traffic monitoring. We have demonstrated our system to the public in several exhibitions. It is realized that this simple invention could be applied to monitor vehicles in a parking garage. The system can then inform drivers of the number of available parking spaces and in which area should they be directed to. This kind of system should avoid drivers frustration in trying endlessly to find a parking space in a crowded parking garage. This paper describes our work to modify our original WSN and applies it to parking garages. Problems associated to applying our original WSN to parking garage are explained, and solutions are proposed

Vehicle classification based on magnetic sensor signal

We extend our work in vehicle classification proposed in [6] and [7]. Our system is based on a low complexity wireless sensor network. The system consists of a low power microprocessor together with AMR magnetic sensors and an RF transceiver. Two AMR magnetic sensors are employed to extracts dominant low-complexity features including vehicle count, speed, length, Hill-pattern peaks, and normalized energy. These features are studied in [6] and [7] and yield a promising result when vehicle classification is based on sizes (96%). However, when classification of similar sizes, e.g. cars, vans, pickup trucks are studied. The results are relatively lower at 77%. The contribution of this paper include (1) the implementation of feature extraction (count, speed, length) on sensor board and (2) the study for additional different low-complexity features such that better classification rate of small vehicles is obtained. These features include Hill-pattern peaks and magnetic signal differential energy normalized to the vehicle speed and length. This paper proposed vehicle classification tree based on above extraction features. Our work focuses on low computational feature extraction and classification processes suitable for implementing on micro-controller. The same data set employed in [7] is analyzed. The classification yields promising improved results over [6] and [7]. The classification rate yield 100 percent for motorcycle, 82.46 percent for car, 78.57 percent for van and 65.71 percent for pickup. The overall accuracy is 81.69 percent.

Automatic vehicle classification using wireless magnetic sensor

This paper proposes an extension to our previous work on an automatic low-computed vehicle classification using embedded wireless magnetic sensor. A realization of our vehicle classification on embedded wireless magnetic sensor is studied in this work. The implementation allows real-time vehicle classification based on vehicle magnetic length, averaged energy, and Hill-pattern peaks. The system automatically detects vehicles, extracts features, and classifies them. The three features are of low-computation. We classify vehicles into 4 types: motorcycle, car, pickup and van. The classification shows a promising result. It can classify motorcycle with 95% accuracy. The classification rates between 70%-80% are achieved with car, pickup and van due to their similarity in these extracted features. The results obtained are comparable to our implementation using PC in our previous work and demonstrate that the algorithm can be realized on the embedded wireless magnetic sensor.

iParking: A parking management framework

In this work we have proposed a parking management framework that monitors vehicles driving in and out, calculates the number of available parking spaces, and finally disseminates the information to the parkings customers. For monitoring vehicles, we show our implementation of magnetic sensor network. The magnetic sensor is capable of collecting number of vehicle passing over the sensor, estimating vehicles speed and length. The data is communicated over wired or wireless links to the server and is stored in the database for analysis and the number of available parking spaces can be displayed for customers before entering the parking garage. The dissemination of the information collected is through social network such as Twitter and Facebook. The test results show that the system yields a very accurate vehicle counting. The data obtained are consistent with the characteristics of drivers who access the parking facility. Analysis of data collected with our system is shown to provide useful information on which our future prediction of parking spaces will be based.

Short-distance and near-ground signal measurements in a car park of wireless sensor network system at 433 MHz

The short-range and near ground measurements of signal attenuation in the UHF band are performed to study radio wave propagation in a car park for a wireless sensor network application. The measurement setup is based on the radio wave propagation along the row of a parking lot (full of cars) by varying heights of server antenna. In the application, a small antenna and a compact antenna are employed at the server antenna and the sensor antenna respectively, by radiating horizontal polarization. The test points are located under cars and above ground. The transmitter is radiated at 433 MHz with 120 cm, 180 cm and 240 cm of antenna height. The propagation models, such as the two-ray model and the free-space model, are compared with measurement results. These results can be used to approximate the signal level in practical planning of wireless sensor network systems in car parks.

Wireless magnetic sensor network for collecting vehicle data

We develop a new traffic data collecting device. The device is based on magneto-resistive technology, in which the circuit resistance is changed with the imposing magnetic field. It is known that ferrous-body vehicles interfere with Earths magnetic field, which can be monitored with our device. The signal will then be processed and yields vehicle count, speed, occupancy time, and classification. We also design our device to communicate to its base station via radio frequency. We form a network of these many sensor nodes at places where traffic monitoring are required. Our system is very flexible and adapt to many environments of vehicle detection.

Two-rectangular-printed-spiral antenna with U-strip

The two-rectangular-printed-spiral antenna with U-strip is proposed. The increasing electrical length and impedance matching is performed by using two spiral arms and adding U-strip. There is no ground plane for this antenna structure. The size is relatively small. The measured return loss is -12.435 dB at 433 MHz with 5.455 % bandwidth (428-452 MHz). The measured absolute gain is about -5 dBi. The performance of this small antenna is efficient for many wireless applications especially wireless sensor networks of ITS.

Wireless Sensor Network: Application to Vehicular Traffic

In this paper we are reporting our current development of wireless sensor network to effectively monitor vehicular traffic. A simple star configuration that consists of a server node communicating with a number of sensor nodes is proposed because of its low complexity, and easy and quick deployment, maintenance and relocation. Our system consists of the sensor, processor, and RF transceiver. We choose the magneto-resistive sensor to detect vehicles as it yields high accuracy with small size. The sensor yields important vehicle informations such as vehicle count, speed, and classification. The network topology is a simple star network. Two Medium Access Communication Protocols (MAC) are analyzed and can be automatically switched based on two different traffic scenarios. An antenna design is shown to fit with a small sensor node. Experiments show that the proposed system yields good data processing results. The classification of vehicles is very promising for major types of vehicles: motorcycle, small vehicle, and bus. RF communications is employed that cable installation can be avoided. Protocol frame formats are provided for both RF communications and RS232. This protocol is very simple and can be easily extended when new sensors or new data types are available.

A compact antenna for server node of wireless sensor network

This paper proposes the compact antenna for server node of wireless sensor network system. The antenna parameters are varied to achieve the nearest horizontally polarized omnidirectional pattern. The overall antenna width, length and height are fixed for suitable installation. The antenna structure is simple and its design is straightforward. The return loss, radiation pattern, absolute gain and cross-polarization are simulated and measured. The measured return loss is equal to -21 dB at the operating frequency with the measured bandwidth of 1.85%. The maximum azimuth ripple is lower than 10 dB. This antenna can be useful for a server node of WSN with applications to ITS that desires small-size antenna.