Wireless magnetic sensor network for road traffic monitoring and vehicle classification

Efficiency of transportation of people and goods is playing a vital role in economic growth. A key component for enabling effective planning of transportation networks is the deployment and operation of autonomous monitoring and traffic analysis tools. For that reason, such systems have been developed to register and classify road traffic usage. In this paper, we propose a novel system for road traffic monitoring and classification based on highly energy efficient wireless magnetic sensor networks. We develop novel algorithms for vehicle speed and length estimation and vehicle classification that use multiple magnetic sensors. We also demonstrate that, using such a low-cost system with simplified installation and maintenance compared to current solutions, it is possible to achieve highly accurate estimation and a high rate of positive vehicle classification

A Survey and Comparison of Low-Cost Sensing Technologies for Road Traffic Monitoring

Abstract This paper reviews low-cost vehicle and pedestrian detection methods and compares their accuracy. The main goal of this survey is to summarize the progress achieved to date and to help identify the sensing technologies that provide high detection accuracy and meet requirements related to cost and ease of installation. Special attention is paid to wireless battery-powered detectors of small dimensions that can be quickly and effortlessly installed alongside traffic lanes (on the side of a road or on a curb) without any additional supporting structures. The comparison of detection methods presented in this paper is based on results of experiments that were conducted with a variety of sensors in a wide range of configurations. During experiments various sensor sets were analyzed. It was shown that the detection accuracy can be significantly improved by fusing data from appropriately selected set of sensors. The experimental results reveal that accurate vehicle detection can be achieved by using sets of passive sensors. Application of active sensors was necessary to obtain satisfactory results in case of pedestrian detection

Real-Time Vehicle Classification System Using a Single Magnetometer

Vehicle count and classification data are very important inputs for intelligent transportation systems (ITS). Magnetic sensor-based technology provides a very promising solution for the measurement of different traffic parameters. In this work, a novel, real-time vehicle detection and classification system is presented using a single magnetometer. The detection, feature extraction, and classification are performed online, so there is no need for external equipment to conduct the necessary computation. Data acquisition was performed in a real environment using a unit installed into the surface of the pavement. A very large number of samples were collected containing measurements of various vehicle classes, which were applied for the training and the validation of the proposed algorithm. To explore the capabilities of magnetometers, nine defined vehicle classes were applied, which is much higher than in relevant methods. The classification is performed using three-layer feedforward artificial neural networks (ANN). Only time-domain analysis was performed on the waveforms using multiple novel feature extraction approaches. The applied time-domain features require low computation and memory resources, which enables easier implementation and real-time operation. Various combinations of used sensor axes were also examined to reduce the size of the classifier and to increase efficiency. The effect of the detection length, which is a widely used feature, but also speed-dependent, on the proposed system was also investigated to explore the suitability of the applied feature set. The results show that the highest achieved classification efficiencies on unknown samples are 74.67% with, and 73.73% without applying the detection length in the feature set

A Novel Variable Geometry based Planar Inductor Design for Wireless Charging Application

In this thesis, the performance, modelling and application of a planar electromagnetic coil are discussed. Due to the small size profiles and their non‐contact nature, planar coils are widely used due to their simple and basic design. The uncertain parameters have been identified and simulated using ANSYS that has been run utilising a newly developed MATLAB code. This code has made it possible to run thousands of trials without the need to manually input the various parameters for each run. This has facilitated the process of obtaining all the probable solutions within the defined range of properties. The optimum and robust design properties were then determined. The thesis discusses the experimentation and the finite element modelling (FEM) performed for developing the design of planar coils and used in wireless chargers. In addition, the thesis investigates the performance of various topologies of planar coils when they are used in wireless chargers. The ANSYS Maxwell FEM package has been used to analyse the models while varying the topologies of the coils. For this purpose, different models in FEM were constructed and then tested with topologies such as circular, square and hexagon coil configurations. The described methodology is considered as an effective way for obtaining maximum Power transfer efficiency (PTE) with a certain distance on planar coils with better performance. The explored designs studies are, namely: (1) Optimization of Planar Coil Using Multi-core, (2) planar coil with an Orthogonal Flux Guide, (3) Using the Variable Geometry in a Planar coil for an Optimised Performance by using the robust design method, (4) Design and Integration of Planar coil on wireless charger. In the first design study, the aim is to present the behaviour of a newly developed planar coil, built from a Mu-metal, via simulation. The structure consists of an excitation coil, sensing coils and three ferromagnetic cores 2 located on the top, middle and bottom sections of the coil in order to concentrate the field using the iterative optimisation technique. Magnetic materials have characteristics which allows them to influence the magnetic field in its environment. The second design study presents the optimal geometry and material selection for the planar with an Orthogonal Flux Guide. The study demonstrates the optimising of the materials and geometry of the coil that provides savings in terms of material usage as well as the employed electric current to produce an equivalent magnetic field. The third design study presents the variable geometry in a planar inductor to obtain the optimised performance. The study has provided the optimum and robust design parameters in terms of different topologies such as circular, square and hexagon coil configurations and then tested, Once the best topology is chosen based on performance. The originality of the work is evident through the randomisation of the parameters using the developed MATLAB code and the optimisation of the joint performance under defined conditions. Finally, the fourth design study presents the development of the planar coil applications. Three shapes of coils are designed and experimented to calculate the inductance and the maximum power transfer efficiency (PTW) over various spacing distances and frequency

Deployment of Inductive Loop Vehicle Traffic Counters Along Trunk Roads in Tanzania

As Tanzania's population grows, there is a greater demand for efficient, effective, and strong road design, as well as a smooth transportation system with a balanced traffic management network architecture. To plan for maintenance and expansion of such a vast network, a credible data inventory and network condition must be established. The deployment of vehicle inductor loop counters along Tanzanian trunk roads is presented in this paper. At test sites, inductor loop sensors and control cards were used to capture vehicle traffic data, which was then wirelessly sent using GSM technology for vehicle classification verification and storage for future road traffic management. The traffic count statistics from selected test sites acquired by the base station monitoring software were examined in real-time and the findings over a one-year period were provided. According to the study's findings, inductive loop vehicle counter technology can count and categorize vehicles along a section of roadway and provide reliable performance indicators for monitoring progress at the local, state, and national levels. The vehicle traffic data collected by this system will be used to project future situations within a transportation system and to keep a record of historical trends that will be used to project into the future what is likely to happen based on actual observations of the past and using other socio-economic data obtained from census information or economic indicators

Archaeological site monitoring: UAV photogrammetry can be an answer

During archaeological excavations it is important to monitor the new excavated areas and findings day by day in order to be able to plan future excavation activities. At present, this daily activity is usually performed by using total stations, which survey the changes of the archaeological site: the surveyors are asked to produce day by day draft plans and sections which allow archaeologists to plan their future activities. The survey is realized during the excavations or just at the end of every working day and drawings have to be produced as soon as possible in order to allow the comprehension of the work done and to plan the activities for the following day. By using this technique, all the measurements, even those not necessary for the day after, have to be acquired in order to avoid a ‘loss of memory'. A possible alternative to this traditional approach is aerial photogrammetry, if the images can be acquired quickly and at a taken distance able to guarantee the necessary accuracy of a few centimeters. Today the use of UAVs (Unmanned Aerial Vehicles) can be considered a proven technology able to acquire images at distances ranging from 4 m up to 20 m: and therefore as a possible monitoring system to provide the necessary information to the archaeologists day by day. The control network, usually present at each archaeological site, can give the stable control points useful for orienting a photogrammetric block acquired by using an UAV equipped with a calibrated digital camera and a navigation control system able to drive the aircraft following a pre-planned flight scheme. Modern digital photogrammetric software can solve for the block orientation and generate a DSM automatically, allowing rapid orthophoto generation and the possibility of producing sections and plans. The present paper describes a low cost UAV system realized by the research group of the Politecnico di Torino and tested on a Roman villa archaeological site located in Aquileia (Italy), a well-known UNESCO WHL site. The results of automatic orientation and orthophoto production are described in terms of their accuracy and the completeness of information guaranteed for archaeological site excavation managemen

Sensors Utilisation and Data Collection of Underground Mining

This study reviews IMU significance and performance for underground mine drone localisation. This research has designed a Kalman filter which extracts reliable information from raw data. Kalman filter for INS combines different measurements considering estimated errors to produce a trajectory including time, position and attitude. To evaluate the feasibility of the proposed method, a prototype has been designed and evaluated. Experimental results indicate that the designed Kalman filter estimates the internal states of a system

Smart Sensor Technologies for IoT

The recent development in wireless networks and devices has led to novel services that will utilize wireless communication on a new level. Much effort and resources have been dedicated to establishing new communication networks that will support machine-to-machine communication and the Internet of Things (IoT). In these systems, various smart and sensory devices are deployed and connected, enabling large amounts of data to be streamed. Smart services represent new trends in mobile services, i.e., a completely new spectrum of context-aware, personalized, and intelligent services and applications. A variety of existing services utilize information about the position of the user or mobile device. The position of mobile devices is often achieved using the Global Navigation Satellite System (GNSS) chips that are integrated into all modern mobile devices (smartphones). However, GNSS is not always a reliable source of position estimates due to multipath propagation and signal blockage. Moreover, integrating GNSS chips into all devices might have a negative impact on the battery life of future IoT applications. Therefore, alternative solutions to position estimation should be investigated and implemented in IoT applications. This Special Issue, “Smart Sensor Technologies for IoT” aims to report on some of the recent research efforts on this increasingly important topic. The twelve accepted papers in this issue cover various aspects of Smart Sensor Technologies for IoT