Ilona Madalina Costea

Monitoring system with applications in road transport

The paper describes a modern traffic monitoring system designed to optimize road traffic flow, while ensuring mobility and access with the aim of meeting the current and future necessities for road travel. Furthermore, the proposed system complies with the requirements for rational use of urban land and the regulation on environmental protection. The importance of finding such solution derives from the current problems faced by the urban road traffic, such as congestions, pollution, security issues. It is with the purpose of solving traffic flow and security problems that the authors are proposing in this paper the implementation of an innovative system utilizing new technologies for real-time collecting, organizing and transmitting of information about traffic and weather conditions. To this end, data collection and processing were performed using LabVIEW programming.

LabVIEW brain computer interface for EEG analysis during sleep stages

In this paper is proposed a brain-computer interface. In order to develop and implement this interface, the programming environment LabVIEW was used. In order to recognize a K complex in the EEG signal, a simple detector was created, using Peak Detector VI in LabVIEW. The detector receives the representation of the power spectrum of the signal and determines the locations and the amplitudes of signals above a certain limit (the limit can be set by moving the horizontal bar in the power spectrum). Then the code determines if the peak correspond to those which designate a K complex. Following these experimental achievements where an EEG signal was used, it was determined that one could reliably observe a K complex in the data from the sleep spindles, focusing on only 2 peaks in the power spectrum. The first peak should appear between 0,5 and 1.50 Hz, having an amplitude exceeding 65 units, while the second peak should appear between 5 and 10 Hz, having an amplitude of at least 30 units.

Communications architecture with applications on the road transportation system

The present paper describes the achievement of communications architecture with applications on the road transportation system. Such a communication system implemented on vehicles can be used not only on highway or a modernized expressway, but on any type of road and most important, in any geographical area (regardless of its economic development). Thus, direct vehicular communication offers opportunities in the forthcoming development of a system for vehicular communication, an achievement obtained with minimal costs. The implementation of the vehicular communication system requires the development of a protocol for communication between vehicles. Moreover, this paper describes an application which collects data from the transportation system and only if an accident occurs the received data will be transmitted to the smartphone.

Model of intelligent traffic sensors — Application in hardware in the loop

The paper has as main subject the elaboration of a model for traffic sensors. This model is implemented in LabVIEWenvironment and it should be used in hardware in the loop (HIL) platform, especially for urban traffic management system. The authors presented the concept of intelligent sensor for traffic and transport applications and the methodology of defining the model and the software environment of this model. The architecture of the model as well as the main interfaces with virtual and real components of sensors for traffic management systems are also described in the paper. The paper is concluded with the recommendation of using the model in HIL platform as well as the development of an autonomic behaviour of the intelligent sensors.

The framework of using models for comparative assessment of traffic sensors

The intelligent transport systems (ITS) are now one of the most dynamic sector in terms of finding solutions for transport domain. These systems are applications of electronics, IT, computer science and other connected disciplines which are installed in terms of increasing the efficiency of the transport activities and decreasing the negative impact of them. ITS are mainly based on a sensor network which is able to collect data from transport processes. The paper is focused on elaboration of a common model for traffic sensor which is able to support comparative assessment of various traffic sensors (the example in the paper is based on inductive loops and virtual loops based on CCTV cameras). The framework and the models are created in LabVIEW and an example of using the model in comparative assessment is provided. The authors presented the methodology for the elaboration of the model as well as the recommendations for comparative assessment based on the proposed framework.

Developing a multi sensors system to detect sleepiness to drivers from transport systems

The increasing number of accidents in transportation (rail, road) recorded in the past few years have become a serious concern for the society. The accidents caused by driving under fatigue, drowsiness and disruptive (stress) factors have a high mortality rate due to decreasing of the abilities of perception, recognition and control which are necessary for the conductors in the field of road and railway. The paper proposes a multi-sensor system for predicting fatigue and drowsiness based on the analysis of the power spectrum density (PSD) of the electroencephalogram (EEG) and correlation with the cardiac cycle (ECG) or with the respiratory cycle. EEG data collecting uses a sensorial system, headset type (physical contact) or capacitive (no physical contact), and for ECG data collecting a new system of sensor is proposed, that does not involve physical contact against the capacitive system currently used. Our results demonstrated that it is possible to estimate with quantitative accuracy the driving performance in a 3D driving simulator, using the multi-sensor system proposed.

Developing an automated system for simultaneous recording of the human physiological parameters

The following paper presents the development of an automated system for simultaneous recording of the human parameters, alongside highlighting the audio-visual stimuli - which are required in the analysis of the emotional perception to which the subject is tested. The automated system consists of two subsystems: the subsystem of acquisition/recording physiological parameters - audio-visual parameters and frame-by-frame storage of the images - and the offline subsystem of reunited analysis of the EKG/EEG signals with the emotional perception detected from the video images. Also, the paper presents the analysis blocks along with the system diagram, including the window method to calculate stress index and the scaling exponent.

Monitoring system with application in air transport

The present paper describes a modern and complete solution to be employed by the airport control tower for the surveillance and monitoring of the surrounding perimeter fence. The proposed solution is based on CCTV (Closed Circuit Television) IP (Internet Protocol) cameras, communication network and server and client video applications running in a virtual environment. The proposed monitoring and surveillance solution aims at improving the existing solutions for security and safety in airports. While using the virtual environment for hosting the server and client applications, the designed solution allows the user to not be hardware dependent by using “of the shelves” inexpensive hardware platforms for virtualization.

Trajectory estimation for transportation systems: Aircraft tracking applications

In this paper the dynamic of an aircraft was modeled based on a discrete-time stochastic linear hybrid system - its modes corresponding to various flight modes of the aircraft. A predictive control model was designed based on the industrial control predictive model (MPC - Model Predictive Control). The interface of the simulator dedicated to estimate the trajectory was created in LabVIEW. As a result, the present work proposes a predictive controller with an internal model to be used with the purpose of predicting the behavior correlated with the assumed entry. Furthermore, an application for the control of unstable helicopters was created in Matlab.

Biomedical signals analysis techniques using the signal processor TMS320C6211B

The present paper presents the technological solution dedicated to the implementation of the K-complex detection algorithm, from the EEG medical signals, with the help of the TMS320C6211B signal processor, produced by Texas Instruments. This application is based on the host-target system architecture, where the target is the DSK (Digital Starter Kit), which performs realtime processing and is transmitted from the software host on the processing computer. The host software is written in G, Labview programming language, and has the objective of achieving an automated detector for the K complex, derived from the sleep electroencephalogram. The K complex detection automatization must establish a verification criterion and a prediction criterion.