Driver monitoring based on low-cost 3-D sensors

A solution for driver monitoring and event detection based on 3-D information from a range camera is presented. The system combines 2-D and 3-D techniques to provide head pose estimation and regions-of-interest identification. Based on the captured cloud of 3-D points from the sensor and analyzing the 2-D projection, the points corresponding to the head are determined and extracted for further analysis. Later, head pose estimation with three degrees of freedom (Euler angles) is estimated based on the iterative closest points algorithm. Finally, relevant regions of the face are identified and used for further analysis, e.g., event detection and behavior analysis. The resulting application is a 3-D driver monitoring system based on low-cost sensors. It represents an interesting tool for human factor research studies, allowing automatic study of specific factors and the detection of special event related to the driver, e.g., driver drowsiness, inattention, or head pose.This work was supported by the Spanish Government through the CICYT projects under Grants TRA2010- 20225-C03-01 and TRA 2011-29454-C03-02. The Associate Editor for this paper was C. Olaverri-Monreal

Data fusion for driver behaviour analysis

A driver behaviour analysis tool is presented. The proposal offers a novel contribution based on low-cost hardware and advanced software capabilities based on data fusion. The device takes advantage of the information provided by the in-vehicle sensors using Controller Area Network Bus (CAN-BUS), an Inertial Measurement Unit (IMU) and a GPS. By fusing this information, the system can infer the behaviour of the driver, providing aggressive behaviour detection. By means of accurate GPS-based localization, the system is able to add context information, such as digital map information, speed limits, etc. Several parameters and signals are taken into account, both in the temporal and frequency domains, to provide real time behaviour detection. The system was tested in urban, interurban and highways scenarios.This work was supported by the Spanish Government through the CICYT project (TRA2013-48314-C3-1-R) and DGT project (SPID2015-01802) and by the company SERCORE Tech. S.L. through the project: “Proyecto de Viabilidad de la Comunicación entre el BUS CAN de un Vehículo Específico con un Dispositivo de Adquisición de Datos Móviles”. SERCORE provided invaluable support in the development of the communication technologies through the CAN BUS, presented in this paper

LOW-COST 3D TECHNIQUES FOR REAL SCULPTURAL TWINS IN THE MUSEUM DOMAIN

The contribution presented is part of a broader study of Cultural Heritage valorisation, defining a workflow for creating full-scale copies of statues using non-contact acquisition tools and 3D printing to enable tactile enjoyment. The research presents an experiment using low-cost active and passive tools to acquire a statuary element in the Ostia Antica Park in Rome. The paper describes a testing process of such instruments, evaluating their performance from a metrological point of view. Furthermore, the experimentation verifies the morphological reliability of different copies of the original, obtained sequentially with different production processes and materials, to validate the production process of statuary copy. The scale of the case study is small and suitable for applying different survey approaches and comparing them towards the definition of a possible working protocol for massive low-cost artefacts 3D acquisition

YAPAY ZEKA İLE GERÇEK ZAMANLI SÜRÜCÜ YORGUNLUK TESPİTİ

Tezsiz Yüksek Lisans Bitirme ProjesiElde edilen istatistikler, trafik kazalarının birçok nedeni olduğunu ortaya koymaktadır. Yanlış davranışlar, dikkatsizlik, ihmal ve benzeri faktörlerin bir araya gelmesi, kazaların oluşmasında etkili olmaktadır. Bu tür kazaların sonuçları can ve mal kaybı gibi ciddi sonuçlar doğurabilmektedir. Günümüzde, trafik kazalarının önde gelen nedenlerinden biri, sürücünün yorgun ve uykusuz olmasıdır. Bu nedenle, sürücülerin anlık durumlarının izlenmesi ve yorgunluk tespitinin yapılması, kazaların sayısında önemli bir azalmaya neden olacaktır. Bu amaçla, gerçek zamanlı ve yüksek doğruluklu bir sistem gerekmektedir. Aracın güvenlik sisteminde, sürücünün yüzünü tanırız ve sürücü gözlerini kırptığında ve uykulu olduğunda uyarılar veririz ve güvenliğini korumak için bir alarm çalarız. Uykusuzluk, günümüzdeki trafik kazalarının ana nedenlerinden biridir. Burada, bu tür kazaları önlemek için uykusuzluk uyarı sistemi ve araç güvenlik sistemi geliştiriyoruz. Yapay Zeka (AI) teknolojisini kullanarak bu sistem inşa ediliyor. İlk olarak, sürücünün resmi çekilir ve yüz tanıma teknikleri kullanılarak tanımlanır. Sürücü araçta olduğunda ve aracı sürmeye başladığında, örneğin uykulu hissederse, bir uyarı/alarm oluşur böylece kendini uyanık tutabilir, mola alabilir ve daha sonra aracı sürebilir

Integration of body sensor networks and vehicular ad-hoc networks for traffic safety

The emergence of Body Sensor Networks (BSNs) constitutes a new and fast growing trend for the development of daily routine applications. However, in the case of heterogeneous BSNs integration with Vehicular ad hoc Networks (VANETs) a large number of difficulties remain, that must be solved, especially when talking about the detection of human state factors that impair the driving of motor vehicles. The main contributions of this investigation are principally three: (1) an exhaustive review of the current mechanisms to detect four basic physiological behavior states (drowsy, drunk, driving under emotional state disorders and distracted driving) that may cause traffic accidents is presented; (2) A middleware architecture is proposed. This architecture can communicate with the car dashboard, emergency services, vehicles belonging to the VANET and road or street facilities. This architecture seeks on the one hand to improve the car driving experience of the driver and on the other hand to extend security mechanisms for the surrounding individuals; and (3) as a proof of concept, an Android real-time attention low level detection application that runs in a next-generation smartphone is developed. The application features mechanisms that allow one to measure the degree of attention of a driver on the base of her/his EEG signals, establish wireless communication links via various standard wireless means, GPRS, Bluetooth and WiFi and issue alarms of critical low driver attention levels.Peer ReviewedPostprint (author's final draft