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The black box has the function that stores driving video, location, time and rear-end collision before/after the accident with mounted on the vehicle. And, in case of car accident, it has GPS function to find the location of accidents. In this paper, the system was designed that traces the moving path of the vehicle and transmits current location of vehicle and the videos of accident happened during movement to the remote control system. As the results of study, it was recognized that the mining system for automotive black box is useful for presenting the driver and administrator with the required traffic status, optimum path and accident situation by accumulating the movement information of vehicle transmitted from the vehicle.

Healthcare, due to the aging of western populations, requires new technologies to help assisting the needs of elders. The smart home paradigm is one of the promising new trends of research aiming to bring socially and economically viable solutions to this challenge. One of the most crucial problems in developing smart environment is activity recognition. It can be defined as the process of inferring, with various sensors, what the patient is doing and then, being able to predict what he might do in the future. We can find in the literature a lot of works on this theme, however the majority remain essentially theoretical. More specifically, they often work only on a particular component of the activity recognition process, for example by focusing only on the hardware (sensors) or solely on the high level recognition part, assuming that low level recognition already works. Furthermore, we noticed that most available recognition test platforms with an infrastructure, such as MavHome, are static and involve a complex set of sensors, which inevitably has a heavy cost. The work presented in this paper aims of providing solutions to these problems by proposing a way to implement from A to Z a complete recognition platform that works, is simple to use, inexpensive, sturdy and portable. This platform is based only on RFID tags and can be reuse everywhere to test various recognition algorithms, even directly at the patients’ home. We also present a first experimentation conducted with this platform using data mining recognition algorithms.

This study proposes effective interface by using face-detection information, which comes from input image of the camera installed on a smart phone, and also by using movement information from reliable characteristics of the object. To do this, augmented reality interface has been constructed by putting the virtual object onto the camera image of the real space. The gamer and the virtual object, which are put in two separate spaces, engage in various real-time interactions such as attack, defense and alert. Difference image per frame of the tracked object information was employed to check if the hand has touched the interested area. Its effectiveness has been proven through experiment. Infusion technology, which combines TTS (text to speech) and vibrating sensor installed on a smart phone, was applied to provide emotional information to help the game participant to get immersed in the game. The proposed method could be applied as the basic material for AR interface.

As 3D movies are becoming increasingly popular due to the advancement of the imaging technology these days, development of contents that use 3D images is taking place actively in diverse fields besides the 3D film industry. As a result, 3D contents industry including the 3D TV, S/W, 3D game and others are growing in general. Accordingly, users too are demanding the 3D contents that enable them to experience optimal 3D feeling instead of simple 3D images. Currently, the degree of the 3D feel in case of the contents that we watch these days is affected significantly by the 3D Depth value. In fact, there are researches under way to improve the sense of 3D feel by using 3D Depth value [5, 6]. However, it is necessary to factor in the user’s distance and location as well along with the 3D Depth value of the image in order to feel 3D effectively when watching 3D image. Accordingly, this research paper presents the index for 3D Depth level analysis that enable users to feel the 3D most effectively and to be immersed deeply into the image according to user’s location and distance through the Depth level change of the 3D images.

Energy conservation can be the most important concern in the deployment of wireless sensor networks. Among all methods, finding an efficient sleep/transmission schedule must be most effective to achieve energy conservation. There are many researches and solutions for sleep schedule, transmission schedule, or topology/routing creation in the past. Nevertheless, almost none of them can solve all of these problems in the same time. Our prior DMAS protocol could be the first cross-layer protocol that can solve all these problems si-multaneously in a distributed way with very low duty cycle. This paper presents the DMAS protocol and an enhanced version of it named EDMAS. The enhancements of EDMAS over DMAS include significant reductions in transmission latency, packet collision probability, and duty cycle.

In recent years, several electronic voting (e-voting) schemes for communication networks have been proposed. In 2006, Chang and Lee presented an anonymous electronic voting scheme which can be applied in real-world elections. However, this paper shows that Chang-Lee’s e-voting scheme suffers from susceptibility to security attacks. As a result, some essential security requirements of their e- voting scheme may be compromised. An improved scheme is suggested to enhance the security of their scheme.

This paper proposed a face detector using network-based services for a remote robot application. To perform an efficient face detecting in a real robot, a face detector needs to light computation cost and low false detection. The proposed face detector has been implemented as a network-based service so that it can be deployed either in any computer nodes in network environments or in the robot itself. The human-following service has been also developed to perform a coordination service for a robot that can follow a user. The proposed method reduces the overall computation time and reduces the number of false positives. And the proposed method has been verified by successfully demonstrating a human-following of a robot in a real indoor environment.

In this paper, we propose a handheld Compute Engine (CE) for personal health devices (PHDs). The CE is a device that receives measurements from more than one PHD, and collects, analyzes and displays the received measurements. It also transfers the collected measurements to a remote monitoring server for more informative analysis. We implement the CE on a handheld device (i.e., smartphone) to provide seamless health monitoring services for patients or users. On the basis of the proposed CE, we construct a u-healthcare system comprising two PHDs: a medication dispenser and a pulse oximeter. The PHDs transfer their measurements to the CE, and the CE displays the received measurements. The application results show that the proposed CE operates properly.

In Wireless Sensor Networks (WSNs), the most important issue is to expand life time of network with the restricted energy resource of sensor nodes. Sensor nodes consume mostly energy when they transmit and receive sensing data. Thus it is important that how to set up a communication method of sensor networks. Generally, to achieve this is a clustering technique. A clustering technique is a communication method which can classify the area by nodes with same or similar sensing and prevent duplicated sensing data to reduce communication. And it can manage sensing data when working locally. To use a clustering technique, the environment to build clustering has to be considered, which means cluster heads counts can affect clustering formation. Thus, this paper proposes use of a clustering technique with zone-based multi-hop communication in WSNs.

Among a lot of rollback-recovery protocols developed for providing fault-tolerance for long-running distributed applications, sender-based message logging with checkpointing is one of the most lightweight fault-tolerance techniques to be capable of being applied in this field, significantly decreasing high failure-free overhead of synchronous logging by using message sender's volatile memory as storage for logging its corresponding message. However, attempting to apply this technique into large-scale and geographically distributed systems such as broker-based sensor networks, etc., the following problems should be addressed; reducing the number of control and data messages passing on core networks occurring during its fully message logging and recovery procedures. In this paper, we present a lightweight message logging protocol for distributed sensor networks to solve all of them by employing the current and future distributed systems' architectural features mentioned above.

Quality of service (QoS) provisioning is an important issue in wireless networks. The less interruption time or packet loss of a communication session is, the better quality of service is. In this paper, we propose a new link switching scheme for LED-ID networks based on the history of location of mobile devices (as known as readers). Our proposed scheme is based on the standpoint that in indoor environments people tendentiously move in restricted trajectories. The simulation results show that our proposed scheme outperforms the conventional scheme.

Recently, there have been widely conducted researches on dual-band radio frequency identification (RFID) tag based on 13.56 MHz (HF) and 900 MHz (UHF). Most dual-band RFID tag has been implemented so that each antenna is separated in a different inlay sheet respectively, which makes the resulting smart card impractically thick, and the typical drawback of dual-band RFID tags incorporated in one inlay is a mutual frequency interference phenomenon due to the fabrication of the HF antenna and the UHF antenna on the same sheet. In this paper, we introduce a novel design of high performance smart card with HF/UHF dual-band RFID tag to overcome the frequency interference problem. Firstly, we have design and tested a UHF RFID tag using a simulation software system. In the smart card hardware design stage, we connect a HF antenna and a UHF antenna and place them in one inlay sheet. Using a spectrum analyzer, we systematically adjust the antenna pattern to detect the optimal patterns that fit the impedance of the RFID chip.

Finding and obtaining information eciently from the Web is one of the important ele- ments in realizing Smart Home environment. Users expect to nd most relevant information within the shortest possible time. In this paper, we investigate the similarity of Web pages within Strongly Connected Components (SCCs). SCCs are overlapping groups of Web pages that may imply a relationship between the Web pages of the same component. Therefore, we seek to trace the similarity of these groups of Web pages using Cosine Similarity. Our experiment performed on Malaysian Web pages indicates that Web pages within same SCC carry a common topic or theme. This nding proves that we may locate Web pages with similar topic using the hyperlinks structure, without performing expensive analysis on the contents of the Web pages.

Cognitive Radio technique exploits underutilized licensed spectrums to improve its bandwidth availability. Using CR technology, node is able to adapt its transmission and reception radio parameters including channel frequency dynamically according to local spectrum availability. In visible light communication, due to the limitation and heterogeneous effect of color channel on different environment, the link quality will effect. In this article, new approach for multi-channel MAC for visible light communication, named Virtual cognitive MAC, is proposed to increase the performance of visible light communication system. It can be used in the promising communication technology, VLC, an encouraging green and energy-efficient communication technology. Numerical results show that, with the proposed system, we can reduce the blocking probability and improve the system performance.

Speech Emotion Recognition (SER) is a hot research topic in the field of Human Computer Interaction (HCI). In this paper, we recognize three emotional states: happy, sad and neutral. The explored features include: energy, pitch, linear predictive spectrum coding (LPCC), mel-frequency spectrum coefficients (MFCC), and mel-energy spectrum dynamic coefficients (MEDC). A German Corpus (Berlin Database of Emotional Speech) and our self-built Chinese emotional databases are used for training the Support Vector Machine (SVM) classifier. Finally results for different combination of the features and on different databases are compared and explained. The overall experimental results reveal that the feature combination of MFCC+MEDC+ Energy has the highest accuracy rate on both Chinese emotional database (91.3% ) and Berlin emotional database (95.1% ).

Measures for inferring context through multiple sensor data fusion are being actively used in various fields. The landslide protection wall refers to the structure/engineering method that prevents the collapse of soil during ground excavation. To prevent safety accidents of the landslide protection wall, it is necessary to devise measures for detecting the deformation of the landslide protection wall and for inferring the cause of the deformation. Context inference through multiple sensor data fusion can be used to analyze the influential factors of the problem among safety-threatening factors during generation of anomalous events in the landslide protection wall. This study presents the method for inferring decisive factors through multiple sensor data fusion based on the Dempster-Shafer evidence theory in an environment in which the deformation of the landslide protection wall is affected by earth pressure, water pressure and surcharge effect. Based on the Basic Probability Assignment (BPA) function of factors, this study calculated the belief and plausibility of factors through Dempster’s Rule of Combination. Uncertainty intervals can be calculated and compared with one another based on the belief and plausibility of factors to achieve inference of decisive factors