• ETRI Journal
• /
• v.30 no.5
• /
• pp.696-706
• /
• 2008

With the increasing need for intelligent environment monitoring applications and the decreasing cost of manufacturing sensor devices, it is likely that a wide variety of sensor networks will be deployed in the near future. In this environment, the way to access heterogeneous sensor networks and the way to integrate various sensor data are very important. This paper proposes the common system for middleware of sensor networks (COSMOS), which provides integrated data processing over multiple heterogeneous sensor networks based on sensor network abstraction called the sensor network common interface. Specifically, this paper introduces the sensor network common interface which defines a standardized communication protocol and message formats used between the COSMOS and sensor networks.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.9 no.6
• /
• pp.1619-1624
• /
• 2008

Recently, In order to provide ubiquitous service, we develop each middleware and interface for sensors networks, RFID(Radio Frequency IDentification) and GPS(Global Positioning System). We use GPS for the location-based services, RFID for identifying the distribution logistics services, sensor networks for collecting the context data such as temperature, humidity, barometric pressure. Recently, there is increasing the need of integrated interface for using these sensor elements complexly in agriculture and livestock, construction, medical applications and, etc. This paper developments a integrated common interface for supporting efficiently process of sensing data using RFID, GPS and sensor network. This interface have the filtering function, parsing function, queuing function, interface management function, access function and, etc. We present the integrated frame structure combined with the collected context data in GPS, RFID and sensor networks and, support the open interface for providing complex ubiquitous application systems. Therefore, this interface will be efficiently used the system using RFID, GPS and sensor network, and supported many ubiquitous application services.

• Journal of the Institute of Convergence Signal Processing
• /
• v.10 no.3
• /
• pp.176-180
• /
• 2009

This paper investigates protocol architecture for a web-sensor gateway interconnecting internet and wireless sensor network, in which Zigbee sensors are connected over the IEEE802.15.4 communication protocol standard. The web-sensor gateway is to deliver data between TCP/IP and Zigbee/IEEE802.15.4 protocols, transparently. Since the gateway provides a means to remotely control and aggregate sensor data over the internet, it needs to be designed in the view point of users and in their convenience. In accordance, the common gateway interface technology satisfying users on the web browser to efficiently manage and query the sensors in the wireless sensor networks, ubiquitously, is also introduced. Finally, a simulation prototype for the web-sensor gateway is proposed and verified using OPNET simulation tool.

• 한국방재학회:학술대회논문집
• /
• 2008.02a
• /
• pp.361-364
• /
• 2008

The Application Model in Wireless Sensor Networks(WSNs) consist of wireless sensor network based on sensor hardwares which is combined the micro-controller, chipset for wireless communication and sensors, middleware for dealing with data processing and user application for common service. Applications in WSN have been applied for environmental monitoring, smart factory and have concentrated the services based on remote monitoring applications which is difficult to watch the situation by human. In this paper, we described the construction model for applying for the Ubiquitous disaster prevention system and deal with its conformity. The proposed system includes the selecting the wireless sensor hardware, routing technique for u-Disaster Prevention, composition of middleware and web-interface for application services.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.7 no.5
• /
• pp.219-226
• /
• 2012

The rises of the life index quality together with the medical technology improvement lead to a longer life expectancy. Then a better health care program, especially for elderly, is needed. The common health problems facing those senior citizens are changed from acute diseases to chronic diseases, such as diabetes, hypertension. Then u-Health takes center stage in medical industry. Although u- Health medical device manufacturers have been improving their instruments, these instruments still rely on proprietary technologies without fixed platform. Even if the interface has been provided by the manufacturer, there is no widely-accepted uniform data model to access data of various u-Health devices. IEEE 11073 is a standard attempting to unify the interfaces of all medical devices. In this paper we have proposed a conversion software platform that assures interoperability among medical devices for ubiquitous sensor network. This module uses in order to develop a standard platform of medical system.

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.353-356
• /
• 2007

With advances in sensor technology, current researches on the pertinent techniques are actively directed toward the way which enables the USN computing service. For many applications using sensor networks, the incoming data are by nature characterized as high-speed, continuous, real-time and infinite. Due to such uniqueness of sensor data characteristics, for some instances a finite-sized buffer may not accommodate the entire incoming data, which leads to inevitable loss of data, and requirement for fast processing makes it impossible to conduct a thorough investigation of data. In addition to the potential problem of loss of data, incoming data in its raw form may exhibit high degree of complexity which evades simple query or alerting services for capturing and extracting useful information. Furthermore, as traditional mining techniques are developed to handle fixed, static historical data, they are not useful and directly applicable for analyzing the sensor data. In this paper, (1) describe how three mining techniques (sensor data outlier analysis, sensor pattern analysis, and sensor data prediction analysis) are appropriate for the USN middleware structure, with their application to the stream data in ocean environment. (2) Another proposal is a middleware structure based on USN environment adaptive to above mining techniques. This middleware structure includes sensor nodes, sensor network common interface, sensor data processor, sensor query processor, database, sensor data mining engine, user interface and so on.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.8 no.5
• /
• pp.65-71
• /
• 2008

Recently, the research is progressing on the SWE(Sensor Web Enablement) platform of OGC(Open Geospatial Consortium) to provide the sensing data and moving pictures collected in a sensor network through the Internet Web. However, existed research does not deal with moving objects like cars, trains, ships, and person. Therefore, we present a method to deal with integrated sensing data collected by GPS device, sensor network, and image devices. Also, this paper proposes an integrated processing method for image and sensing data based on location in mobile sensor networks. Additionally, according to proposed methods, we design and implement the combine adapter. This combine adapter receives a contexts data, and provides the common interface included parsing, queueing, creating unified message function. We verity the proposed method which deal with the integrated sensing data based on combine adapter efficiently. Therefore, the research is expected to help the development of a various context information service based on location in future.

• Journal of Sensor Science and Technology
• /
• v.12 no.6
• /
• pp.289-297
• /
• 2003

In this paper, we propose accurate classification method of an EEG signals during a mental tasks. In the experimental task, subjects achieved through the process of responding to visual stimulus, understanding the given problem, controlling hand motions, and select a key. To recognize the subjects' selection time, we analyzed with 4 types feature from the filtered brain waves at frequency bands of $\alpha$, $\beta$, $\theta$, $\gamma$ waves. From the analysed features, we construct specific rules for each subject meta rules including common factors in all subjects. In this system, the architecture of the neural network is a three layered feedforward networks with one hidden layer which implements the error back propagation learning algorithm. Applying the algorithms to 4 subjects show 87% classification success rates. In this paper, the proposed detection method can be a basic technology for brain-computer-interface by combining with discrimination methods.