Nowadays ubiquitous sensor network (USN) has been considered as a key technique in all kinds of industrial area. The main purpose of this study is to search and analyze systems in real industrial fields based on USN. USN technique has been applied into various industrial fields such as ground/underground management system, visitor counter system, monitoring system, unmanned vehicles system and so on. The result of this study will be fruitful not only for researches but also for practices in industrial fields related to USN.

In this paper, And improve the performance of the current bridge inspection systems Intelligent sensor platform of the bridge, Bridges Management and Control, U- disaster warning, Intelligent prevention, etc. The intelligence to maximize the capabilities of the existing bridge inspection systems It proposes an efficient management plan through a ubiquitous sensor network. Since these services are very important to minimize situations where the bridge disaster casualties. Through RFID, RTLS and smartphones, IT technology and sensor fusion, etc. Build bridges to the entire inspection time and unattended automated disaster detection system minimizes the time to invest in bridge inspection and efficiency is to be maximized.

The objectives of this research have been focussed on 1) developing prediction techniques for the flash flood and landslide based on rainfall prediction data in agricultural area and 2) developing an integrated forecasting system for the abrupt disasters using USN based real-time disaster sensing techniques. This study contains following steps to achieve the objective; 1) selecting rainfall prediction data, 2) constructing prediction techniques for flash flood and landslide, 3) developing USN and communication network protocol for detecting the abrupt disaster suitable for rural area, & 4) developing mobile application and SMS based early warning service system for local resident and tourist. Local prediction model (LDAPS , UM1.5km) supported by Korean meteorological administration was used for the rainfall prediction by considering spatial and temporal resolution. NRCS TR-20 and infinite slope stability analysis model were used to predict flash flood and landslide. There are limitations in terms of communication distance and cost using Zigbee and CDMA which have been used for existing disaster sensors. Rural suitable sensor-network module for water level and tilting gauge and gateway based on proprietary RF network were developed by consideration of low-cost, low-power, and long-distance for communication suitable for rural condition. SMS & mobile application forecasting & alarming system for local resident and tourist was set up for minimizing damage on the critical regions for abrupt disaster. The developed H/W & S/W for integrated abrupt disaster forecasting & alarming system was verified by field application.

최근 장대 교량 및 복잡한 교량의 형상이 자주 건설됨에 따라, 교량의 안전도 및 건전성 평가에 많은 관심이 집중되고 있다. 장대교량의 경우 다양한 종류의 계측기 들이 설치되어, 측정된 센싱(Sensing)자료를 신호처리를 통해 케이블을 이용하여 장거리 전송하거나, Smart Health 모니터링 개념으로 교량 현장에서 게이트웨이(Gateway)를 통해 외부 무선통신망에 연결하여 정보를 전송하는 최신 무선통신 기술을 적용하고 있다. 하지만, 전 세계적으로 발생한 교량 관련 안전사고의 경우 위험 또는 사고인지에 따른 실시간 예방적, 지능적 조치가 미흡하여 대형사로를 유발한 것으로 보고되고 있다. 이런 문제점을 해결하고자 본 논문에서는 첨단 무선통신인 RFID(Radio Frequency Identification)/USN (Ubiquitous Sensor Network)기술의 기본 개념인 "Communication Among things" 사물 간 통신 개념을 교량 계측모니터링에 적용하여, 교량에 탑재된 다양한 계측 센서 노드로부터 내구성/안전성에 관련된 위험신호를 추출하여 긴박한 안전사고 등이 인지된 경우 사고예방개념에서 사물 간 통신개념으로, 교량의 센서노드가 바로 교량 인근의 교통신호등에 RF 무선 전파를 송신하여 교량의 교통을 차단하며, 대형 사고를 예방할 수 있는 USN기반의 지능형 교량 시스템을 구축을 위한 센서노드모듈을 설계 하였으며, TinyOS 기반 미들웨어 설계와 센서 자유공간 송수신거리 테스트를 실시하여 센서의 성능을 검증 하였다.

We propose and develop Home Security robot system based on Sensor Network (HSSN) configured by sensor nodes including radio frequency (RF), ultrasonic, temperature, light and sound sensors. Our system can acknowledge security alarm events that are acquired by sensor nodes and relayed in the hop-by-hop transmission way. There are sensor network, Home Security Mobile Robot (HSMR) and Home Server(HS) in this system. In the experimental results of this system, we presented that our system has more enhanced performance of response to emergency context and more speedy and accurate path planning to target position for arriving an alarm zone with obstacle avoidance and acquiring the context-aware information.