The IoT-based sensor network is one of the methods that can be efficiently applied to maintain the facilities, such as bridges, at a low cost. In this study, based on LoRa LPWAN, one of the IoT communications, sensor board for cable tension monitoring, data acquisition board for constructing sensor network along with existing measurement sensors, are developed to create bridge structural health monitoring system. In addition, we designed and manufactured a smart sensor node for LoRa communication and established a sensor network for monitoring. Further, we constructed a test bed at the Yeonggwang Bridge to verify the performance of the system. The test bed verification results suggested that the LoRa LPWAN-based sensor network can be applied as one of the technologies for monitoring the bridge structure soundness; this is excellent in terms of data rate, accuracy, and economy.

A wireless sensor network is emerging technology and intelligent wireless communication paradigm that is dynamically aware of its surrounding environment. It is also able to respond to it in order to achieve reliable and efficient communication. The dynamical cognition capability and environmental adaptability rely on organizing dynamical networks effectively. However, optimally clustering the cognitive wireless sensor networks is an NP-complete problem. The objective of this paper is to develop an optimal sensor network design for maximizing the performance. This proposed Ranking Artificial Bee Colony (RABC) is developed based on Artificial Bee Colony (ABC) with ranking strategy. The ranking strategy can make the much better solutions by combining the best solutions so far and add these solutions in the solution population when applying ABC. RABC is designed to adapt to topological changes to any network graph in a time. We can minimize the total energy dissipation of sensors to prolong the lifetime of a network to balance the energy consumption of all nodes with robust optimal solution. Simulation results show that the performance of our proposed RABC is better than those of previous methods (LEACH, LEACH-C, and etc.) in wireless sensor networks. Our proposed method is the best for the 100 node-network example when the Sink node is centrally located.

국내 고도성장기 이후 본격 건설되기 시작한 사회 기반 시설물은 노후화가 빠르게 진행되고 있다. 특히 사고 발생 시 대량 인명 피해로 직결될 수 있는 교량, 터널 등의 대형 구조물들에 대한 안전성 평가가 필요하다. 하지만, 기존의 유선 센서 기반의 SHM을 개선한 무선 스마트 센서네트워크는 짧은 신호도달거리로 인해 경제적이고 효율적인 시스템 구축이 힘들다. 따라서 LoRa LPWAN시스템은 사물인터넷의 확산과 더불어 저전력 장거리통신이 각광을 받고 있으며, 이를 구조건전성 모니터링에 응용함으로써 경제적이면서도 효율적인 SHM 구축이 가능하다. 본 연구에서는 LoRa LPWAN의 구조건전성 모니터링에 적용 가능성을 검토하고 비면허 통신 대역을 사용함으로 인해 발생하는 채널간의 충돌을 해결하면서 대역폭을 효율적으로 활용할 수 있는 채널 기반의 LoRa 네트워크 운영방법을 제안한다.

본 연구에서는 각기 다른 두 제조사의 AgNW를 활용하여 스핀코팅 속도, 열처리 온도 및 방법 그리고 PDMS코팅 속도에 따른 AgNW/PDMS composite공정 연구를 실시하였다. 실험결과 peel off 특성에 영향을 미치는 인자로 건조방식이 주요하게 작용하며 공정온도 또한 전극 특성에 영향을 주었다. 핫플레이트를 사용한 건조방식은 한방향 열전달로 인해 PDMS를 충분히 건조시키지 못하였지만 오븐 건조를 통해 그 결점을 보완할 수 있었다. 또한, PDMS 코팅속도가 증가함에 따라 스트레처블 특성이 향상되었고 GF는 0.03에서 0.07로 약 100정도 향상되었다.

선박 및 해양구조물의 화물 중 많은 수가 가연성, 휘발성의 석유 및 석유 가공 화물이다. 뿐만 아니라 컨테이너 박스, 벌크화물, 차량 등의 중량 화물이 그 나머지를 차지한다. 게다가 선박은 파랑, 해류 등의 하중을 주기/비주기적으로 받기 때문에 화물의 위치 및 이동 가능성이 존재한다. 그렇기 때문에 선상 사고 위험은 육상의 산업현장 보다 훨씬 크다. 선박 및 해양구조물은 화물 및 화물의 영향으로 인한 사고 위험성이 항시 존재하기 때문에 그 모니터링과 대비가 반드시 필요하다. 이에 본 연구에서는 선상에서 선원 및 작업자의 안전을 보장하기 위해 무선센서네트워크를 도입하여 모니터링 시스템을 구축하기 위한 연구를 진행하였다.

A kind of field bus called Actuator and Sensor interface bus(AS-i) was designed in this paper. The configuration of AS-i network system used Application Specific Integrated Circuit(ASIC) SAP5S chip and PLC S7-200 station, which included CPU 224 and AS-i master module CP 243-2. We also created an example program for PLC S7-200 to control AS-i network. The fire and smoke detection system was made with AS-i network system that was designed. This system had got more advantages than other system such as number of stations, easy installation, wide working area, etc. And designed system can be used as a partner network for higher level field bus networks.

This paper proposes an information maximization method to extract useful informations for streaming signals. The information maximization method is to extract signals using stream partitioning function and standard normalization function. The stream partitioning function divides streaming signals into intervals. Signal coefficient and interval coefficient are used at generating a interval by using stream partitioning function. Signal coefficient determines the quantity of data included in a signal interval. Interval coefficient determines the starting point of a signal interval. The standard normalization function determines a signal range by using the probability density function for streaming signals. The information maximization method becomes resistant to outliers and missing values. A normal signal can be extracted effectively for streaming signals by the Information maximization method. The effectiveness of proposed method are also presented by several experimental results.

In the previous study, the construction guide line of IT infra-structure for a u-City was introduced. However, it is only concentrated on the components and construction procedure for provider-oriented and technology-oriented sensor networks. In this paper the architecture and building process of demander-oriented sensor networks for sustainable u-City service are proposed. In the paper it is described (1) the enhancement methods of the procedure that can be flexibly constructed according to the scale of the project, (2) the methods that can improve the structure from the wireless sensor network such as RFID/USN to the hybrid sensor network, and (3) the consideration factors for providing the sustainable u-City service.

Recently, one-dimensional semiconducting nanomaterials have attracted considerable interest for their potential as building blocks for fabricating various nanodevices. Among these semiconducting nanomaterials,, SnO2 nanostructures including nanowires, nanorods, nanobelts, and nanotubes were successfully synthesized and their electrochemical properties were evaluated. Although SnO2 nanowires and nanobelts exhibit fascinating gas sensing characteristics, there are still significant difficulties in using them for device applications. The crucial problem is the alignment of the nanowires. Each nanowire should be attached on each die using arduous e-beam or photolithography, which is quite an undesirable process in terms of mass production in the current semiconductor industry. In this study, a simple process for making sensitive SnO2 nanowire-based gas sensors by using a standard semiconducting fabrication process was studied. The nanowires were aligned in-situ during nanowire synthesis by thermal CVD process and a nanowire network structure between the electrodes was obtained. The SnO2 nanowire network was floated upon the Si substrate by separating an Au catalyst between the electrodes. As the electric current is transported along the networks of the nanowires, not along the surface layer on the substrate, the gas sensitivities could be maximized in this networked and floated structure. By varying the nanowire density and the distance between the electrodes, several types of nanowire network were fabricated. The NO2 gas sensitivity was 30~200 when the NO2 concentration was 5~20ppm. The response time was ca. 30~110 sec.

현재까지 USN(Ubiquitous Sensor Network)이라 통칭되어지는 센서망은 불특정 공간에 배포된 무선방식의 센서노드를 통해 유선방식의 센서 인프라를 대체하려는 기술 지향적 및 공급자중심의 구성을 가지고 있다. 본 논문은 기존의 공급자 위주의 기술지향적인 제한적 구성에서 벗어나, u-City에서 제공하고자 하는 서비스들의 목적과 서비스 대상의 요구사항분석을 기반으로 성능, 품질, 비용 등을 고려하도록 다양한 기술들을 융 복합하여 서비스를 제공하는 하이브리드 센서망의 제안을 위한 선행 연구 결과이다. 우선, 센서망과 u-City 서비스와의 관계에 대해 서술한 후, 기존 센서망에 대한 조사, 분석 결과 및 문제점, 그리고 선진국에서의 하이브리드 센서망 적용 사례와 시사점에 대해 논의하도록 한다.

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.

This paper presents a 6-DOF relocalization using a 3D laser scanner and a monocular camera. A relocalization problem in robotics is to estimate pose of sensor when a robot revisits the area. A deep convolutional neural network (CNN) is designed to regress 6-DOF sensor pose and trained using both RGB image and 3D point cloud information in end-to-end manner. We generate the new input that consists of RGB and range information. After training step, the relocalization system results in the pose of the sensor corresponding to each input when a new input is received. However, most of cases, mobile robot navigation system has successive sensor measurements. In order to improve the localization performance, the output of CNN is used for measurements of the particle filter that smooth the trajectory. We evaluate our relocalization method on real world datasets using a mobile robot platform.

3D depth perception has played an important role in robotics, and many sensory methods have also proposed for it. As a photodetector for 3D sensing, single photon avalanche diode (SPAD) is suggested due to sensitivity and accuracy. We have researched for applying a SPAD chip in our fusion system of time-of-fight (ToF) sensor and stereo camera. Our goal is to upsample of SPAD resolution using RGB stereo camera. Currently, we have 64 x 32 resolution SPAD ToF Sensor, even though there are higher resolution depth sensors such as Kinect V2 and Cube-Eye. This may be a weak point of our system, however we exploit this gap using a transition of idea. A convolution neural network (CNN) is designed to upsample our low resolution depth map using the data of the higher resolution depth as label data. Then, the upsampled depth data using CNN and stereo camera depth data are fused using semi-global matching (SGM) algorithm. We proposed simplified fusion method created for the embedded system.

In this study, concrete slab with insulation and non-insulated formwork was used to monitor and control its strength using a wireless sensor network with equivalent age method. As a result, the temperature and compressive strength of the structures were monitored without any problems, which revealed a good management tool.

In this study examined the strength of wall concrete using insulated molds and non-insulated forms by monitoring the strength of the structure using a wireless sensor network by maturity method. It was confirmed that the temperature and compressive strength of the structures are monitored in real time, along with effective strength control.

Based on IoT (Internet of Things) where its concept contains providing convenience to human life by connecting every objects around us, numerous projects have been done in civil engineering field. This paper has conducted the basic study on adopting IoT sensing technology and network system into harbor.

사회기반시설물의 안전성을 효과적으로 평가하고 모니터링하기 위해 무선 스마트 센서가 개발되어 전 세계적으로 연구가 진행되 고 있다. 무선 스마트 센서는 통상 계측 및 임베디드 데이터 연산, 무선 통신이 가능한 공통점을 갖고 있어 기존의 유선 기반 센서가 가진 단점을 극복할 수 있을 것으로 기대되고 있다. 그러나 구조물의 장기 모니터링의 경우 내구성이 충분하지 못해 발생하는 센서 고장이나, 환경적 이유 로 인한 무선 통신이 불안정할 경우 계측 데이터를 가져올 수 없는 문제가 발생할 수 있다. 본 연구에서는 무선 스마트 센서 기반의 네트워크에 서 이와 같은 문제로 센서 노드에 무선 통신으로 접근할 수 없는 경우를 대처하기 위해, 칼만 필터 기반의 데이터 복구를 수행하여 무선 스마트 센서 네트워크의 신뢰성을 향상시키는 기법을 제안한다. 본 논문에서는 무선 스마트 센서의 연산 기능을 활용하여 네트워크 내에서 계측된 가 속도 데이터를 바탕으로 유실된 센서의 가속도 계측 데이터를 추정한다. 개발된 무선 스마트 센서 네트워크 시스템의 성능을 확인하기 위해 단 순보 구조에서 실험을 수행하여 추정된 가속도 응답과 계측 값을 비교하였다.

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.

Temperature of fresh concrete can be effectively used to predict the strength of concrete being cured and make an informed decision for stripping the molds. A hygrothermograph and thermo-couple sensors that require an extensive wiring have been applied to measure a temperature of concrete at the early stage of the curing process on site. Therefor, this study on the strength prediction using Maturity is mainly focused on, but the study on the concrete mixing blast furnace slag powder is insufficient. The purpose of this study is to investigate the relationships between compressive strength and equivalent age by Maturity function and is to compare and examine the strength prediction of concrete mixing Blast Furnace Slag Power using ACI and Logistic Curve prediction equation.