• Smart Structures and Systems
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• v.6 no.3
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• pp.309-333
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• 2010

Civil infrastructure, in both its construction and maintenance, represents the largest societal investment in this country, outside of the health care industry. Despite being the lifeline of US commerce, civil infrastructure has scarcely benefited from the latest sensor technological advances. Our future should focus on harnessing these technologies to enhance the robustness, longevity and economic viability of this vast, societal investment, in light of inherent uncertainties and their exposure to service and even extreme loadings. One of the principal means of insuring the robustness and longevity of infrastructure is to strategically deploy smart sensors in them. Therefore, the objective is to develop novel, durable, smart sensors that are especially applicable to major infrastructure and the facilities to validate their reliability and long-term functionality. In some cases, this implies the development of new sensing elements themselves, while in other cases involves innovative packaging and use of existing sensor technologies. In either case, a parallel focus will be the integration and networking of these smart sensing elements for reliable data acquisition, transmission, and fusion, within a decision-making framework targeting efficient management and maintenance of infrastructure systems. In this paper, prudent and viable sensor and health monitoring technologies have been developed and used in several large structural systems. Discussion will also include several practical bridge health monitoring applications including their design, construction, and operation of the systems.

• Smart Structures and Systems
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• v.5 no.1
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• pp.43-54
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• 2009

This study introduces a novel approach for locating damage in a structure using wireless sensor system with local level computational capability to alleviate data traffic load on the centralized computation. Smart wireless sensor systems, capable of iterative damage-searching, mimic an optimization process in a decentralized way. The proposed algorithm tries to detect damage in a structure by monitoring abnormal increases in strain measurements from a group of wireless sensors. Initially, this clustering technique provides a reasonably effective sensor placement within a structure. Sensor clustering also assigns a certain number of master sensors in each cluster so that they can constantly monitor the structural health of a structure. By adopting a voting system, a group of wireless sensors iteratively forages for a damage location as they can be activated as needed. Since all of the damage searching process occurs within a small group of wireless sensors, no global control or data traffic to a central system is required. Numerical simulation demonstrates that the newly developed searching algorithm implemented on wireless sensors successfully localizes stiffness damage in a plate through the local level reconfigurable function of smart sensors.

• Journal of Sensor Science and Technology
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• v.33 no.4
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• pp.230-236
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• 2024

This study aimed to analyze the environmental factors affecting tomato growth by examining the correlation between weather and growth environment sensor data from P Smart Farm located in Gwangseok-myeon, Nonsan-si, Chungcheongnam-do. Key environmental variables such as the temperature, humidity, sunlight hours, solar radiation, and daily light integral (DLI) significantly affect tomato growth. The optimal temperature and DLI conditions play crucial roles in enhancing tomato growth and the photosynthetic efficiency. In this study, we developed a model to correct and predict the time-series variations in internal environmental sensor data using external weather sensor data. A linear regression analysis model was employed to estimate the external temperature variations and internal DLI values of P Smart Farm. Then, regression equations were derived based on these data. The analysis verified that the estimated variations in external temperature and internal DLI are explained effectively by the regression models. In this research, we analyzed and monitored smart-farm growth environment data based on weather sensor data. Thereby, we obtained an optimized model for the temperature and light conditions crucial for tomato growth. Additionally, the study emphasizes the importance of sensor-based data analysis in dynamically adjusting the tomato growth environment according to the variations in weather and growth conditions. The observations of this study indicate that analytical solutions using public weather data can provide data-driven operational experiences and productivity improvements for small- and medium-sized facility farms that cannot afford expensive sensors.

• Smart Structures and Systems
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• v.9 no.6
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• pp.489-504
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• 2012

For the safety of prestressed structures such as cable-stayed bridges and prestressed concrete bridges, it is very important to ensure the prestress force of cable or tendon. The loss of prestress force could significantly reduce load carrying capacity of the structure and even result in structural collapse. The objective of this study is to present a smart PZT-interface for wireless impedance-based prestress-loss monitoring in tendon-anchorage connection. Firstly, a smart PZT-interface is newly designed for sensitively monitoring of electro-mechanical impedance changes in tendon-anchorage subsystem. To analyze the effect of prestress force, an analytical model of tendon-anchorage is described regarding to the relationship between prestress force and structural parameters of the anchorage contact region. Based on the analytical model, an impedance-based method for monitoring of prestress-loss is conducted using the impedance-sensitive PZT-interface. Secondly, wireless impedance sensor node working on Imote2 platforms, which is interacted with the smart PZT-interface, is outlined. Finally, experiment on a lab-scale tendon-anchorage of a prestressed concrete girder is conducted to evaluate the performance of the smart PZT-interface along with the wireless impedance sensor node on prestress-loss detection. Frequency shift and cross correlation deviation of impedance signature are utilized to estimate impedance variation due to prestress-loss.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1057-1069
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• 2017

The applications of Wireless Sensor Networks (WSN) are progressively adopting for various smart home services such as home automation, controlling smart home household appliances, constrained application services in a smart home, etc. However, enabling a seamless and ubiquitous WSN communication between the smart home appliances is still a challenging job. Therefore, in this paper, we propose a smart home control system using an Actuator based ZigBee networking (AZNET). The working of the proposed system is further divided into three phases, 1) an interference avoidance system is adopted to mitigate the effect of interference caused due to the co-existence of IEEE 802.11x based wireless local area networks (WLAN) and WSN, 2) a sensor-based smart light control system is used to fulfill the light requirement in the smart home using the sunlight with light source, and 3) an autonomous home management system is used to regulate the usage time of the electronic appliances in the smart home. The smart is tested in real time environment to use the sunlight with light sources in a various time of the day. Similarly, the performance of the proposed smart home is verified through simulation using C# programming language. The results and analysis revealed that the proposed smart home is less affected by the interference and efficient in reducing the energy consumption of the appliances available in the smart home scenario.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.06a
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• pp.360-361
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• 2006

This paper describes a wire and wireless network sensor for temperature and humidity measurements. The network sensor comprises PLC(Power Line Communication) and RF transmitter(433MHz) for acquiring an internal (on-board) sensor signal, and measured data is transmitted to a main processing unit. The network sensor module is consist of MEMS sensor, 10-bit A/D converter, pre-amp., gain-amp., ADUC812 one chip processor and PLC/RF transmitting unit. The temperature and humidity sensor is based on MEMS piezoelectric membrane structure and is implemented by using dual function sensor for smart home and smart building.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.8
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• pp.327-342
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• 2017

In this paper, we introduce an integrated processing system of smart sensor data for IoT service which collects sensor data and efficiently processes it. Based on the technology of collecting sensor data to the development of the IoT field and sending it to the network · Based on the receiving technology, as various projects such as smart homes, autonomous running vehicles progress, the sensor data is processed and effectively An autonomous control system to utilize has been a problem. However, since the data type of the sensor for monitoring the autonomous control system varies according to the domain, a sensor data integration processing system applying the autonomous control system to various different domains is necessary. Therefore, in this paper, we introduce the Smart Sensor Data Integrated Processing System, apply it and use the window as a reference to process internal and external sensor data 1) receiveData, 2) parseData, 3) addToDatabase 3 With the process of the stage, we provide and implement the automatic window opening / closing system "Smart Window" which ventilates to create a comfortable indoor environment by autonomous control system. As a result, standby information is collected and monitored, and machine learning for performing statistical analysis and better autonomous control based on the stored data is made possible.

• Smart Structures and Systems
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• v.7 no.4
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• pp.303-317
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• 2011

A specially designed tendon, which is proposed by embedding an FBG sensor into the center king cable of a 7-wire strand tendon, was applied to monitor the prestress force and load transfer of ground anchor. A series of tensile tests and a model pullout test were performed to verify the feasibility of the proposed smart tendon as a measuring sensor of tension force and load transfer along the tendon. The smart tendon has proven to be very effective for monitoring prestress force and load transfer by measuring the strain change of the tendon at the free part and the fixed part of ground anchor, respectively. Two 11.5 m long proto-type ground anchors were made simply by replacing a tendon with the proposed smart tendon and prestress forces of each anchor were monitored during the loading-unloading step using both FBG sensor embedded in the smart tendon and the conventional load cell. By comparing the prestress forces measured by the smart tendon and load cell, it was found that the prestress force monitored from the FBG sensor located at the free part is comparable to that measured from the conventional load cell. Furthermore, the load transfer of prestressing force at the tendon-grout interface was clearly measured from the FBGs distributed along the fixed part. From these pullout tests, the proposed smart tendon is not only expected to be an alternative monitoring tool for measuring prestress force from the introducing stage to the long-term period for health monitoring of the ground anchor but also can be used to improve design practice through determining the economic fixed length by practically measuring the load transfer depth.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3958-3971
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• 2016

With Internet of Things (IoT) technology, home environment becomes smarter than ever. Not only smart devices such as smart phone or smart TV, but also various IoT devices including sensor, smart thermostat, and smart scale has now become very common on the market. These devices have connectivity to the Internet, so that user can read data from the device or control the device using Internet technology. However, due to diversity of smart home requirements, device collaboration in smart home remains a challenging task still. Usually smart home is built with various technologies to fulfill its own purpose, and these purposes cover very wide area from controlling low-power sensor devices to controlling high-performance devices like smart TV and smart phone. This variety of smart home requirements makes smart home very complicated due to mixed network architecture, protocol and technology. In this paper, a framework to enable managing and collaborating heterogeneous IoT devices in smart home environment is proposed. Several programming models are defined in the proposed framework to make application development for heterogeneous devices more intuitive. The proposed framework has been implemented as a web service, and a case study with real-world smart home IoT devices is presented.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.4
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• pp.470-475
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• 2014

Recently, smart phones are spread out as a universal mobile terminal equipment. Its provide USB interface to connect with various devices. Smart phones may be replaced with high priced monitoring equipments because of portability and mobility as its merit. In addition to that, the various sensor devices detecting surrounding environment of the radioactivity, sodium or electromagnetic waves have been announced. But the plug and play methods of sensor devices have some problem to connect smart phone with USB accessory device. We propose an integrated methodology that can connect smart phone with USB sensor devices and also, we realized USB accessory plug and play with one App that can collect measurement data through various sensor devices.