• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2003.11a
• /
• pp.792-796
• /
• 2003

In this paper, to detect external sound frequency on the latticed structure, fiber optic sensor net using Sagnac interferometer was fabricated and tested. The latticed structure fabricated with dimension of 50cm in width and 50cm in height, the optical fiber, 50m in length, distributed and fixed on the latticed structure. Single mode fiber, a laser with 1,550nm in wavelength, 2${\times}$2 coupler were used. External sound signal applied to the fiber optic sensor net and the detected optical signals were compared and analyzed to the detected microphone signals against time and frequency domain. Based on the experimental results, fiber optic sensor net using Sagnac interferometer detected external sound frequency, effectively. This system can be expanded to the structural health monitoring system.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.14 no.7
• /
• pp.569-576
• /
• 2004

In this paper, to detect external sound frequencies on the latticed structure, fiber optic sensor net using Sagnac interferometer was fabricated and tested. The latticed structure was fabricated with a dimension of 50 cm in width and 50 cm in height. The optical fiber of 50m in length was distributed and fixed on the surface of the latticed structure. Single mode fiber, a laser with 1,550 nm in wavelength, 2 ${\times}$ 2 coupler were used. External sound signal, 240 Hz, 495 Hz, 1.445 kHz, 2k Hz, applied to the fiber optic sensor net and the detected optical signals were compared to the detected microphone signals against time and frequency domains. Based on the experimental results, fiber optic sensor net using Sagnac interferometer detected external sound frequency, effectively. This system can be expanded to the structural health monitoring system.

• Journal of the Institute of Convergence Signal Processing
• /
• v.7 no.3
• /
• pp.87-94
• /
• 2006

For realizing an ubiquitous home network(uHome-net), various sensors should be able to be connected to an integrated wire/wireless sensor network. This paper describes an application case of applying LonWorks technology being widely used in control network to wire/wireless sensor network in uHome-net and the design and application of LonRF device that consists of a neuron chip including LonTalk protocol, a 433.92MHz RF transceiver, a sensor, and application programs. As an application example of the LonRF device, the LonRF smart badge that can measure the 3D location of objects in indoor environment and interwork with the uHome-net was developed. LonRF device based home network services were realized on the uHome-net testbed such as indoor positioning service, remote surveillance service and remote metering service were realized. This research shows that LonWorks technology based sensor network could be applicable to the control network in an ubiquitous home network and the LonRF device can be used as a wireless node in various sensor networks.

• Journal of Korea Spatial Information System Society
• /
• v.12 no.1
• /
• pp.28-36
• /
• 2010

Some context is characterized by a single event in computing environment, but many other contexts are determined by a lot of things which occur with a space and a time. The Realtime Sensor Network context-awareness service that interacts with the physical space can have property such as time. A methodology that is specified the relationship between the contexts and the service needs to be developed to Realtime context-awareness deal with spatio-temporal. In this paper, we propose an approach which should include spatio-temporal property in the context model, and verify its effectiveness using enhanced Petri-Net. The context-awareness service modeling of Realtime Sensor Network is discussed the properties of model such as basic Petri-Net, patterned Petri-Net, or Spatio-temporal Petri-Net. The proposed methodology demonstrated using an example that is SAEMANGUEM warming watching system. The use of Spatio-temporal Petri-Net will contribute not only to develop the application but also to model the spatio-temporal context awareness.

• The KIPS Transactions:PartB
• /
• v.15B no.3
• /
• pp.219-228
• /
• 2008

For real-time social networking service, mobile interaction in a usable-unified-ubiquitous (U3) web service was studied. Both as a convenient mobile HCI for real-time social networks and as indexing keys to metadata information in ubiquitous web service, the multi-lingual single-character domain names (e.g. 김.net, 이.net, 가.net, ㄱ.net, ㄴ.net, ㅎ.net, ㅏ.net, ㅔ.net, ㄱ.com, ㅎ.com) are convenient mobile interfaces when searching for social information and registering information. We introduce the sketched design goals and experience of mobile interaction in Korea, Japan and China, with the implementation of real-time social networking service as an example of U3 Web service. We also introduce the possibility of extending the application to the metadata directory service in IP-USN (IP-based Ubiquitous Sensor Network) for a unified information management in the service of social networking and sensor networking.

• Nuclear Engineering and Technology
• /
• v.53 no.7
• /
• pp.2229-2236
• /
• 2021

In nuclear-related facilities, such as nuclear power plants, research reactors, accelerators, and nuclear waste storage sites, radiation detection, and mapping are required to prevent radiation overexposure. Sensor network systems consisting of radiation sensor interfaces and wxireless communication units have become promising tools that can be used for data collection of radiation detection that can in turn be used to draw a radiation map. During data collection, malfunctions in some of the sensors can occasionally occur due to radiation effects, physical damage, network defects, sensor loss, or other reasons. This paper proposes a reproduction strategy for radiation maps using a U-net model to compensate for the loss of radiation detection data. To perform machine learning and verification, 1,561 simulations and 417 measured data of a sensor network were performed. The reproduction results show an accuracy of over 90%. The proposed strategy can offer an effective method that can be used to resolve the data loss problem for conventional sensor network systems and will specifically contribute to making initial responses with preserved data and without the high cost of radiation leak accidents at nuclear facilities.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.4 no.4
• /
• pp.41-49
• /
• 2008

Sensor networks are often deployed in unattended environments, thus leaving these networks vulnerable to false data injection attacks in which an adversary injects forged reports into the network through compromised nodes. Such attacks by compromised sensors can cause not only false alarms but also the depletion of the finite amount of energy in a battery powered network. In order to reduce damage from these attacks, several security solutions have been proposed. Researchers have also proposed some techniques to increase the energy-efficiency of such security solutions. In this paper, we propose a CH(Cluster Header) selection algorithm to choose low power delivery method in sensor networks. The CNP(Contract Net Protocol), which is an approach to solve distribution problems, is applied to choose CHs for event sensing. As a result of employing CNP, the proposed method can prevent dropping of sensing reports with an insufficient number of message authentication codes during the forwarding process, and is efficient in terms of energy saving.

• Proceedings of the KIEE Conference
• /
• 2003.11b
• /
• pp.223-226
• /
• 2003

This paper presents a realization of sensor signal processing(noise filtering) and Fieldbus based communication for condition monitoring of check valve. we first acquired the AE(Acoustic Emission) sensor data at the KAERI check valve test loop, and their frequencies were analyzed to find the informative band. To reject background noises, bandpass filters have been designed. Also, to send the processed data to a remote site, wired communication facility has been realized via DeviceNet.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.5
• /
• pp.55-67
• /
• 2022

Sensor data can provide fault diagnosis for equipment. However, the cause analysis for fault results of equipment is not often provided. In this study, we propose an explainable convolutional neural network framework for the sensor-based time series classification model. We used sensor-based time series dataset, acquired from vehicles equipped with sensors, and the Wafer dataset, acquired from manufacturing process. Moreover, we used Cycle Signal dataset, acquired from real world mechanical equipment, and for Data augmentation methods, scaling and jittering were used to train our deep learning models. In addition, our proposed classification models are convolutional neural network based models, FCN, 1D-CNN, and ResNet, to compare evaluations for each model. Our experimental results show that the ResNet provides promising results in the context of time series classification with accuracy and F1 Score reaching 95%, improved by 3% compared to the previous study. Furthermore, we propose XAI methods, Class Activation Map and Layer Visualization, to interpret the experiment result. XAI methods can visualize the time series interval that shows important factors for sensor data classification.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
• /
• v.28 no.3
• /
• pp.237-244
• /
• 2022

Onions are a significant crop in Korea, and cultivation is increasing every year along with high demand. Onions are planted in the fall and mainly harvested in June, the rainy season, therefore, physiological changes in onion bulbs during long-term storage might have happened. Onions are stored in cold room and at adequate relative humidity to avoid quality loss. In this study, bio-yield stress and weight loss were measured as the quality parameters of net packaged onions during 10 weeks of storage, and the storage environmental conditions are monitored using sensor networks systems. Quality estimation of net packaged onion during storage was performed using the storage environmental condition data through machine learning approaches. Among the suggested estimation models, support vector regression method showed the best accuracy for the quality estimation of net packaged onions.