• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.135-147
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• 2023

Internet of things has revolutionaries every field of life due to the use of artificial intelligence within Machine Learning. It is successfully being used for the study of Radiation monitoring, prediction of Ultraviolet and Electromagnetic rays. However, there is no particular system available that can monitor and detect waves. Therefore, the present study designed in which IOT enables intelligence system based on machine learning was developed for the prediction of the radiation and their effects of human beings. Moreover, a sensor based system was installed in order to detect harmful radiation present in the environment and this system has the ability to alert the humans within the range of danger zone with a buzz, so that humans can move to a safer place. Along with this automatic sensor system; a self-created dataset was also created in which sensor values were recorded. Furthermore, in order to study the outcomes of the effect of these rays researchers used Support Vector Machine, Gaussian Naïve Bayes, Decision Trees, Extra Trees, Bagging Classifier, Random Forests, Logistic Regression and Adaptive Boosting Classifier were used. To sum up the whole discussion it is stated the results give high accuracy and prove that the proposed system is reliable and accurate for the detection and monitoring of waves. Furthermore, for the prediction of outcome, Adaptive Boosting Classifier has shown the best accuracy of 81.77% as compared with other classifiers.

• Journal of Korea Multimedia Society
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• v.18 no.6
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• pp.742-752
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• 2015

The communications through the power lines are called as the PLC and this is a common name for the communication modes for the information delivery. This technology transmits the data through the power lines on which the information is stored with the form of high frequency signal. The characteristic of the frequency signal is that the signal can be separated from the power line through exclusive power line modem and transmitted to the terminal devices. In this paper, 'In-home Headcount' checking algorithm using Wi-Fi and taking above mentioned advantages is proposed, and the basic Technology for such Solitary Senior Citizen's Lonely Death monitoring system has been designed and implemented. The comparative analysis has been conducted in this paper with the test-operated and test bed-completed 'Hyosimi 119 Safety-Welfare System' which is still being tested since 2008. With the 'In-home Headcount Checking Algorithm', Wi-Fi connection/disconnection status and SSIDs of relevant Wi-Fis will be checked. We expect that our proposed method will become as the basic Technology which can prevent lonely deaths of elderly people living alone. Since the PLC technology can be normally implement all the functions used on internet anticipate that the technology could be applied to many areas to construct a new form of communication network.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.783-788
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• 2020

Surges generated by direct strike or induction of lightning, frequent opening and closing of power system breakers, etc. cause excessive overvoltage, which can interfere with normal operation of transformers, circuit breakers, and power equipment. In order to prevent such phenomena, this study goes further from the method of establishing countermeasures by installing lightning arresters on power equipment or lines in parallel, and furthermore, remotely checking the condition of the lightning arrester and preparing immediate countermeasures when an event occurs. The purpose of the study is to prevent damage in advance.

• Journal of Sensor Science and Technology
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• v.24 no.5
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• pp.331-341
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• 2015

In this paper, real-time water quality monitoring system of small water supply facilities based on IEEE 802.15.4e-2012 DSME MAC and IEEE 802.15.4g-2012 PHY standard is presented, which is capable to acquire for highly reliable water quality information in the wide outdoor areas for effective water quality management of small water quality facilities is distributed in the long distance and remote areas. Previously, Long distance transmission is difficult in most water quality sensor module is using RS-485 protocol. But with this system, even in harsh outdoor environment, it is possible to establish a radio wave sensor in a wide area network, and not only water quality sensor shall be connected to the wireless system, but also wireless integrated management system shall provide more effective way of management of the numerous small water supply facilities spread throughout the community, so that the administrator can remotely monitor the data of water turbidity, pH, residual chlorine in the water-supply, water-level, and generate alarm to cope with risks. The management of small water facilities is done by residents will be very effective to notice water quality information of small water facilities to residents.

• Smart Structures and Systems
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• v.32 no.3
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• pp.179-193
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• 2023

This study explores an alternative to the existing centralized process for data anomaly detection in modern Internet of Things (IoT)-based structural health monitoring (SHM) systems. An edge intelligence framework is proposed for the early detection and classification of various data anomalies facilitating quality enhancement of acquired data before transmitting to a central system. State-of-the-art deep neural network pruning techniques are investigated and compared aiming to significantly reduce the network size so that it can run efficiently on resource-constrained edge devices such as wireless smart sensors. Further, depthwise separable convolution (DSC) is invoked, the integration of which with advanced structural pruning methods exhibited superior compression capability. Last but not least, quantization-aware training (QAT) is adopted for faster processing and lower memory and power consumption. The proposed edge intelligence framework will eventually lead to reduced network overload and latency. This will enable intelligent self-adaptation strategies to be employed to timely deal with a faulty sensor, minimizing the wasteful use of power, memory, and other resources in wireless smart sensors, increasing efficiency, and reducing maintenance costs for modern smart SHM systems. This study presents a theoretical foundation for the proposed framework, the validation of which through actual field trials is a scope for future work.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Economic and Environmental Geology
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• v.53 no.5
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• pp.609-617
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• 2020

After introducing the industry 4.0 policy, Korean government announced 'Digital New Deal' and 'Green New Deal' as 'Korean New Deal' in 2020. We analyzed Korea Institute of Geoscience and Mineral Resources (KIGAM)'s research projects related to that policy and conducted markets analysis focused on Digital Twin and environmental monitoring technologies. Regarding 'Data Dam' policy, we suggested the digital geo-contents with Augmented Reality (AR) & Virtual Reality (VR) and the public geo-data collection & sharing system. It is necessary to expand and support the smart mining and digital oil fields research for '5th generation mobile communication (5G) and artificial intelligence (AI) convergence into all industries' policy. Korean government is suggesting downtown 3D maps for 'Digital Twin' policy. KIGAM can provide 3D geological maps and Internet of Things (IoT) systems for social overhead capital (SOC) management. 'Green New Deal' proposed developing technologies for green industries including resource circulation, Carbon Capture Utilization and Storage (CCUS), and electric & hydrogen vehicles. KIGAM has carried out related research projects and currently conducts research on domestic energy storage minerals. Oil and gas industries are presented as representative applications of digital twin. Many progress is made in mining automation and digital mapping and Digital Twin Earth (DTE) is a emerging research subject. The emerging research subjects are deeply related to data analysis, simulation, AI, and the IoT, therefore KIGAM should collaborate with sensors and computing software & system companies.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.191-204
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• 2024

IOT has carried out important function in converting the traditional fitness care corporation. With developing call for in population, traditional healthcare structures have reached their outmost functionality in presenting sufficient and as plenty as mark offerings. The worldwide is handling devastating developing antique population disaster and the right want for assisted-dwelling environments is turning into inevitable for senior citizens. There furthermore a determination by means of the use of way of countrywide healthcare organizations to increase crucial manual for individualized, right blanketed care to prevent and manipulate excessive coronial situations. Many tech orientated packages related to Health Monitoring have been delivered these days as taking advantage of net boom everywhere on globe, manner to improvements in cellular and in IOT generation. Such as optimized indoor networks insurance, community shape, and fairly-low device fee performances, advanced tool reliability, low device energy consumption, and hundreds higher unusual common usual performance in network safety and privacy. Studies have highlighted fantastic advantages of integrating IOT with health care location and as era is improving the rate also cannot be that terrific of a problem. However, many challenges in this new paradigm shift notwithstanding the fact that exist, that need to be addressed. So the out most purpose of this research paper is 3 essential departments: First, evaluation of key elements that drove the adoption and boom of the Internet of factors based totally domestic some distance off monitoring; Second, present fashionable improvement of IOT in home a long manner off monitoring shape and key building gadgets; Third, communicate future very last effects and distinct guidelines of such type a long way off monitoring packages going ahead. Such Research is a wonderful manner in advance now not outstanding in IOT Terminology but in standard fitness care location.

• Journal of the Korean Solar Energy Society
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• v.38 no.3
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• pp.21-28
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• 2018

The objects of PV (Photovoltaic) monitoring system is to reduce the loss of system and operation and maintenance costs. In case of PV plants with configured of centralized inverter type, only 1 PV module might be caused a large loss in the PV plant. For this reason, the monitoring technology of PV module-level that find out the location of the fault module and reduce the system losses is interested. In this paper, a fault diagnosis algorithm are proposed using thermal and electrical characteristics of PV modules under failure. In addition, the monitoring system applied with proposed algorithm was constructed. The wireless sensor using LoRa chip was designed to be able to connect with IoT device in the future. The characteristics of PV module by shading is not failure but it is treated as a temporary failure. In the monitoring system, it is possible to diagnose whether or not failure of bypass diode inside the junction box. The fault diagnosis algorithm are developed on considering a situation such as communication error of wireless sensor and empirical performance evaluation are currently conducting.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2444-2452
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• 2022

The field-programmable gate array (FPGA) is gaining popularity in industrial automation such as nuclear power plant instrumentation and control (I&C) systems due to the benefits of having non-existence of operating system, minimum software errors, and minimum common reason failures. Separate functions can be processed individually and in parallel on the same integrated circuit using FPGAs in comparison to the conventional microprocessor-based systems used in any plant operations. The use of FPGAs offers the potential to minimize complexity and the accompanying difficulty of securing regulatory approval, as well as provide superior protection against obsolescence. Wireless sensor networks (WSNs) are a new technology for acquiring and processing plant data wirelessly in which sensor nodes are configured for real-time signal processing, data acquisition, and monitoring. ZigBee (IEEE 802.15.4) is an open worldwide standard for minimum power, low-cost machine-to-machine (M2M), and internet of things (IoT) enabled wireless network communication. It is always a challenge to follow the specific topology when different Zigbee nodes are placed in a large network such as a plant. The research article focuses on the hardware chip design of different topological structures supported by ZigBee that can be used for monitoring and controlling the different operations of the plant and evaluates the performance in Vitex-5 FPGA hardware. The research work presents a strategy for configuring FPGA with ZigBee sensor nodes when communicating in a large area such as an industrial plant for real-time monitoring.