• International Journal of Contents
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• v.15 no.2
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• pp.75-78
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• 2019

The Integration technique of combining the measurement method with the fine precision of the sensor collecting the satellite-based information to determine the displacement space is available to a variety of diagnostic information. The measurement method by a GNSS with the sensors is needed since there will always be occasional occurrence of natural disasters caused by various environmental factors and the surroundings. Such attempts carried out nationally by distributed torsional displacement of the terrain and facilities. The combination of the various positioning analysis of mm-class for the facility of main area observed is required constantly in real time information of the USN/IoT Smart sensors and should be able to utilize such information as a precisely fine positioning information for the precisely fine displacement of the semi-permanent main facilities. In this study, for the installation of the receiving system, the USN/IoT base line positioning are easily accessible for the target bridges. Transmitting hourly from the received data is also executed in real time using the wireless Wi-Fi/Bluetooth bridges and related facilities to automatically process a fine position displacement. The results obtained from this method can be analyzed by real-time monitoring for a large structure or facilities for disaster prevention.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3275-3298
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• 2022

Cloud-based architectures for precision agriculture are domain-specific controlled and require remote access to process and analyze the collected data over third-party cloud computing platforms. Due to the dynamic changes in agricultural parameters and restrictions in terms of accessing cloud platforms, developing a locally controlled and real-time configured architecture is crucial for efficient water irrigation and farmers management in agricultural fields. Thus, we present a new implementation of an independent sensor-enabled architecture using variety of wireless-based sensors to capture soil moisture level, amount of supplied water, and compute the reference evapotranspiration (ETo). Both parameters of soil moisture content and ETo values was then used to manage the amount of irrigated water in a small-scale agriculture field for 356 days. We collected around 34,200 experimental data samples to evaluate the performance of the architecture under different agriculture parameters and conditions, which have significant influence on realizing real-time monitoring of agricultural fields. In a proof of concept, we provide empirical results that show that our architecture performs favorably against the cloud-based architecture, as evaluated on collected experimental data through different statistical performance models. Experimental results demonstrate that the architecture has potential practical application in a many of farming activities, including water irrigation management and agricultural condition control.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.33-42
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• 2022

One of the most pressing socioeconomic problems confronting humanity on a worldwide scale is food security, particularly in light of the expanding population and declining land productivity. These causes have increased the number of people in the world who are at risk of starving and have caused the natural ecosystems to degrade at previously unheard-of speeds. Happily, the Internet of Things (IoT) development provides a glimmer of light for those worried about food security through smart agriculture-a development that is particularly relevant to automating food production operations in order to reduce labor expenses. When compared to conventional farming techniques, smart agriculture has the benefit of maximizing resource use through precise chemical input application and regulation of environmental factors like temperature and humidity. Farmers may make data-driven choices about the possibility of insect invasion, natural disasters, anticipated yields, and even prospective market shifts with the use of smart farming tools. The technical foundation of smart agriculture serves as a potential response to worries about food security. It is made up of wireless sensor networks and integrated cloud computing modules inside IoT.

• Journal of Sensor Science and Technology
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• v.33 no.1
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• pp.30-33
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• 2024

The occurrence of harmful algae on the coast of Korea has been a cause of damage to the aquaculture industry and deterioration of the coastal ecosystem environment. A method is required to predict their outbreak in real-time at the site. Therefore, this study attempted to develop a small hybrid optical sensor and real-time monitoring system based on LiDAR that can be used in the field and laboratory and can be applied to various platforms. FMS-L specifically suggested the amount of Chlorophyll a (Chl a) in the sample by measuring and analyzing the fluorescence emitted by the irradiating light. The accuracy of FMS-L was verified by measuring the concentrations of standard Chlorophyll a substances and Margalfidinium polykirkoids. In addition, the precision was verified by comparing the measurement results of FMS-L using commercial equipment Phyto-PAM-II. This equipment is compact and easy to move. Therefore, it can be easily applied to field surveys, allows short time measurements (10 s), and can be applied at a distance of 10 m from the measurement site.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.37-47
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• 2024

This study presents the results of designing a system that determines the location of a person in an indoor environment based on a single IMU sensor attached to the tip of a person's shoe in an area where GPS signals are inaccessible. By adjusting for human footfall, it is possible to accurately determine human location and trajectory by correcting errors originating from the Inertial Measurement Unit (IMU) combined with advanced machine learning algorithms. Although there are various techniques to identify stepping, our study successfully recognized stepping with 98.7% accuracy using an artificial intelligence model known as Long Short-Term Memory (LSTM). Drawing upon the enhancements in our methodology, this article demonstrates a novel technique for generating a 200-meter trajectory, achieving a level of precision marked by a 2.1% error margin. Indoor pedestrian navigation systems, relying on inertial measurement units attached to the feet, have shown encouraging outcomes.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.23 no.8
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• pp.593-600
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• 2010

In this paper, High brightness LED (light-emitting diodes) driver IC (integrated circuit) using new current sensing circuit is proposed. This LED driver IC can provide a constant current with high current precision over a wide input voltage range. The proposed current-sensing circuit is composed of a cascode current sensor and a current comparator with only one reference voltage. This IC minimizes the voltage stress of the MOSFET (metal oxide semiconductor field effect transistor) from the maximum input voltage and has low power consumption and chip area by using simple-structured comparator and minimum bias current. To confirm the functioning and characteristics of our proposed LED driver IC, we designed a buck converter. The LED current ripple of the designed IC is in ${\pm}5%$ and a tolerance of the average LED current is lower than 2.43%. This shows much improved feature than the previous method. Also, protections for input voltage and operating temperature are designed to improve the reliability of the designed IC. Designed LED driver IC uses 1.0 ${\mu}m$ X-Fab. BiCMOS process parameters and electrical characteristics and functioning are verified by spectre (Cadence) simulation.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.7
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• pp.585-590
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• 2014

Recently, monitoring systems, such as POP, take a core role in scheduling or planning of manufacturing facilities for production, maintenance, and so on. Such monitoring systems require functionalities for real-time parameter monitoring and controlling to maximize efficiency of facilities. However, vendors usually do not provide internal communication protocols or interface to access the machine controller. Therefore, the values of parameters related to machine operations and controls cannot be easily accessed from external devices. In this paper, we propose an interface methodology for a real-time monitoring and controlling of injection molding machine parameters such as user input parameters, embedded sensor data and injection molding status information.

• Journal of the Korean Society for Precision Engineering
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• v.34 no.3
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• pp.179-184
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• 2017

Recently, traffic accidents and damage on the highway have increased because of overloaded vehicles. The existing overload-detecting system has a low accuracy rate. An overload-detecting system using a weigh-in-motion (WIM) system has been developed to solve this problem. The WIM system can be used to detect overloaded vehicles by measuring the weight of the vehicles. The WIM system is divided into high-speed and low-speed types. The inaccuracy rate in the low-speed WIM system results mainly from the low response rate of the sensor when the velocity is moving at more than 20 km/h. In this study, a low-speed overload-detecting pad with a hydraulic structure using a WIM system was developed to make the system more accurate. The structural and formal analysis was carried out by using a finite element method (FEM) in order to analyze the structural stability and the extrusion velocity of the system. In addition, a static load test was performed to confirm the linearity and accuracy of the pad.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.10
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• pp.851-856
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• 2015

This study aimed to develop a sensory feedback system which could measure force and temperature for the user of myoelectric prosthetic hands. The Sensory measurement module consisted of a force sensing resistor to measure forces and non-contact infrared temperature sensor. These sensors were attached on the fingertips of the myoelectric prosthetic hand. The module was validated by using standard weights corresponding to external force and a Peltier module. Sensory transmission module consisted of four vibration motors. Eight vibration patterns were generated by combining motion of each vibration motor and were dependent on kinds and/or magnitude. The module was verified by using standard weigts and water at varying temperatures. There were correlations of force and temperature between the sensory measurement module and standard weight and water. Additionally, exact vibration patterns were generated, indicating the efficacy of the sensory feedback system for the myoelectric prosthetic hand.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.2
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• pp.1-7
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• 2018

Recently, as interest in the internet of things has increased, a vibration energy harvester has attracted attention as a power supply method for a wireless sensor. The vibration energy harvester can be divided into piezoelectric types, electromagnetic type and electrostatic type, according to the energy conversion type. The electromagnetic vibration energy harvester has advantages, in terms of output density and design flexibility, compared to other methods. The efficiency of an electromagnetic vibration energy harvester is determined by the shape, size, and spacing of coils and magnets. Generating all the experimental cases is expensive, in terms of time and money. This study proposes a method to perform design optimization of an electromagnetic vibration energy harvester using an open source, big data platform.