• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.157-161
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• 2010

Most of air pollution in a metropolis is the result of exhaust gas emissions from automotive vehicles, and the world-wide regulation against environmental pollution is becoming more strict. Moreover the demand on development and supply of an environment-friendly automobile is increasing and the market share about that is expected to grow rapidly in this time of high oil price. The secondary batteries the most important component to store the electrical energy in hybrid electric vehicle. It needs to the higher power characteristics to emit the energy instantaneous. In this paper, we proposed the system to monitor reliably the charge and discharge states of the secondary batteries for hybrid electric vehicle. The material is about SW and HW module the software and hardware module mounted on the charge and discharge system and the monitoring system to control the charge and discharge performance effectively.

• Biomedical Engineering Letters
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• v.8 no.4
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• pp.365-371
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• 2018

Uninterrupted monitoring of multiple subjects is required for mass causality events, in hospital environment or for sports by medical technicians or physicians. Movement of subjects under monitoring requires such system to be wireless, sometimes demands multiple transmitters and a receiver as a base station and monitored parameter must not be corrupted by any noise before further diagnosis. A Bluetooth Piconet network is visualized, where each subject carries a Bluetooth transmitter module that acquires vital sign continuously and relays to Bluetooth enabled device where, further signal processing is done. In this paper, a wireless network is realized to capture ECG of two subjects performing different activities like cycling, jogging, staircase climbing at 100 Hz frequency using prototyped Bluetooth module. The paper demonstrates removal of baseline drift using Fast Fourier Transform and Inverse Fast Fourier Transform and removal of high frequency noise using moving average and S-Golay algorithm. Experimental results highlight the efficacy of the proposed work to monitor any vital sign parameters of multiple subjects simultaneously. The importance of removing baseline drift before high frequency noise removal is shown using experimental results. It is possible to use Bluetooth Piconet frame work to capture ECG simultaneously for more than two subjects. For the applications where there will be larger body movement, baseline drift removal is a major concern and hence along with wireless transmission issues, baseline drift removal before high frequency noise removal is necessary for further feature extraction.

• Journal of Sensor Science and Technology
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• v.28 no.5
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• pp.311-317
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• 2019

Rotating devices are commonly installed in power plants and factories. This study proposes a self-powered sensor node that is powered by converting the vibration energy of a rotating device into electrical energy. The self-powered sensor consists of a piezoelectric harvester for self-power generation, a rectifier circuit to rectify the AC signal, a sensor unit for measuring the vibration frequency, and a circuit to control the light emitting diode (LED) lighting. The frequency of the vibration source was measured using a piezoelectric-cantilever-type vibration frequency sensor. A green LED was illuminated when the measured frequency was within the normal range. The power generated by the piezoelectric harvester was determined, and the LED operation was assessed in terms of the vibration frequency. The piezoelectric harvester was found to generate a power of 3.061 mW or greater at a vibration acceleration of 1.2 g ($1g=9.8m/s^2$) and vibration frequencies between 117 and 123 Hz. Notably, the power generated was 4.099 mW at 122 Hz. As such, our self-powered sensor node can be used as a module for monitoring rotating devices, because it can convert vibration energy into electrical energy when installed on rotating devices such as air compressors.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.69-77
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• 2019

Today, most of elevators have an emergency call facility for emergency situations. However, if the network installed in the elevator is also out of power, it cannot be used for the elevator remote monitoring and management. So, we develop an integrated and unified emergency call system, which can transmit not only telephone call but also data signals using PSTN(Public Switched Telephone Network) in order to remote monitoring and management of elevators, even though a power outage occurs. The proposed integrated emergency call system to process multiple data such as voice and operational information is a multi-channel board system which is composed of an emergency phone signal processing module and an operational information processing module in the control box of elevator. In addition, the RMS(remote management server) systems based on the Web consist of a dial-up server and a remote monitoring server where manages the elevator's operating information, status records, and operational faults received via the proposed integrated and unified emergency call system in real time. So even if there's a catastrophic emergency, the proposed RMS systems shall ensure and maintain the safety of passengers inside the elevator. Also, remote control of the elevator by this system should be more efficient and secure. In near future, all elevator emergency call system need to support multifunctional capabilities to transmit operational data as well as phone calls for the safety of passengers. In addition, for safer elevators, it is necessary to improve them more efficiently by combining them with high-tech technologies such as the Internet of Things and artificial intelligence.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.4
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• pp.183-189
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• 2021

In recent years, active research has been devoted toward developing a monitoring system using ambient vibration data in order to quantitatively determine the deterioration occurring in a structure over a long period of time. This study developed a low-cost edge computing system that detects the abnormalities in structures by utilizing the dynamic characteristics acquired from the structure over the long term for ensemble learning. The system hardware consists of the Raspberry Pi, an accelerometer, an inclinometer, a GPS RTK module, and a LoRa communication module. The structural abnormality detection afforded by the ensemble learning using dynamic characteristics is verified using a laboratory-scale structure model vibration experiment. A real-time distributed processing algorithm with dynamic feature extraction based on the experiment is installed on the Raspberry Pi. Based on the stable operation of installed systems at the Community Service Center, Pohang-si, Korea, the validity of the developed system was verified on-site.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.743-754
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• 2022

This paper contains the results of the development and performance evaluation of the environmental data monitoring system for the fish farm. For the hardware development, the analogue sensor is used to collect dissolved oxygen, pH, salinity, and temperature of the fish farm water, and the digital sensor is used for collecting ambient temperature, humidity, and location information via a GPS module to be sent to cloud-based Firebase DB. A set of LoRa transmitters and receivers is used as a communication module to upload the collected data. The data stored in Firebase is retrieved as a graph on a web and mobile application to monitor the environmental data changes in real-time. A notification will be delivered if the collected data is outside the determined optimal value. To evaluate the performance of the developed system, a response time from hardware modules to web and mobile applications is ranging from 6.2 to 6.85 seconds, which indicates satisfactory results.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.1
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• pp.108-117
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• 2016

In this paper, a portal system compatible with MRV regulation was designed to monitoring, reporting and verifying $CO_2$ emission and fuel consumption data from an international ship. A portal system supports monitoring and reporting task of international shipping companies and calculates national greenhouse gas inventory. EU MRV law, MRV discussions of IMO, responses of international shipping companies to ship energy efficiency and greenhouse gas regulation, and greenhouse gas statistics on international shipping were analyzed to drive portal system requirements. For ship energy efficiency and $CO_2$ emitted monitoring, a data collection module was designed based on on-board equipment, energy efficiency measuring device and navigation report. Data transfer module with easy management and minimized usage to transfer ship data to shore was designed. A portal system was designed to convert the collected data into the standard reporting format, perform monitoring, statical analysis, verification and auto report generation, and support national greenhouse gas inventory.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.375-383
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• 2011

Recent advances in digital technology and diversified internet services have resulted in a rapid growth of research on monitering systems using embedded web servers in USN systems. In designing USN systems equipped with wireless sensor modules requiring extra power for heating sensors for their appropriate operations, excessive power consumption introduces inefficiency to the entire system. In this paper, using embedded systems in web environment, we develop a remote-monitoring system with VOC (Volatile Organic Compounds) sensor signal, and propose a real time method of processing sensor-data streams by way of the serial bus from the sensor module in the USN system. The proposed system has an advantage of monitering the harmful gases on real-time basis and can be used semi-permanently by providing the sensor module with power through the serial bus. The harmful gas to be detected by the VOC sensor module is Toluene and the sensor module is composed of TGS-2602 VOC(Volatile Organic Compounds) sensors of FIGARO. The detected signal is transferred to the embedded web server using the RS-485 serial communication device. The proposed remote VOC monitering system is designed to coordinate in such a way that the VOC sensor module and embedded web server (EMPOS-II) work together effectively for real time monitering of harmful gases on the web at any places where the internet is connected.

• Journal of Biosystems Engineering
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• v.28 no.6
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• pp.511-516
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• 2003

Computer vision technology has been utilized as one of the most powerful tools to automate various agricultural operations. Though it has demonstrated successful results in various applications, the current status of technology is still for behind the human's capability typically for the unstructured and variable task environment. In this paper, a man-machine interactive hybrid decision-making system which utilized a concept of tole-operation was proposed to overcome limitations of computer image processing and cognitive capability. Tasks of greenhouse watermelon cultivation such as pruning, watering, pesticide application, and harvest require identification of target object. Identifying water-melons including position data from the field image is very difficult because of the ambiguity among stems, leaves, shades. and fruits, especially when watermelon is covered partly by leaves or stems. Watermelon identification from the cultivation field image transmitted by wireless was selected to realize the proposed concept. The system was designed such that operator(farmer), computer, and machinery share their roles utilizing their maximum merits to accomplish given tasks successfully. And the developed system was composed of the image monitoring and task control module, wireless remote image acquisition and data transmission module, and man-machine interface module. Once task was selected from the task control and monitoring module, the analog signal of the color image of the field was captured and transmitted to the host computer using R.F. module by wireless. Operator communicated with computer through touch screen interface. And then a sequence of algorithms to identify the location and size of the watermelon was performed based on the local image processing. And the system showed practical and feasible way of automation for the volatile bio-production process.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.2
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• pp.85-92
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• 2023

Respiratory infections such as COVID-19 mainly occur within enclosed spaces. The presence or absence of abnormal symptoms of respiratory infectious diseases is judged through initial symptoms such as fever, cough, sneezing and difficulty breathing, and constant monitoring of these early symptoms is required. In this paper, image matching correction was performed for the RGB camera module and the thermal imaging camera module, and the temperature of the thermal imaging camera module for the measurement environment was calibrated using a blackbody. To detection the target recommended by the standard, a deep learning-based object recognition algorithm and the inner canthus recognition model were developed, and the model accuracy was derived by applying a dataset of 100 experimenters. Also, the error according to the measured distance was corrected through the object distance measurement using the Lidar module and the linear regression correction module. To measure the performance of the proposed model, an experimental environment consisting of a motor stage, an infrared thermography temperature screening system and a blackbody was established, and the error accuracy within 0.28℃ was shown as a result of temperature measurement according to a variable distance between 1m and 3.5 m.