• Title/Summary/Keyword: National monitoring

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Applications of Drones for Environmental Monitoring of Pollutant-Emitting Facilities

  • Son, Seung Woo;Yu, Jae Jin;Kim, Dong Woo;Park, Hyun Su;Yoon, Jeong Ho
    • Proceedings of the National Institute of Ecology of the Republic of Korea
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    • v.2 no.4
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    • pp.298-304
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    • 2021
  • This study aimed to determine the applicability of drones and air quality sensors in environmental monitoring of air pollutant emissions by developing and testing two new methods. The first method used orthoimagery for precise monitoring of pollutant-emitting facilities. The second method used atmospheric sensors for monitoring air pollutants in emissions. Results showed that ground sample distance could be established within 5 cm during the creation of orthoimagery for monitoring emissions, which allowed for detailed examination of facilities with naked eyes. For air quality monitoring, drones were flown on a fixed course and measured the air quality in point units, thus enabling mapping of air quality through spatial analysis. Sensors that could measure various substances were used during this process. Data on particulate matter were compared with data from the National Air Pollution Measurement Network to determine its future potential to leverage. However, technical development and applications for environmental monitoring of pollution-emitting facilities are still in their early stages. They could be limited by meteorological conditions and sensitivity of the sensor technology. This research is expected to provide guidelines for environmental monitoring of pollutant-emitting facilities using drones.

Assessment of a smartphone-based monitoring system and its application

  • Ahn, Hoyong;Choi, Chuluong;Yu, Yeon
    • Korean Journal of Remote Sensing
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    • v.30 no.3
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    • pp.383-397
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    • 2014
  • Information technology advances are allowing conventional surveillance systems to be combined with mobile communication technologies, creating ubiquitous monitoring systems. This paper proposes monitoring system that uses smart camera technology. We discuss the dependence of interior orientation parameters on calibration target sheets and compare the accuracy of a three-dimensional monitoring system with camera location calculated by space resectioning using a Digital Surface Model (DSM) generated from stereo images. A monitoring housing is designed to protect a camera from various weather conditions and to provide the camera for power generated from solar panel. A smart camera is installed in the monitoring housing. The smart camera is operated and controlled through an Android application. At last the accuracy of a three-dimensional monitoring system is evaluated using a DSM. The proposed system was then tested against a DSM created from ground control points determined by Global Positioning Systems (GPSs) and light detection and ranging data. The standard deviation of the differences between DSMs are less than 0.12 m. Therefore the monitoring system is appropriate for extracting the information of objects' position and deformation as well as monitoring them. Through incorporation of components, such as camera housing, a solar power supply, the smart camera the system can be used as a ubiquitous monitoring system.

Laboratory Environment Monitoring: Implementation Experience and Field Study in a Tertiary General Hospital

  • Kang, Seungjin;Baek, Hyunyoung;Jun, Sunhee;Choi, Soonhee;Hwang, Hee;Yoo, Sooyoung
    • Healthcare Informatics Research
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    • v.24 no.4
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    • pp.371-375
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    • 2018
  • Objectives: To successfully introduce an Internet of Things (IoT) system in the hospital environment, this study aimed to identify issues that should be considered while implementing an IoT based on a user demand survey and practical experiences in implementing IoT environment monitoring systems. Methods: In a field test, two types of IoT monitoring systems (on-premises and cloud) were used in Department of Laboratory Medicine and tested for approximately 10 months from June 16, 2016 to April 30, 2017. Information was collected regarding the issues that arose during the implementation process. Results: A total of five issues were identified: sensing and measuring, transmission method, power supply, sensor module shape, and accessibility. Conclusions: It is expected that, with sufficient consideration of the various issues derived from this study, IoT monitoring systems can be applied to other areas, such as device interconnection, remote patient monitoring, and equipment/environmental monitoring.

Improving National Curriculum Monitoring System (국가 교육과정 모니터링 체제 개선 연구)

  • Lee, Keunho;Lee, Byeongcheon;Ka, Euna;Lee, Jooyoun
    • The Journal of the Korea Contents Association
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    • v.16 no.2
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    • pp.588-599
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    • 2016
  • This study aims to provide suggestions for improving national curriculum monitoring system. To achieve this goal, we analyzed the Korean national curriculum monitoring system in terms of actual problems and challenges faced by school teachers, and drew criteria for analyzing overseas curriculum monitoring system. Based on the criteria, we investigated the Australian and Singaporean national curriculum monitoring system. We especially carried out interviews with school teachers, principals, officials in Ministry of Education, and tried to identify the actual condition of curriculum monitoring system beyond superficial investigation of them. The results of this study provide four suggestions such as integrated way of monitoring, multi-way open system, and substantial approach into monitoring operation which will lead into meeting with the purpose of the monitoring system of national curriculum.

Suggestions on the Selection Method of Priority Monitoring Sites for Hazardous Air Pollutants in Megacities (유해대기오염물질 모니터링을 위한 대도시 우선순위 측정지점 선정기법 제안)

  • Kwon, Hye-Ok;Kim, Seong-Joon;Kim, Yong Pyo;Kim, Sang-Kyun;Hong, Ji-Hyung;Choi, Sung-Deuk
    • Journal of Korean Society for Atmospheric Environment
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    • v.33 no.6
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    • pp.544-553
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    • 2017
  • There is an overall guideline of the installation of air quality monitoring stations in Korea, but specified steps for the selection of monitoring sites for hazardous air pollutants(HAPs) are not provided. In this study, we proposed a systematic method for the selection of monitoring sites for HAPs using geographic information system (GIS). As a case study, the Seoul metropolitan area (Seoul, Incheon, and Gyeonggi Province) was chosen, and 15 factors including population, vehicle registration, and emission data were compiled for each grid cell ($7km{\times}7km$). The number of factors above the top 30% of individual data for each grid cell was used to select priority monitoring sites for HAPs. In addition, several background sites were added for data comparison and source identification. Three scenarios were suggested: Scenario 1 with 7 sites, Scenario 2 with 17 sites, and Scenario 3 with 30 sites. This proposal is not the final result for an intensive monitoring program, but it is an example of method development for selecting appropriate sampling sites. These results can be applied not only to HAPs monitoring in megacities but also to the national HAPs monitoring network.

Dual Monitoring with Stump Pressure and Electroencephalography During Carotid Endarterectomy

  • Chang, Jee Won;Kim, Su Wan;Lee, Seogjae;Lee, Jonggeun;Ku, Min Jung
    • Journal of Chest Surgery
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    • v.50 no.2
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    • pp.94-98
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    • 2017
  • Background: Intraoperative monitoring during carotid endarterectomy is crucial for cerebral protection. We investigated the results of carotid endarterectomy under dual monitoring with stump pressure and electroencephalography. Methods: We retrospectively reviewed the medical records of 50 patients who underwent carotid endarterectomy between March 2010 and February 2016. We inserted a temporary shunt if the stump pressure was lower than 35 mm Hg or if any intraoperative change was observed on electroencephalography. Results: Seventeen (34%) patients used a temporary shunt, and the mean stump pressure was 26.8 mm Hg in the shunt group and 46.5 mm Hg in the non-shunt group. No postoperative mortality or bleeding occurred. Postoperatively, there were 3 cases (6%) of minor stroke, all of which took place in the shunt group. A comparison of the preoperative and the intraoperative characteristics of the shunt group with those of the non-shunt group revealed no statistically significant difference between the 2 groups (p<0.01). Conclusion: Dual monitoring with stump pressure and electroencephalography was found to be a safe and reliable monitoring method with results comparable to those obtained using single monitoring. Further study should be performed to investigate the precise role of each monitoring method.

A Study on Real Time Cutting Monitoring using Profibus (프로피버스 통신을 이용한 실시간 절삭 상태 모니터링에 관한 연구)

  • Yoon, Sang-Hwan;Cho, Sang-pil;Lyu, Sung-gi
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.15 no.3
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    • pp.1-7
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    • 2016
  • The cutting processes used for monitoring engineering includes analysis and feedback about strange conditions, tools collision and tools wear in real time, for improving the working ratio of equipment and productivity. In this study, we proposed monitoring using profibus to increase the reliability as the most important factor for cutting monitoring. The profibus can increase the reliability of cutting monitoring for cutting torque of a main spindle motor and a feed motors through PLC-based interface.

Development of Wireless Monitoring System for Layers Rearing in Multi-tier Layers Battery by Machine Vision (기계시각을 이용한 고단 직립식 산란계 케이지의 무선 감시시스템 개발)

  • Lim, Song-Su;Chang, Dong-Il;Lee, Seung-Joo;So, Jae-Kwang
    • Journal of Biosystems Engineering
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    • v.32 no.3
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    • pp.173-178
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    • 2007
  • This research was conducted to develop and analyze a wireless monitoring system for judging if sick or dead layers (SDL) exist in multi-tier layers battery (MLB) by machine vision, and to evaluate the performance between a wired monitoring system and it. This study used the AP (Access Point), the RS-285 to RS-232 converter, RS-232 to Ethernet converter, PICBASIC board and upgraded lump image processing method to change wired monitoring system into wireless monitoring system. The system was tested at a pilot farm and farm layer house. Results showed that monitoring judgement success rate at a pilot farm on normal cage (without SDL) was 82.3% and that on abnormal cage (with SDL) was 87.5%, respectively. And communication performance test results showed at farm layer house was $700{\sim}900$ kbps while equipments operated. There were dropped slightly than performance of wired monitoring system, however, the quantity was too small to make a significant difference of performance of the controling system developed for wireless communication.

A Machine Learning-based Real-time Monitoring System for Classification of Elephant Flows on KOREN

  • Akbar, Waleed;Rivera, Javier J.D.;Ahmed, Khan T.;Muhammad, Afaq;Song, Wang-Cheol
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.8
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    • pp.2801-2815
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    • 2022
  • With the advent and realization of Software Defined Network (SDN) architecture, many organizations are now shifting towards this paradigm. SDN brings more control, higher scalability, and serene elasticity. The SDN spontaneously changes the network configuration according to the dynamic network requirements inside the constrained environments. Therefore, a monitoring system that can monitor the physical and virtual entities is needed to operate this type of network technology with high efficiency and proficiency. In this manuscript, we propose a real-time monitoring system for data collection and visualization that includes the Prometheus, node exporter, and Grafana. A node exporter is configured on the physical devices to collect the physical and virtual entities resources utilization logs. A real-time Prometheus database is configured to collect and store the data from all the exporters. Furthermore, the Grafana is affixed with Prometheus to visualize the current network status and device provisioning. A monitoring system is deployed on the physical infrastructure of the KOREN topology. Data collected by the monitoring system is further pre-processed and restructured into a dataset. A monitoring system is further enhanced by including machine learning techniques applied on the formatted datasets to identify the elephant flows. Additionally, a Random Forest is trained on our generated labeled datasets, and the classification models' performance are verified using accuracy metrics.