• Korean Journal of Ecology and Environment
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• v.38 no.spc
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• pp.76-83
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• 2005

The marked increase in the number of environmental problems, combined with the increase in their intensity and spatial extent, has resulted in an ever-increasing need for constant monitoring. This is complicated by the occurrence of new and complicated environmental issues that often prevent a thorough understanding of the entire monitoring framework. In the present study, a diagrammatic method was developed to present the entire framework of a monitoring plan. The diagram was separated into three sections- "Problem Section", "Research Process and Data Section" and "Entities Section" - to clearly present the disparate relationships between monitoring objectives and the monitoring procedure. Notation of the diagrams was undertaken using Unified Modeling Language (UML). A hypothetical monitoring plan for an environmental problem was designed to assess usefulness of the diagrammatic method. The diagram was capable of reviewing and revising the monitoring plan and could be used to select a monitoring procedure according to the monitoring objectives of the plan. The results suggested that this diagrammatic method was effective for designing an appropriate monitoring plan for a given monitoring objective.

• Journal of Environmental Impact Assessment
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• v.4 no.3
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• pp.31-39
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• 1995

Environmental Impact Assessment (EIA) is composed of various procedures, such as screening, scoping, inventory survey, prediction, assessment, alternative assessment, mitigation measures, and post management. Environmental monitoring data for air quality or water quality, etc. is applied in the EIA process, especially in prediction and post management. As an effective tool of environmental monitoring, the remote sensing method, introduced recently, was used in collecting nationwide data concerning ecosystem and land use. This article explains the current monitoring status in Korea. Monitoring factors include air quality, water quality, soil, ocean, odor, noise, and ecosystems. This report explains the organization of the environmental monitoring system managed by the Ministry of Environment in Korea. Furthermore, it shows the environmental criteria and environmental policies applied to EIA in Korea.

• Smart Structures and Systems
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• v.17 no.4
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• pp.669-690
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• 2016

Advances in sensor technologies have led to the instrumentation of sensor networks for bridge monitoring and management. For a dense sensor network, enormous amount of sensor data are collected. The data need to be managed, processed, and interpreted. Data management issues are of prime importance for a bridge management system. This paper describes a data management infrastructure for bridge monitoring applications. Specifically, NoSQL database systems such as MongoDB and Apache Cassandra are employed to handle time-series data as well the unstructured bridge information model data. Standard XML-based modeling languages such as OpenBrIM and SensorML are adopted to manage semantically meaningful data and to support interoperability. Data interoperability and integration among different components of a bridge monitoring system that includes on-site computers, a central server, local computing platforms, and mobile devices are illustrated. The data management framework is demonstrated using the data collected from the wireless sensor network installed on the Telegraph Road Bridge, Monroe, MI.

• Hwankyungkyoyuk
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• v.10 no.2
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• pp.311-324
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• 1997

General citizens can be a valuable resource for various types of environmental monitoring when they are well-trained and managed. Successful use of volunteer monitors depends on understanding that citizens are partners sharing expanded roles as the guardians of their local environment. Citizen volunteer monitoring programs are developed for three reasons: 1) to supplement environmental data collected by professional staffs in governmental agencies and scientific institutions; 2) to educate the public about local environmental problems; 3) to build a constituency of citizen to practice sound environmental management at a local level and build public support for environmental protection. All three goals can be achieved with a well-organized program which provides useful and credible data. Initial step in planning a successful volunteer monitoring project is to clearly identify the use to be made of the data. Technical advice from the identified potential user groups should be convened early in the planning stage to refine the program objectives and determine if volunteers can provide the level of expertise required. Data users must have confidence in the representativeness, consistency, and accuracy of data collected by volunteers. Effective quality assurance and quality control(QA/QC) procedures are essential to ensure the utility of environmental monitoring data. Volunteers must be trained in advance to carry out specific environmental monitoring tasks. Another components of successful volunteer monitoring programs is to give the volunteers praise and feedback as well as to encourage experienced volunteers to impose increased responsibilities. The increase of volunteer monitoring programs in Korea will play a major role in developing a participatory system in which the people are "empowered" to make decisions and make a difference.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.171-178
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• 2017

Data mashup is a web technology that combines information from multiple sources into a single web application. Mashup applications create a new horizon for new services, like environmental monitoring. Environmental monitoring is a serious tool for the state and private organizations, which are located in regions with environmental hazards and seek to gain insights to detect hazards and locate them clearly. These organizations utilize a data mashup to merge datasets from different Internet of multimedia things (IoMT) context-based services in order to leverage its data analytics performance and the accuracy of the predictions. However, mashup different datasets from multiple sources is a privacy hazard as it might reveal citizens specific behaviors in different regions. The ability to preserve privacy in mashuped datasets and at the same time provide accurate insights becomes a key success for the spread of mashup services. In this paper, we present our efforts to build a fog-based middleware for private data mashup (FMPM) to serve a centralized environmental monitoring service. The proposed middleware is equipped with concealment mechanisms to preserve the privacy of the merged datasets from multiple IoMT networks involved in the mashup application. Also, these mechanisms preserve the aggregates in the dataset to maximize the usability of information to attain accurate analytical results. We also provide a scenario for IoMT-enabled data mashup service and experimentation results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1097-1100
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• 2003

Data Loggers for environmental monitoring are mostly dispersion in installation and systems located at long distance from monitoring system. And, it requests mostly flexible functions and high performances. that can fit to various sensor inputs, sensor interfaces and conditions or system working. In this research, we developed the micro controller based Data Logger with minimum hardware construction that allows the higher flexibility of application. Finally, we developed software function for water quality monitoring and tested in real system launched at Han river.

• Smart Structures and Systems
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• v.12 no.2
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• pp.209-233
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• 2013

With an annual growth rate of about 30%, wind energy systems, such as wind turbines, represent one of the fastest growing renewable energy technologies. Continuous structural health monitoring of wind turbines can help improving structural reliability and facilitating optimal decisions with respect to maintenance and operation at minimum associated life-cycle costs. This paper presents an integrated monitoring system that is designed to support structural assessment and life-cycle management of wind turbines. The monitoring system systematically integrates a wide variety of hardware and software modules, including sensors and computer systems for automated data acquisition, data analysis and data archival, a multiagent-based system for self-diagnosis of sensor malfunctions, a model updating and damage detection framework for structural assessment, and a management module for monitoring the structural condition and the operational efficiency of the wind turbine. The monitoring system has been installed on a 500 kW wind turbine located in Germany. Since its initial deployment in 2009, the system automatically collects and processes structural, environmental, and operational wind turbine data. The results demonstrate the potential of the proposed approach not only to ensure continuous safety of the structures, but also to enable cost-efficient maintenance and operation of wind turbines.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.6
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• pp.648-660
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• 2012

Reliable response measurements are extremely important for proper bridge health monitoring but incomplete and unreliable data may be acquired due to sensor problems and environmental effects. In the case of a sensor malfunction, parts of the measured data can be missing so that the structural health condition cannot be monitored reliably. This means that the dynamic characteristics of natural frequencies can change as if the structure is damaged due to environmental effects, such as temperature variations. To overcome these problems, this paper proposes a systematic procedure of data analysis to recover missing data and eliminate the environmental effects from the measured data. It also proposes a health index calculated statistically using revised data to evaluate the health condition of a bridge. The proposed method was examined using numerically simulated data with a truss structure and then applied to a set of field data measured from a cable-stayed bridge.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.349-356
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• 2022

Currently, the agricultural population in Korea indicates a decreasing and aging orientation. As the population of farm labor continues to decline, so farmers are feeling the pressure to be stable crop production. To solve the problem caused by the decreasing of farm labor, it is necessary to change over to "Digital agriculture". Digital agriculture is tools that digitally collect, store, analyze, and share electronic data and/or information in agriculture, and aims to integrate the several digital technologies into crop and livestock management and other processes in agriculture fields. In addition, digital agriculture can offer the opportunity to increase crop production, save costs for farmer. Therefore, in this study, for data-based Digital Agriculture, a greenhouse environment monitoring system for crop growth monitoring based on Node-RED, which even beginners can use easily, was developed, and the implemented system was verified in a hydroponic greenhouse. Several sensors, such as temperature, humidity, atmospheric pressure, CO₂, solar radiation, were used to obtain the environmental data of the greenhouse. And the environmental data were processed and visualized using Node-RED and MariaDB installed in rule.box digital. The environment monitoring system proposed in this study was installed in a hydroponic greenhouse and obtained the environmental data for almost two weeks. As a result, it was confirmed that all environmental data were obtained without data loss from sensors. In addition, the dashboard provides the names of installed sensors, real time environmental data, and changes in the last three days for each environmental data. Therefore, it is considered that farmers will be able to easily monitor the greenhouse environment using the developed system in this study.

• Journal of Multimedia Information System
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• v.3 no.3
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• pp.63-68
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• 2016

Environmental downtime produces a significant cost to organizations and makes them unable to do business because what happens in the data center affects everyone. In addition, the amount of electrical energy consumed by data centers increases with the amount of computing power installed. Installation of physical Information Technology and facilities related to environmental concerns, such as monitoring temperature, humidity, power, flood, smoke, air flow, and room entry, is the most proactive way to reduce the unnecessary costs of expensive hardware replacement or unplanned downtime and decrease energy consumed by servers. In this paper, we present remote system for monitoring datacenter implementing using open-source hardware platforms; Arduino, Raspberry Pi, and the Gobetwino. The sensed data displayed through Arduino are transferred using Gobetwino to the nearest host server such as temperature, humidity and distance every time an object hitting another object or a person coming in entrance. The raspberry Pi records the sensed data at the remote location. The objective of collecting temperature and humidity data allows monitoring of the server's health and getting alerts if things start to go wrong. When the temperature hits $50^{\circ}C$, the supervisor at remote headquarters would get a SMS, and then they would take appropriate actions to reduce electrical costs and preserve functionality of servers in data centers.