표제지
국문 요약
목차
제1장 서론 18
1. 연구 배경 및 필요성 18
2. 연구 목적 21
제2장 연구방법 22
1. 연구흐름도 22
2. 자료 수집 및 분석 24
2.1. Personal Oriented Modeling (POM) 24
2.2. 환경오염인자의 실시간 측정 27
2.3. 개인 위치 추적 33
2.4. 일일 평균 노출량(Average Daily Dose : ADD) 37
2.5. 존재인구 데이터 39
2.6. Inverse Distance Weighted (IDW) 42
3. 시스템 개발 설계 44
3.1. 시스템 구성도 44
3.2. DataBase 설계 47
3.3. 알고리즘 설계 48
제3장 연구결과 49
1. 자료 수집 및 분석 49
1.1. 환경유해인자의 실시간 측정 데이터 시스템 49
1.2. 개인 위치 추적 시스템 52
1.3. 존재인구 데이터 시스템 55
1.4. IDW 적용 시스템 58
1.5. 알고리즘 적용 64
2. 시스템 개발 결과 66
2.1. 시스템 구현도 66
2.2. 개인 노출량 산정 시스템 74
2.3. 집단 노출량 산정 시스템 79
제4장 고찰 83
1. 연구 자료 및 방법에 대한 고찰 83
2. 연구 결과에 대한 고찰 84
2.1. 개인 위해성 평가 84
2.2. 집단 위해성 평가 86
제5장 결론 89
참고문헌 91
Abstract 109
〈Table 2-1〉 Standards for equivalence evaluation test for PM2.5 automatic measuring instrument. 28
〈Table 2-2〉 Recent Development Equipment Comparison Individual Exposure to PM₂.₅ 31
〈Table 2-3〉 Specification of the system hardware. 45
〈Table 2-4〉 Real-time based envicnmental hazadous factor concentraion. 47
〈Table 2-5〉 GPS tracker data structure from device. 47
〈Table 2-6〉 Personal location based concentration in Database system. 47
〈Table 3-7〉 GPS Tracker data per 10 minutes. 53
〈Table 3-8〉 Population data with age/sex/grid. 55
〈Table 3-9〉 Distance weight change without station ②. 61
〈Table 3-10〉 Results of IDW performance test. 63
〈Table 3-11〉 TTA test results for TTA system performance evaluation. 73
〈Table 2-12〉 Comparison of exposure levels with receptor location. 78
〈Table 3-13〉 Comparison of the existing population for the first Monday of April 2020 and 2021. 80
〈Table 4-14〉 AI-based high-resolution concentration data status. 86
〈Figure 2-1〉 The research flow chart is to implement the exposure estimation system through literature research, data collection and... 23
〈Figure 2-2〉 Flow chart of Personal Oriented Modelingfor the complete framework consisting of four loops: uncertainty, individual,... 25
〈Figure 2-3〉 Framework for personal exposure assessment and usage of highly resolved temporal data. 26
〈Figure 2-4〉 Block diagram: the detailed module for fine dust measurement. 27
〈Figure 2-5〉 A product corresponding to the performance certification grade 1 was used for PM2.5. 28
〈Figure 2-6〉 Performance evaluation of the 16 ch. the instrumemt Dust Monitor compared with the Grimm Dust Monitor. 29
〈Figure 2-7〉 The data of PM₂.₅ meter is transmitted to the server according to the defined protocol and stored in the DB. 30
〈Figure 2-8〉 RTI's MicroPEM was used to compare and analyze the results of the system. 32
〈Figure 2-9〉 Placement of exposure and accelerometric sensors on an adult during scripted testing, with the Oxycon Mobile face mask for... 32
〈Figure 2-10〉 The GPS tracker locates the user's location using the GPS location data and network location data of the smartphone. 34
〈Figure 2-11〉 The GPS tracker basically performs positioning per every 10 minutes.. 35
〈Figure 2-12〉 GPS tracker algorithm: The GPS tracker performs positioning using GPS information every 10 minutes, but if GPS data... 35
〈Figure 2-13〉 GPS tracker data flow: The GPS data collection process consists of a smartphone for data generation, a data collection server,... 36
〈Figure 2-14〉 Illustration of Inhalation Route: Exposure and Dose. 37
〈Figure 2-15〉 Populationdata geration: The mobile communication system-based existing population data is calculated by applying subscriber... 41
〈Figure 2-16〉 IDW interpolation algorytme: The interpolation algorithm using IDW utilizes data from the 4 nearest measuring stations. 43
〈Figure 2-17〉 Hardware architecture: System hardware consists of collection server, application server and DB server. 44
〈Figure 2-18〉 The hardware used a nationally-approved cloud server. 45
〈Figure 2-19〉 Software architecture: The software system configuration is designed with data generation unit, collection unit, storage/analysis unit... 46
〈Figure 2-20〉 Algorithm for personal and population exposure estimation: The exposure level evaluation system consists of... 48
〈Figure 3-21〉 The outdoor measurement data stored in the DB is displayed based on GIS so that the user can check it in real time. 49
〈Figure 3-22〉 The indoor measurement data stored in the DB is displayed based on GIS including the building name so that users can... 50
〈Figure 3-23〉 The data collected at each measuring station was developed so that the entire history can be viewed in order to... 50
〈Figure 3-24〉 Alarm function is provided for maintenance, in out-of-service of instruments. 51
〈Figure 3-25〉 It shows the data measurement and flow of the GPS tracker. 52
〈Figure 3-26〉 GPS tracker system is offring the solution for checking the daily movement. 54
〈Figure 3-27〉 With the GPS tracker heat map function, it is possible to grasp the accumulated daily residence time. 54
〈Figure 3-28〉 Population data is expressed on GIS per 100m*100m grid. 56
〈Figure 3-29〉 A function to check each of the 2,204 grids in Guro-gu is provided.. 56
〈Figure 3-30〉 It shows the daily change of the population for 2019/10/01 in Guro-gu. 57
〈Figure 3-31〉 Observed PM₂.₅ data to apply IDW interpolation. 58
〈Figure 3-32〉 Using IDW interpolation technology, the system calculates 100m*100m concentration. 59
〈Figure 3-33〉 It shows the daily change of the high resolution concentration for 2019/10/01 in Guro-gu. 60
〈Figure 3-34〉 IDW performance verification: One grid was selected(blue dot), and when there was no data from the ② measuring device,... 61
〈Figure 3-35〉 Method to evaluate the performance of IDW by using the interpolation algorithm of Kalman Filter. 62
〈Figure 3-36〉 Data compare oof standard value and replaced value: The value (standard value) generated by the use of measuring device ② and... 62
〈Figure 3-37〉 Result of the correlation analysis for IDW performance evaluation: R² is 0.9936, which can be determined as a usable algorithm.. 63
〈Figure 3-38〉 The individual exposure level evaluation was designed based on model establishment, PM₂.₅ concentration and... 64
〈Figure 3-39〉 The population exposure level evaluation was designed based on model establishment, high-resolution PM₂.₅ concentration and... 65
〈Figure 3-40〉 The system is applied with data collection and transmission/storage/processing and user interface. 66
〈Figure 3-41〉 Roles and data flow are defined for each module for web services. 67
〈Figure 3-42〉 The software architecture consists of a collection server, storage/analysis server, service management and DB, and interfaces... 68
〈Figure 3-43〉 The measurement data is delivered to the collection server by the protocol defined by the meter and implemented in a DB... 69
〈Figure 3-44〉 API was defined and implemented so that the data of this system can be utilized for other research. 70
〈Figure 3-45〉 It shows the overall featues of the implemented system. 71
〈Figure 3-46〉 Test items, test methods, and target values for TTA performance evaluation are discussed before evaluation. 72
〈Figure 3-47〉 As a result of the system performance evaluation, the response time was measured within the target value.. 73
〈Figure 3-48〉 To calculate the personal exposure amount, the location information of the individual was used using the location... 74
〈Figure 3-49〉 (a) It shows the researcher's movement and accumulated residence time for each scenario. 75
〈Figure 3-50〉 (b) It shows the researcher's movement and accumulated residence time for each scenario. 76
〈Figure 3-51〉 Comparison gragh amng the outdoor concentration, PM₂.₅ concentration with I/O ratio, the RTI value as the true value. 77
〈Figure 3-52〉 R² was found to be 0.6058, indicating that more accurate observed data should be applied. 78
〈Figure 3-53〉 A system population exposure calculated in real time using observed PM₂.₅ concentration data, high-resolution concentration... 79
〈Figure 3-54〉 Almost similar patterns and numbers can be confirmed by comparing the population data of the 다사464429 grid on the UTM-K... 81
〈Figure 3-55〉 It can be seen that the total population data for 2020/04/06 and 2021/04/05 are similar. 81
〈Figure 3-56〉 R² was found to be 0.9921, indicating that historical data can be used for population exposure prediction. 82
〈Figure 4-57〉 Environmental health service should provide overall matters from measurement of environmental hazadous factors to risk... 83
〈Figure 4-58〉 Using the smartphone's geomagnetic sensors and related algorithm, it is possible to grasp the details of each... 84
〈Figure 4-59〉 A more accurate exposure level evaluation system can be implemented by adding personal physical activity data to the... 85
〈Figure 4-60〉 Future population exposure evaluation system: In order to implement a more valuable group exposure assessment system, a method... 87
〈Figure 4-61〉 Future POM and ICT/IoT-based exposure assessment system: Individual clinical information collection using wearable devices... 88