External Radiation Exposure Estimation by OGC-based Sensor Information Platforms
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| Number of Parts | 183 | |
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| License | CC Attribution - NonCommercial - ShareAlike 3.0 Germany: You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor and the work or content is shared also in adapted form only under the conditions of this | |
| Identifiers | 10.5446/32146 (DOI) | |
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| Production Year | 2015 | |
| Production Place | Seoul, South Korea |
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Computer animation
Transcript: English(auto-generated)
00:04
Okay, let me start my presentation about the, about the LIFI platforms to have Fukushima residents to reduce possible health effects from the external radiation exposure.
00:21
My name is Kyungsu Kim. I'm a researcher at National Institute of Advanced Industrial Science and Technology in Japan. Actually, I'm Korean, but now I work in Japan, sorry. As you know, Japan had a big disaster damages
00:43
from 2011, the earthquake and tsunami on March 11th. In particular, a significant amount of radioactive materials to release into the environment after the accident of the nuclear power plants in Fukushima.
01:03
So the radiation exposure has the blood of lots of concerns about the environmental containment or economic and social consequences. So, sorry. 2013, one of the Japanese government's agency is JIA.
01:26
It started a project to collect and clean and publish the radiation monitoring data of the Fukushima area. So several research institute and the university is involved in this project.
01:42
In this project, the role of the AISC, is my institute, was to develop a common platform to share radiation databases. Actually, JIA has struggled to manage their legacy style of the databases,
02:01
like the CSV files, and they are also with a slightly different data schema, and also different special temper granularities. Not only JIA, but also other agency had a difficulty to use and reuse and assess.
02:22
Their data in their, again, our applications. So, in order to provide ease of use and then interoperable interfaces of the data services and integrations, we refer to OGC standard.
02:42
So, yeah, OGC is, sorry, I forgot the animation. So, especially, we employed GeoSober for WFS and WFS.
03:00
Do you know the WFS, WFS? Okay. And, 52 North SOS was our base mount to develop OGC-based sensor information platforms. And, when we successfully finished the project,
03:22
we showed many use cases of the data mesh up based on our platform. So, this is one of the examples to, example of the combination of our SOS with the weather data from other WMS data source. In this example, we showed a certain area
03:43
has the low level of radiation compared to the other places because of the heavy rains. Also, local governments can use our platform to determine the effect of their contininations work.
04:04
However, we were motivated to extend our sensor platform for real-time and mobile environment last year. Actually, the previous platform is just considered over to shared archiving data, so not near-time data.
04:23
Also, we moved to our target user from the government to mobile user, mobile general user. So, we thought we could use the real-time, the radiation, the dose rate to quickly and easily deliver the exposure estimation for the mobile user.
04:48
And also, we can send some notification to mobile user when the people's activity patterns have the more possibility to raise the health risk.
05:02
For example, someone always work outside to near to the hotspot area, but he doesn't know about that fact. But in our system, we manage all the monitoring data so we can detect some spots,
05:21
and then we can use that information to deliver the notifications. And so, therefore, we start the new project is an IP platform. So, according to the WHO report, the increased risk of the cancer, such as the leukemia or breast cancer
05:42
and thyroid cancer is predicted only certain area is the most to exposure group of the locations. Despite its very low level of the exposure, the potential health risk assessment is the primary point in the long-term plan.
06:03
So, in order to assess a long-term effect of the healthcare, it's really difficult, so we applied the concept of the personal life logging. So, the personal life log is the timeline of the chronological sequences of the activity,
06:25
such as food record or exercise record, or, what is that, is some event pictures, like this kind of, it's already different from the medical record. The development of the wearable devices with smartphones,
06:43
we expect we can store our whole life through the open interfaces for data format. For example, Sony already, they provide the less-based web services, API, for life log based on the smart band and the smartphone.
07:04
One of the main use cases in our project, the individuals, people who live in Fukushima, they want to know where and when and which activity is affected external radiation effect,
07:20
radiation in their daily life. So, I think we can use some life logging mechanism to manage the long-term health effect. This is the main component of the LIFI platform, is we have five components.
07:40
The first is the shutter is the personal dosimeter sensor to measure the individual's dose level. And mobile application play to connect between the digital tool and our cloud services. And then we also took cloud service, is logging system, and analyze the systems.
08:01
Also, the behind the background, we collect the real-time data by scrapping the web pages. Because NLA, they did not provide some web services to provide real-time data, but they just update the web pages, so we scrapped that.
08:22
So first, digital tool is developed by AIST and Chioda Technology Corporation. So this is personal dosimeters. So it is very light and a very compact size, such as just the twice of 500N is very small size.
08:42
And then it can be operate for one year without exchange of battery. So it's very merit for people to using this sensor. So people can check and print their dose level, the individual dose level, by using the dedicated readers and the desktops.
09:04
But, so it is not convenient, right? So even though the device is portable devices, but if I want to check my radiation level, I should go to some places to check. So we think, oh, we can use the smartphone
09:22
to deliver the data or check the radiation levels. So now we are planning to develop the new version of the digital tool, which is equipped by the mobile communication interface, especially Bluetooth LE. Also, the interface to control the sensor tasking,
09:41
because if we just, you know, if we have, it has the communication capability, the battery is very big problem. So we want to adjust of the tasking, sensor tasking part. So we need to submit the best control.
10:04
And then this is the mobile applications. So mobile application on the smartphone. The main role is to transfer data from digital tools to cloud services, and to track GPS locations. Another function is to collect semantic information
10:22
about the activity of a user, mobile user. Such as, I'm going to school, or I'm in the outside, kind of. So because many user don't want to look at is their low level of data, they want to know some abstract information.
10:41
For example, the average or high radiation exposure when I'm working outside, kind of information they need. So we want to create this kind of information for using the some tagging system. So this is, we put some,
11:00
a user can tag their activity using our application. And the current prototype is developed by Ionic open source framework. Have you, no? So Ionic provide a front-end SDK for developing hybrid mobile application with web technologies based on Apache Cordoba,
11:24
and AngularJS, and the globe. So it is very helpful to rapidly deploy a prototype applications. So please try to use. I'm not a person of the Ionic, but it's very convenient.
11:42
And this is some screenshot of our prototype of the mobile application. Because of the health concerns, the gender, and the age, and the job information is mandatory in our user profile. So we want to put some user file information about that.
12:01
And then we divide the tagging levels into the three categories, where you are, what are you doing, and then I can define any kind of levels. So when push the tagging buttons, and then user can see the log information, like the right side.
12:21
So there is the list of log. And then also, if you click the one log, you can tag of your geolocation on the web, or if the location is very different from where I am, then they can divide of their location using the map.
12:42
Before loading the, uploading the data to the cloud, the user cannot assess the radiation level of the shuttle and then ambient air dose. So ambient air is monitoring data. So when click the synchronize button on the top right, the mobile application sends the data to cloud server,
13:04
and the cloud server starts to integrate its personal log and then environment monitoring data. And then we estimate the external radiation exposure at the locations.
13:21
So we send the updated log information to mobile user. So, okay, sorry. And then it changes the color to get the estimation values. Now we cannot connect of the digital now, so just the ambient color is different, it changes.
13:46
Also we developed the, now we develop the cloud services to store many of life log, also provide of the estimation information and summary information. So especially, not only for our application,
14:01
but those other application can use our services using this API. So, but in summary part, we cannot, still we cannot publish the, we cannot develop this part because of, in commonly mobile user, they don't want to share their whole, you know, whole their life log.
14:21
But they want to know that someone, the expert to interpret their data and give some guidance to my activity. So that's why we think about the summary data. Maybe if we make the summary data, they can share. So in order to represent it of a summary data,
14:41
we look at some data format, such as the STMX, especially JSON because we think about the LASPU interfaces. So STMX, JSON, or JSON state, or GeoJSON is one of our candidate to represent it of summary data.
15:01
But now it's a little, I cannot find of good capabilities. So maybe we need to combine of those kind of format. For, okay, for design our format, okay, before the design of our format,
15:21
we have a developing of some analyzed application to compare the personal sense of things and the official monitoring data by using R. So we're trying to analyze the several cases and what kind of summary data we should provide. So current, also the all of data in our case,
15:43
in our platform, we're using the OrientedDB. So have you heard of OrientedDB? Oh, today I introduced many new technologies. So OrientedDB is similar to MongoDB, but also similar to Neo4j. So it provide a multimodal databases,
16:04
it's document and graph. And then most of the attractive thing is they provide a SQL-like interface to manipulate of data. So it's very, a little easier if we all know about the SQL. So you can get the more information
16:22
if you're using this URL. However, it has no functionality to manage of the special temporary data actually. So now we have lots of work to develop the plug-in to manage of the special temporary information on the top of the OrientedDB.
16:41
So yeah, okay, there are lots of work to do. In our previous platforms, we referred a little old-fashioned OGC standards. It's WFS or WPS, WMS. But now I think it's turn to our interest
17:04
to new generation of OGC standard, such as the sensor thing API and the moving feature encoding and indoor GMS. I thought that some presentation about the sensor thing API and indoor GMS,
17:21
so I expect they provide some open source about that. But the moving feature part is only they provide of the encoding part. So just to represent it of the data format. But they have no specification to how to use the update.
17:42
So now we are trying to contribute, to develop some open source to handle the moving feature. So moving feature is kind of trajectory information of the mobile user or mobile object. But moving feature, currently they defined XMS tile
18:02
and the CSV format. But in our applications, we prepare to JSON format. So maybe we have two extent of GeoJSON to represent the moving picture, I think. And anyway, when I look at the many open sources, still we cannot find a good candidate
18:22
to using the trajectory information in our platforms. So please consider to join our platform to develop. Yeah, I think we are very welcome to join our project. And thank you for your attention.
18:50
Any question? So the reason you're using OrientDB,
19:02
because it's a multi-model database, is that because of the different kinds of information you're getting in, like from the mobile, and then from the other sensors that you have? The reason is, I have to say, manage of the live link information, because for example, trajectory is connected of locations.
19:24
But if we just individually manage it, we always try to combine, make the trajectory information on the applications. But OrientDB is make the graph structure to connect. So if I pick up the one point, I can get all of the trajectory.
19:43
Also, one other reason, we make the tagging system, right? So it's very dynamically put the label information. So we want to connect that information, it's trajectory, or some locations. It's dynamically.
20:00
So that is one of the reasons to use OrientDB. Also, I think Neo4j is graph database, it's a good candidate. But the problem is, is they're using the Cypher query languages, their own query languages. But already complicated to using that. But OrientDB, they're using the SQLite.
20:21
So it's very easier to use for me. And then very hard to say, is a good function to kind of a point concept. So please use. Please try to use.
20:43
Could you discuss a little bit more about the use of iconic? Yeah. Where, why you chose that, or why it was the best fit? Iconic? Iconic?
21:01
Ah, ionic. Yeah. Yes. Actually, we start to the Cordoba, Apache Cordoba. Apache Cordoba is open source of the PongGap platform. I think PongGap is very popular. So this is main attribute,
21:21
is the develop the hybrid of web application, but web application operate on the top of the mobile phone so we don't need to refactor to our application for mobile phone. But the Cordoba is just to provide
21:42
of the very hardware, the plug-ins. So, but we need more fashion of it, right? Is more design, good design. So we're using the kind of, what is that, boot script of Twitter, right? So it's kind of, ionic is one of the CSS components.
22:04
So we can more beautiful, we can make more beautiful applications. But, and then, but, AkuaJS is the, they provide model, view, and control. So they are very good combinations, you know, of this platform, I think.
22:29
Okay, thank you.