Difference between revisions of "Team:NTHU Taiwan/Demonstrate"
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When we started building this system, we aimed not only to solve a few farmers’ problems but on a bigger scale, agricultural and industrial, since in most of the developing countries, factories could be easily found in between farmland. On the left-hand side of the flowchart, we developed the system that could sense the concentration of the EDC in the water and control the valve to protect the farmland from polluted water. And on the right-hand side of the flowchart, we could collect such data, such as the concentration, time, and place. If the number of devices could grow to dozens or say hundreds, we would be able to tell where and when did the pollution came from. | When we started building this system, we aimed not only to solve a few farmers’ problems but on a bigger scale, agricultural and industrial, since in most of the developing countries, factories could be easily found in between farmland. On the left-hand side of the flowchart, we developed the system that could sense the concentration of the EDC in the water and control the valve to protect the farmland from polluted water. And on the right-hand side of the flowchart, we could collect such data, such as the concentration, time, and place. If the number of devices could grow to dozens or say hundreds, we would be able to tell where and when did the pollution came from. | ||
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Latest revision as of 03:05, 2 November 2017
Demonstrate
The Smart EDC Farmland Protection System
In order to solve some real environmental challenges, our team has proposed an integrated system that can both detect and degrade endocrine disrupting chemicals (EDCs) suitable for farmland water protection.
When we started building this system, we aimed not only to solve a few farmers’ problems but on a bigger scale, agricultural and industrial, since in most of the developing countries, factories could be easily found in between farmland. On the left-hand side of the flowchart, we developed the system that could sense the concentration of the EDC in the water and control the valve to protect the farmland from polluted water. And on the right-hand side of the flowchart, we could collect such data, such as the concentration, time, and place. If the number of devices could grow to dozens or say hundreds, we would be able to tell where and when did the pollution came from.
IoT System and App
With the implementation of our device, we now can provide farmers a water protection system. Furthermore, we have developed an app and IoT system. The app will allow the user to know the condition of the farmland water, and the IoT system is set to save all the data and collaborate with other nearby protection systems to build up a “safe web.” When our devices are widely spread around a region, we would not only be able to help the farmers keep their farmland’ water source safe, but even identify when and where the pollution came from.
The App Design
Why we built this APP?
The purpose of building this APP is that we hope to monitor values from our detection point in periodically.Furthermore, if we have multiple detection points in the future, we can label all data with different colors of markers according to their concentrations, and show them on the google map. Therefore, we can get regional concentrations at once, which enable us to identify sources of pollution with ease.
How do we build our APP?
The software we use is Android Studio. And we manage to represent our detection data in the following ways:
Tab1: Periodically detection value from a single detection point.
Tab2: Historical monitoring data from a single detection point.
Tab3: The distribution of all detection points and their visualized EDC concentrations.
Since our detection system has implemented Internet of Things (IoT), therefore, all data being detected will be stored to our cloud in JSON format (For details, please refer to DEVICE / Software – IoT page). So if we want to retrieve those data from our cloud, what we have to do can be simplified as followings:
1. Get JSON file from server.
2. Parse JSON to retrieve specific data.
3. Display.
Now we will go through those steps one by one :
1. Get JSON file from server
Data is uploaded to our cloud were stored in JSON format (Figure 1), and data being uploaded by different sensors have their own unique URL. So, in our code, by searching the specific URL (Figure 2), we can get the information we need.
(Notice: Since our EDC sensor has not been made yet, so here we use the value detected by ultrasound for replacement. However, our detector’s mechanical design proposal and the software parts are ready.)
