By monitoring soil and atmosphere condition, our models can use AI machine learning to maximize productivity. Thus, we constructed an IoT system with Arduino Yun and sensors on our experimental farm to monitor the conditions in time. Through the IoT system, we can improve our soil enhancing system to coincident with real condition. Besides, the current conditions will be shown on the user interface.
Difference between revisions of "Team:NCTU Formosa/Hardware"
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<img src="https://static.igem.org/mediawiki/2018/0/01/T--NCTU_Formosa--Arduino.png" class="Arduino"> | <img src="https://static.igem.org/mediawiki/2018/0/01/T--NCTU_Formosa--Arduino.png" class="Arduino"> | ||
<p> | <p> | ||
| − | + | This is the schematic diagram on the design of our Arduino Yun. We connect soil electrical conductivity sensors, soil moisture sensors, soil pH sensors, weather box and power module with Arduino Yun. So that all the data from the farm can be collected and analyzed. | |
</p> | </p> | ||
| − | + | <div class="explanation"> | |
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| − | <div class=" | + | |
<svg class="icon" aria-hidden="true" data-prefix="fas" data-icon="arrow-circle-up" class="svg-inline--fa fa-arrow-circle-up fa-w-16" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M8 256C8 119 119 8 256 8s248 111 248 248-111 248-248 248S8 393 8 256zm143.6 28.9l72.4-75.5V392c0 13.3 10.7 24 24 24h16c13.3 0 24-10.7 24-24V209.4l72.4 75.5c9.3 9.7 24.8 9.9 34.3.4l10.9-11c9.4-9.4 9.4-24.6 0-33.9L273 107.7c-9.4-9.4-24.6-9.4-33.9 0L106.3 240.4c-9.4 9.4-9.4 24.6 0 33.9l10.9 11c9.6 9.5 25.1 9.3 34.4-.4z"></path></svg> | <svg class="icon" aria-hidden="true" data-prefix="fas" data-icon="arrow-circle-up" class="svg-inline--fa fa-arrow-circle-up fa-w-16" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M8 256C8 119 119 8 256 8s248 111 248 248-111 248-248 248S8 393 8 256zm143.6 28.9l72.4-75.5V392c0 13.3 10.7 24 24 24h16c13.3 0 24-10.7 24-24V209.4l72.4 75.5c9.3 9.7 24.8 9.9 34.3.4l10.9-11c9.4-9.4 9.4-24.6 0-33.9L273 107.7c-9.4-9.4-24.6-9.4-33.9 0L106.3 240.4c-9.4 9.4-9.4 24.6 0 33.9l10.9 11c9.6 9.5 25.1 9.3 34.4-.4z"></path></svg> | ||
Figure 1: IOT System | Figure 1: IOT System | ||
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<img src="https://static.igem.org/mediawiki/2018/f/f9/T--NCTU_Formosa--self1017.png" class="Bella"> | <img src="https://static.igem.org/mediawiki/2018/f/f9/T--NCTU_Formosa--self1017.png" class="Bella"> | ||
<img src="https://static.igem.org/mediawiki/2018/8/80/T--NCTU_Formosa--box1017.png" class="Bella"> | <img src="https://static.igem.org/mediawiki/2018/8/80/T--NCTU_Formosa--box1017.png" class="Bella"> | ||
| + | <p> | ||
| + | Above are the sensors that we installed in the demonstration farm, which including electrical conductivity sensors, soil moisture sensors, soil pH sensors, weather box, etc. | ||
| + | </p> | ||
| + | <img src="https://static.igem.org/mediawiki/2018/f/f7/T--NCTU_Formosa--dashboard.png" class="Bella"> | ||
| + | <p> | ||
| + | The data in the farm can be shown in the dashboard clearly so that the farm holders can real time monitor the farm. Most importantly, predictions results including turmeric yield, spore germination (diseases eruption) and ovum hatch (pests occurrence) can also been shown in the dashboard after data analysis. | ||
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| + | By this system, the farms can be managed automatically and provide advices to farm holders to achieve precise agriculture. | ||
| + | </p> | ||
<div class="title_1"><p>References</p></div> | <div class="title_1"><p>References</p></div> | ||
<div class="text"> | <div class="text"> | ||
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| + | <p> | ||
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| + | </p> | ||
<p> | <p> | ||
Revision as of 03:30, 18 October 2018
Procedure
1. Construct our IoT system with Arduino Yun and sensors on the farm for instant supervisor.
2. Arduino Yun receives the conditions and transmit to our cloud server through wi-fi.
3. Print out the current conditions to user interface with IoTtalk.
System Design
This is the schematic diagram on the design of our Arduino Yun. We connect soil electrical conductivity sensors, soil moisture sensors, soil pH sensors, weather box and power module with Arduino Yun. So that all the data from the farm can be collected and analyzed.
Figure 1: IOT System
Above are the sensors that we installed in the demonstration farm, which including electrical conductivity sensors, soil moisture sensors, soil pH sensors, weather box, etc.
The data in the farm can be shown in the dashboard clearly so that the farm holders can real time monitor the farm. Most importantly, predictions results including turmeric yield, spore germination (diseases eruption) and ovum hatch (pests occurrence) can also been shown in the dashboard after data analysis. By this system, the farms can be managed automatically and provide advices to farm holders to achieve precise agriculture.
References
1. Lin, Y., et al. (2017). "IoTtalk: A Management Platform for Reconfigurable Sensor Devices." IEEE Internet of Things Journal 4(5): 1552-1562.
