By monitoring soil and atmosphere condition, our models can use AI machine learning to calculate how to maximize productivity and improvee the soil health. Thus, we constructed an IoT(Internet of Things) 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.
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| − | 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. | + | By monitoring soil and atmosphere condition, our models can use AI machine learning to calculate how to maximize productivity and improvee the soil health. Thus, we constructed an IoT(Internet of Things) 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. | Besides, the current conditions will be shown on the user interface. | ||
</p> | </p> | ||
</div> | </div> | ||
<div class="title_1"><p>Procedure</p></div> | <div class="title_1"><p>Procedure</p></div> | ||
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<p> | <p> | ||
1. Construct our IoT system with Arduino Yun and sensors on the farm for instant supervisor.<br> | 1. Construct our IoT system with Arduino Yun and sensors on the farm for instant supervisor.<br> | ||
2. Arduino Yun receives the conditions and transmit to our cloud server through wi-fi.<br> | 2. Arduino Yun receives the conditions and transmit to our cloud server through wi-fi.<br> | ||
3. Print out the current conditions to user interface with IoTtalk.<br> | 3. Print out the current conditions to user interface with IoTtalk.<br> | ||
| − | + | Monitoring conditions: Temperature, Humidity, Soil moisture, altitude, Atmosphere pressure, pH value, EC value. | |
</p> | </p> | ||
</div> | </div> | ||
<div class="title_1">System Design</div> | <div class="title_1">System Design</div> | ||
<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"> | ||
| + | <div class="text"> | ||
<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. | |
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| − | <img src="https://static.igem.org/mediawiki/2018/f/ | + | <img src="https://static.igem.org/mediawiki/2018/f/f5/T--NCTU_Formosa--_drip_irrigation1017.png" class="Bella left"> |
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<div class="text"> | <div class="text"> | ||
<p> | <p> | ||
| + | Above are the sensors, irrigation system, and control center that we installed in our demostration farm, which including electrical conductivity sensors, soil moisture sensors, soil pH sensors, weather box, etc. | ||
| + | </p> | ||
| + | </div> | ||
| − | + | <img src="https://static.igem.org/mediawiki/2018/a/a0/T--NCTU_Formosa--Demo_IoT.png" class="Arduino"> | |
| + | <div class="text"> | ||
| + | <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. | ||
| + | By this system, the farms can be managed automatically and provide advices to farm holders to achieve precise agriculture. | ||
</p> | </p> | ||
| − | + | </div> | |
| + | |||
| + | <div class="title_1"><p>References</p></div> | ||
| + | <div class="text"> | ||
| + | <p> | ||
| + | 1. Lin, Y., et al. (2017). "IoTtalk: A Management Platform for Reconfigurable Sensor Devices." IEEE Internet of Things Journal 4(5): 1552-1562.<br> | ||
| + | </p> | ||
| + | </div> | ||
</div> | </div> | ||
Latest revision as of 06:38, 4 December 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.
Monitoring conditions: Temperature, Humidity, Soil moisture, altitude, Atmosphere pressure, pH value, EC value.
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.
Above are the sensors, irrigation system, and control center that we installed in our demostration 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.
