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.
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<img src="https://static.igem.org/mediawiki/2018/7/76/T--NCTU_Formosa--IOT_SYSTEM_1017.png" class="Bella"> | <img src="https://static.igem.org/mediawiki/2018/7/76/T--NCTU_Formosa--IOT_SYSTEM_1017.png" class="Bella"> | ||
| + | <div class="explanation"> | ||
| + | <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 | ||
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<img src="https://static.igem.org/mediawiki/2018/1/17/T--NCTU_Formosa--pHsensor1017.png" class="Bella"> | <img src="https://static.igem.org/mediawiki/2018/1/17/T--NCTU_Formosa--pHsensor1017.png" class="Bella"> | ||
<img src="https://static.igem.org/mediawiki/2018/f/f5/T--NCTU_Formosa--_drip_irrigation1017.png" class="Bella"> | <img src="https://static.igem.org/mediawiki/2018/f/f5/T--NCTU_Formosa--_drip_irrigation1017.png" class="Bella"> | ||
Revision as of 03:16, 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
Figure 1: IOT System
References
1. Lin, Y., et al. (2017). "IoTtalk: A Management Platform for Reconfigurable Sensor Devices." IEEE Internet of Things Journal 4(5): 1552-1562.
