Development of Automatic Home-Based Fish Farming Using the Internet of Things
Satien Janpla1, Nisanart Tachpetpaiboon2, Chaiwat Jewpanich3
1Satien Janpla, Department of Computer Science, Suan Sunandha Rajabhat University, Bangkok, Thailand.
2Nisanart Tachpetpaiboon, Department of Computer Science, Suan Sunandha Rajabhat University, Bangkok, Thailand.
3Chaiwat Jewpanich, Department of Educational Technology and Computers, Suan Sunandha Rajabhat University, Bangkok, Thailand.
Manuscript received on 02 March 2019 | Revised Manuscript received on 06 March 2019 | Manuscript published on 30 July 2019 | PP: 3308-3315 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2677078219/19©BEIESP | DOI: 10.35940/ijrte.B2677.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This research purposed to design an automatic home-based fish farming using the internet of things and to evaluate its efficiency. There were 3 processes in this research: 1. creating a home-based fish farming environment (fish pond) 2. designing and developing home-based fish farming by using the internet of things and 3. experimenting and implementing the system. The fish pond (90 x 180 x 50 cm) was made up of 90 blocks. It was coated with waterproofed plastic in order to contain a maximum of 80 cm x 170 cm x 40 cm. or 0.544 m3 of water. The automatic home-based fish farming system using the internet of things consisted of 6 parts in the form of 1. A NodeMCU Microcontroller 2. An automatic fish feeder 3. A relay module 4. Home Wi-Fi 5. Web Application 6. Line Notify. The NodeMCU Microcontroller was the main module use to control the automatic working of the system. The experiment resulted in a number of findings. Firstly, Fish feeder experiment, Experiment for the fish feeder to release food for 30 grams, 5 times, average time 23 seconds, error rate + 8.70%, -7.25%; Experiment for the fish feeder to release food for 45 grams, 5 times, average time 35 seconds, error rate + 10.00%, -8.57%; Experiment for the fish feeder to release food for 60 grams, 5 times, average time 48 seconds, error rate + 2.08%, -5.27%; finally, 75g fish feeder, 5 times, average time 75 seconds, error rate +8.33%, -8.02%. As a result, the dispensing variation was no more than ±10%. Secondly, the timing of this machine was divided into 4 periods: during days 1 to 30, it dispensed food 30g. During days 31 to 60, it dispensed food 45g. During days 61 to 90, it dispensed food 60g. During days 91 to 142, it dispensed food 75g. It would feed 2 times: 7 am. and 6 pm. each day. Thirdly, the test was to turn on and off the water and oxygen pumps by just clicking a button on the web application. The system was used to feed 80 3-inch long catfish over a period of 142 days. At the end of the period, 43 catfish were left with 37 having died. The survival rate was 54%. These fish weighed 5,380 grams in total and their growth varied. There were 24 small fish which weighed 120-220 gram (61%), 10 medium sized fish which weighed 230-330 (23%) and 7 large fish which weighed 340-440 (16%). As a result, this system could be used for feeding fish, but it needs some improvements such as the introduction of a waste water monitoring system and an automatic water changing system which would enhance the automatic working of the system.
Index Terms: Automatic Home-Based Fish Farming, Internet of Things (IoT), Web Application, Line Notification.
Scope of the Article: IoT