碩士 / 靜宜大學 / 資訊管理學系 / 107 / In recent years, with the awareness of life, many people have begun to pay attention to their own quality of life. Many of them will choose to raise pets to accompany themselves or to improve the quality of life. This research uses the Internet of Things technology and various sensors to monitor the variables in the aquarium, and automatically adjusts the equipment in the aquarium according to the collected variables.
Unlike the previous manual monitoring of water quality and temperature information, the water in the aquarium may be replaced when the water quality is acceptable, resulting in poor fish adaptation and a greater impact than no water change. Or ignore the temperature changes that cause fish and water plants to be frostbitten or burned or even cause death.
The method proposed in this study can reduce the loss caused by human error. When the temperature is too low, the heater can be automatically activated. When the water is turbid, the owner can be reminded to replace the filter, and the data is collected and sent to the cloud, even if it is working out can also view the real-time data in the aquarium through web pages and mobile phones, which can reduce the time and effort required for people to raise fish.
In addition, combined with the technique of image recognition and processing, this study proposes a method to measure the activity of fish. After getting the fishes locations by the image recognition technology, the displacement, velocity and direction can be calculated. Then, the distance can be judged, and the observation of the activity force can be detected. It can instantly adjust the environment required in the fish in the box, and provide modern people with a busy life without worrying about whether their aquarium is quietly becoming an environment that is not suitable for fish to survive.
| Identifer | oai:union.ndltd.org:TW/107PU000396010 |
| Date | January 2019 |
| Creators | Chen, Xian-Zong, 陳顯宗 |
| Contributors | Yeh, Jieh-Shan, 葉介山 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 59 |
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