近年隨著地球人口的增加食物產量已經無法再滿足人們了，漁業和水產養殖促進糧食供應很大一部分，水產養殖是指飼養，飼養，和動物和植物的所有類型的水的環境中，包括池塘，河流，湖泊和海洋收穫。
根據FAO(Food and Agriculture Organization of the United Nations) 聯合國糧農組織研究指出全球的養殖漁業在2010產量已經超越了捕撈漁業，但養殖漁業者仍面臨到許多挑戰，其中最主要就是成本問題，包括了飼料、電、水等，水產飼料的用量通常是由經驗豐富的水產養殖戶決定，飼料撒放過多不但造成不必要的成本浪費，也會讓水質環境造成惡化影響，魚成長不完全、環境惡劣導致食安問題，這些都是養殖業者現在面臨最大的課題。
本論文主旨在提出了一個水質監控系統幫助養殖漁業控管成本，我們可以依照目前的水質感應數值去預測未來水質走向，像是Oxidation-Reduction Potential (ORP)氧化還原電位, potential Hydrogen (pH)酸鹼度，基於預測的水質，並建議用戶調整他們的飼料用量，在還沒到達一定惡化標準前，會先採取行動，可以替養殖業者省去不必要的成本開銷。

As global population continues to grow, food product will no longer meet the demand for human consumption. Fisheries and aquaculture contribute to a large portion of food supply and play a crucial role in eliminating hunger, promoting health and reducing poverty. Aquaculture refers to the breeding, rearing, and harvesting of animals and plants in all types of water environments including ponds, rivers, lakes, and the ocean. It is the fastest growing food-producing sector which accounts for nearly 50 percent of the world's food fish. According to Food and Agriculture Organization of the United Nations (FAO), the global aquaculture production has already exceeded the production quantities derived from wild fishery capture.
However, aquaculture is still facing number of challenges. One of which is the cost such as aquafeeds (i.e., fish food), electricity, and water. Amount of aquafeeds are usually determined by experienced aqua-farmers. Under feeding can reduce lower growth in size and number of harvested fish. On the other hand, over feeding can results not only waste of money but also deterioration of water quality. In fact, over feeding is one of the main reasons of water deterioration. As water quality deteriorated, water circulation pump needs to be turn on or water needs to be change, depend on the level of water quality. If no action is taken in time, the harvested fish will be lost. All of which increase the cost in aquaculture.
In this paper, we proposed a real-time water quality monitoring system for aquaculture. The proposed system predicts the trends in water quality based on the historical monitored sensor data, i.e., Oxidation-Reduction Potential (ORP), potential Hydrogen (pH), and temperature. Based on the predicted water quality, our system can suggest amount of aquafeeds to dispense into ponds , amount of time to turn on and off water circulation pump, and amount of fresh water need to be exchanged. The proposed system is able predict the water quality and suggest appropriate actions to reduce the cost of aquaculture.

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