Building a Fish-Vegetable Coexistence System Based on a Wireless Sensor Network

The foremost purpose of this study is to use wireless sensor network (WSN) technology to build an intelligent fish-vegetable coexistence system. As a traditional fish-vegetable coexistence system lacks intelligent diagnoses, personnel and the original materials are difficult to control, and efficien...

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Veröffentlicht in:IEEE access 2020, Vol.8, p.192119-192131
Hauptverfasser: Hsiao, Sung-Jung, Sung, Wen-Tsai
Format: Artikel
Sprache:eng
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Zusammenfassung:The foremost purpose of this study is to use wireless sensor network (WSN) technology to build an intelligent fish-vegetable coexistence system. As a traditional fish-vegetable coexistence system lacks intelligent diagnoses, personnel and the original materials are difficult to control, and efficiency is low. We expect to remotely monitor the environmental values of the fish-vegetable coexistence system at any time through Internet of Things technology and to control the feeding time and the brightness of LED lamps. The key concept of this system is to "let the fishes be farmers", meaning that when the system is balanced, the nutrient supply and water purification can form a good circulation system as long as fish feed is provided and the evaporated moisture is supplemented in a timely manner. The main control board of the system is an Arduino Mega 2560, and the ZigBee communication protocol is used as a wireless transmission tool, which is combined with a temperature humidity sensor and an illuminance sensor. Thus, the performance of the traditional temperature humidity sensor is improved, and the fish yield is increased. Real-time monitoring can minimize the loss of fish. This expert system increases the success rate of culturing and planting, and the overall system efficiency is increased. Our team creates a human-computer interaction interface using the C# programming language. This interface can be used to monitor the current sensing values and store the data in an Excel data sheet, thus allowing users to query and analyze previously detected data. Users can monitor the system operation status and control the load through the designed human-machine interface to achieve smart network remote monitoring.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3032795