物联网支持的有效水产养殖水质实时监测方法

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES
MethodsX Pub Date : 2024-08-13 DOI:10.1016/j.mex.2024.102906
Rupali P. Shete , Anupkumar M. Bongale , Deepak Dharrao
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引用次数: 0

摘要

从可持续粮食供应和县域经济发展的角度来看,水产养殖是一个不断发展的产业。以技术为导向的水产养殖是有效监测水质和实现高产的解决方案。物联网(IoT)集成水产养殖可以满足这些要求。本研究文章介绍了一种综合方法,旨在利用 Arduino 板和通信模块将物联网传感器无缝集成到水产养殖环境中。所提出的方法可测量精确的水质参数,如温度、pH 值和溶解氧(DO),这些参数对于维持适宜的水产养殖环境的最佳条件至关重要。该方法能够实时收集关键数据点,这些数据点对预防鱼类疾病和死亡至关重要,而且人工干预和维护成本低。该方法的主要贡献如下:-设计和开发了紧凑高效的印刷电路板(PCB),以实现水产环境中精确的传感器数据读数和可靠的通信。-通过数据驱动决策,结合溶解氧、pH 值和温度传感器数据的相关性,预防鱼类疾病和死亡率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

IoT-enabled effective real-time water quality monitoring method for aquaculture

IoT-enabled effective real-time water quality monitoring method for aquaculture

Aquaculture is growing industry from the perspective of sustainable food fulfillment and county's economic development. Technology oriented aquafarming is the solution for effective water quality monitoring and high yield production. Internet of Things (IoT) integrated aquaculture can cater to such requirements. This research article introduces a comprehensive method aimed at seamlessly incorporate IoT sensors into aquafarming environments, utilizing Arduino boards and communication modules. The proposed method measures accurate water quality parameters, such as temperature, pH levels, and Dissolved Oxygen (DO), which are essential for maintaining optimal conditions for suitable aquaculture environment. This method enables the real-time collection of critical data points that are essential prevent fish diseases and mortality with low human intervention and maintenance cost. The key contributions of the methodology are mentioned below.

  • Design and development of a compact and efficient Printed Circuit Board (PCB) to achieve accurate sensor data readings and reliable communication in an aqua environment.

  • Prevent fish disease and mortality rate through data-driven decision incorporating correlation of DO, pH, and temperature sensor data.

  • Conducted instrument calibration checks and cross-validated automated system data with manual observations through repeatability tests to ensure precise measurements of sensor parameters.

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来源期刊
MethodsX
MethodsX Health Professions-Medical Laboratory Technology
CiteScore
3.60
自引率
5.30%
发文量
314
审稿时长
7 weeks
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