基于物联网遥测系统的水产养殖渔业智能测量和监测系统

Prisma Megantoro, Antik Widi Anugrah, Muhammad Hudzaifah Abdillah, Bambang Joko Kustanto, Marwan Fadhilah, Pandi Vigneshwaran
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摘要

本文讨论了水产养殖介质在线监测设备的仪器设计。该物联网(IoT)实时遥测系统的主处理器是一块 ESP32 板。温度、酸度水平、电导率水平、溶解氧(DO)水平和水中的氧还原程度是测量的水产养殖参数。ESP32 从每个传感器收集数据,将其分组为一个数据集,显示在 LCD 上,保存到 SD 卡,然后上传到实时数据库。此外,正在为用户开发安卓应用程序。该设备已经过测试,以确保每个测量参数都准确无误。精确度测试是实验室规模测试的主要结果之一,它表明每个参数都有不同的测量误差,代表着平均误差的绝对值。6 个受测传感器/仪器接受了测试。温度传感器的平均绝对误差为 +0.76%,pH 传感器的平均绝对误差为 +1.52%,电导率(EC)传感器的平均绝对误差为 +10.8%,氧化还原电位(ORP)传感器的平均绝对误差为 +14.6%,溶解氧传感器的平均绝对误差为 +9.3%,总溶解固体(TDS)传感器的平均绝对误差为 +13.2%。该设备非常可靠、方便,可实时、准确地监测水产养殖介质的状况。
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Smart measurement and monitoring system for aquaculture fisheries with IoT-based telemetry system
The instrumentation design of an online monitoring device for aquaculture media is discussed in this article. The main processor in this internet of things (IoT) real-time telemetry system is an ESP32 board. Temperature, acidity level, conductivity level, dissolved oxygen (DO) level, and degree of oxygen reduction in the water were the aquaculture parameters measured. The ESP32 collects data from each sensor, groups it into a dataset, displays it on the LCD, saves it to the SD card, and then uploads it to the real-time database. In addition, an Android application is being developed for users. This device has been tested to ensure that each measured parameter is accurate and precise. The accuracy test, one of the major results of laboratory scale tests, demonstrates that each parameter has a different measurement error that represents with average error absolute. Six tested sensors/instruments were subjected to the test. Average absolute error for temperature sensor is +0.76%, pH sensor is +1.52%, electrical conductivity (EC) sensor is +10.8%, oxidation reduction potential (ORP) sensor is +14.6%, DO sensor is +9.3%, and total dissolve solids (TDS) sensor is +13.2%. This device is very dependable and convenient for monitoring the condition of aquaculture media in real-time and accurately.
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