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Developing a LoRaWAN-Based Data Acquisition Device Empowered by AI

delete2026-01-01
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PRE
AI
M
Menno J. Faber *
H
Hélder R. O. Rocha
M
Marcelo E. V. Segatto
J
Jair A. L. Silva
DOI：10.1007/978-3-031-98287-3_2delete
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摘要

摘要

En 中文
针对工业物联网（IIoT）应用，提出了一种定制化的数据采集（DAQ）设备。该设备名为2S Tools Flex DAq，是一种多变量无线DAQ设备，支持LoRaWAN、LTE和ZigBee等先进连接选项，并兼容低功耗的多种传感器。为展示将人工智能（AI）集成到包含传感器、2S Tools Flex DAq及云系统的潜力，我们应用长短期记忆（LSTM）神经网络对设备采集的水质参数进行预测分析。具体而言，我们利用远程监控系统中的2S Tools Flex DAq采集的实时数据，预测pH值、水位和温度。LSTM模型在预测pH值和温度方面取得了高精度，R²值分别为0.97和0.99。这些实验结果表明，将AI能力嵌入我们构建的DAQ设备中，以增强IIoT环境下的预测性维护和流程优化是可行的。
Keyword:
LoRaWAN
Data Acquisition
Artificial Intelligence
LSTM

期刊

S
SMART TECHNOLOGIES, SYSTEMS AND APPLICATIONS, SMARTTECH-IC 2024, PT I
IF:
0
论文数:
32
被引数:
0

机构

U
universidade federal do espirito santo
学者数:
6.9K
论文数: 4.0K
被引数: 4
引用论文

引用论文

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