物联网设备代码翻译使用LSTM网络

K. Cashion, Satish Ravindran, Nilesh U. Powar, Joshua Gold
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引用次数: 3

摘要

目前,大型建筑用于管理室内气候的物联网(IOT)平台使用来自多个制造商的不同控制器和传感器。这些设备之间的通信需要有人将每个设备的数据转换为与公共集成引擎和存储历史记录兼容。主题专家需要破译用于每个设备的非标准命名约定,并在每次必须集成新设备时手动翻译数千个代码。为了帮助人类翻译,我们提出了一种使用深度神经网络(DNN)实现智能翻译的技术,该技术通过自动将任何具有识别数据模式的寄存器分配给标准化标签。
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IOT device code translators using LSTM networks
Currently, the Internet of Things (IOT) platform used by large buildings to manage the indoor climate uses different controllers and sensors from multiple manufacturers. Communication between these devices requires a human in the loop to translate each devices data to to be compatible with a common integration engine and storage historian. The subject matter expert needs to decipher the non-standard naming convention used for each device and manually translate thousands of codes each time a new device has to be integrated. To aid the human translator, we propose a technique to implement a smart translator using Deep Neural Networks (DNN) by automatically assigning any registers with recognized data patterns to standardized labels.
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