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Edge Intelligent Water Affairs Test Bed
Huawei Technologies Co., Ltd.
Wapwag (Shanghai) Smart Water Public Co., Ltd.
This lab platform is the second phase of the Edge Intelligent Water Affairs Test Bed. Based on the existing functions of smart water affairs platforms, stream-processing engines are deployed on edge computing nodes of this platform to enable the nodes to process stream data and respond to emergencies in real time. With the introduction of edge computing capabilities, most data does not need to be uploaded to a cloud platform, reducing bandwidth transmission costs and data storage fees on the central cloud platform.
In addition to deploying stream-processing engines on edge computing nodes, this lab platform also explores ways to implement interaction between the cloud (central cloud platform) and devices (edge computing nodes). For deep learning algorithms, model training tends to consume a large amount of data and computing power. Therefore, the model training process is not suitable to be deployed at the edge node side. Once model training is completed and models are used to analyze data, the consumption of hardware resources will be small. That is, the analysis function can be deployed on edge computing nodes.
By deploying stream-processing engines and deep learning models on edge computing nodes, a smart water system supports edge intelligence. This brings great value for the system to handle water supply emergencies, perform predictive maintenance of devices, and reduce the utilization cost.
Based on Huawei's G2500 edge computing nodes, and by leveraging Huawei's cloud platform and Wapwag's smart water platform, the platform can be used to monitor and manage water supply equipment to ensure efficient, secure, and reliable operations of water supply systems.
By introducing the edge stream-processing engine, this lab platform coordinates with Enterprise Intelligence (EI) services (such as deep learning) using Huawei's cloud platform and Wapwag's smart water platform to build the entire system.
Based on the existing smart water test bed, the platform reduces system operation costs by 10%, increases the system response speed by 50%, and improves the system reliability by 50%.
Determined on the basis of the existing smart water test bed, the platform improves security and reliability of water supply and reduces energy consumption.