Edge Connector Autoconfiguration for Building Device Cloud Links
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Solution Overview
Problem
Building management systems (BMS) face challenges in efficiently configuring and optimizing edge processing devices for communication with cloud computing systems, particularly in automatically identifying and configuring new devices and managing data communication protocols, leading to inefficiencies in data collection and control operations.
Innovation Solution
A system that generates and deploys connector components for edge processing devices, utilizing REST APIs and graphical user interfaces to configure communication parameters, and manages data access and updates, while also identifying machine-learning models and optimizing components based on device processing capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual configuration methods are used for edge processing devices, then configuration accuracy can be ensured, but configuration time and operational complexity increase significantly
Solution Approach 1:
The system enables edge processing devices to automatically self-configure by generating connector components based on device identifiers and deploying them autonomously. The device retrieves its own configuration parameters (communication direction, server fields, sensor fields, default values) and configures its communication protocols without manual intervention, achieving both high accuracy and time efficiency.
Solution Approach 2:
The system pre-generates connector templates with all necessary configuration parameters before deployment. When a new edge device is added, the pre-configured connector template is quickly instantiated and deployed, eliminating the need for time-consuming manual configuration while ensuring accuracy through pre-validated templates.
2Productivity
If automated configuration systems are implemented, then configuration speed increases, but system complexity and difficulty of managing communication protocols increase
Solution Approach 1:
The system employs a universal connector template that can be applied to multiple edge processing devices regardless of their specific types or communication protocols. The template includes configurable parameters for different communication directions, server fields, sensor fields, and default values, allowing it to adapt to various protocols (REST APIs, MQTT, HTTP) without requiring separate configuration systems for each protocol type.
Solution Approach 2:
The system manages complexity by parameterizing the connector template with configurable fields (communication direction, server fields, sensor fields, default values). Instead of creating complex dedicated configurations for each device type, the system adjusts parameters within the universal template to accommodate different communication protocols and device requirements, simplifying the overall system architecture.
3Adaptability or versatility
If custom connector components are generated for each device, then communication compatibility improves, but processing time and computational resources increase
Solution Approach 1:
The system generates custom connector components for each edge processing device by copying and instantiating a pre-defined connector template. This template contains all necessary structural elements and configuration parameters. The copying process is rapid and automated, producing device-specific connectors that inherit the template's compatibility features while requiring minimal processing time compared to creating custom connectors from scratch for each device.
Data Source
AI summary
Systems, methods, and non-transitory computer-readable media for optimization and autoconfiguration of edge processing devices are disclosed. A cloud computing system can receive a request to configure a target building device. The cloud computing system can identify, based on the target building device, a connector template for the target building device. The connector template can include one or more parameters for a connector component configured to cause the target building device to communicate with the cloud computing system. cloud computing system can generate the connector component for the target building device based on the one or more parameters. cloud computing system can deploy the connector component to the target building device.