Cloud Building Device Update Gateway Protocol Translation
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Solution Overview
Problem
Existing systems for monitoring and controlling physical environments face challenges such as data privacy issues, scalability, and the need for comprehensive strategies to accurately time-stamp and process data for energy or space usage efficiency, particularly in large buildings with diverse sensor devices generating data in various formats.
Innovation Solution
A cloud-based monitoring and control system that includes a computing cloud with modules for project service, data update, and image repository, along with a building server and gateway, using communication protocols like HTTPS and MQTT to manage and update system devices, ensuring data privacy, scalability, and efficient data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a cloud-based system with multiple modules and communication protocols is implemented to monitor and control physical environments, then data processing accuracy and privacy protection are improved, but system complexity and deployment difficulty increase
Solution Approach 1:
The system is divided into distinct functional modules: a computing cloud for centralized data processing, a building server for local coordination, and a gateway for device communication. Each module has a specific responsibility, allowing complex data processing tasks to be broken down into manageable segments that can be developed, deployed, and maintained independently while maintaining overall system accuracy.
Solution Approach 2:
The gateway acts as an intermediary layer between diverse sensor devices and the building server, translating various device protocols into standardized communication formats. This intermediary approach simplifies the overall system architecture by handling protocol conversion and data normalization at the gateway level, preventing complexity from propagating through the entire system.
2Adaptability or versatility
If the system is designed to handle diverse sensor devices and large amounts of data from multiple sources, then scalability and adaptability are improved, but data processing time and resource requirements increase
Solution Approach 1:
The gateway pre-processes and normalizes data from diverse sensor devices before transmitting it to the building server. This preliminary action includes filtering, aggregation, and standardization of data formats, which reduces the processing burden on upstream systems and enables faster handling of diverse device inputs without compromising adaptability.
Solution Approach 2:
The system introduces a hierarchical dimension with multiple processing levels: device-level filtering at the gateway, building-level aggregation at the server, and cloud-level analytics. This dimensional approach allows the system to maintain adaptability to diverse devices while distributing processing time across different hierarchical levels, preventing any single level from becoming a bottleneck.
3Reliability
If comprehensive data collection and processing strategies are implemented to ensure accurate time-stamping and energy usage measurement, then measurement precision and reliability are improved, but system resource consumption and complexity increase
Solution Approach 1:
The system implements selective data collection where the gateway filters and prioritizes which sensor data to transmit based on predefined criteria such as data significance, change thresholds, and scheduling requirements. This partial action approach ensures that only necessary data with sufficient quality for reliable measurements is processed and transmitted, maintaining data reliability while reducing overall system resource consumption.
Solution Approach 2:
The system dynamically adjusts data processing parameters such as sampling rates, transmission intervals, and aggregation levels based on current system conditions, data types, and reliability requirements. This allows the system to optimize the balance between measurement precision and resource consumption by changing operational parameters rather than maintaining fixed high-resource settings for all scenarios.
Data Source
AI summary
Disclosed are systems and methods for updating a system device in a cloud-based system for monitoring and controlling physical environments. A system comprises a computing cloud with a project service module for responding to requests to access project data, an update module for providing access to data associated with a project hierarchy, and an images repository module for providing data identifying the location of update data. The system also comprises a building server communicatively coupled with the computing cloud, a gateway communicatively coupled with the building server and associated with the system device in need of an update.