Dual-Server IoT Architecture for Data-Driven Building Climate Control
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Solution Overview
Problem
Conventional IoT architectures for building climate control lack integration of low-energy technologies and do not allow for comprehensive experimentation or data-driven operations, limiting their ability to optimize energy efficiency and indoor environmental conditions.
Innovation Solution
A dual-system IoT architecture that includes a rule-based server for operation control and a data-driven server for predictive modeling and optimization, integrated with various sensors and actuators, allowing for data acquisition, management, and separate commanding mechanisms to test and implement learning algorithms across multiple zones or the entire building.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional IoT architecture is used for building climate control, then system simplicity is maintained, but integration capability of low-energy technologies and experimentation capability are limited
Solution Approach 1:
The system is divided into two independent servers: a rule-based server for operational control and a data-driven server for predictive modeling and experimentation. This segmentation allows each server to specialize in specific functions, enabling integration of complex low-energy technologies while maintaining manageable system operation through clear functional separation
Solution Approach 2:
The dual-server architecture provides multi-functionality by enabling both traditional rule-based control operations and advanced data-driven experimentation simultaneously. The system can handle diverse low-energy technologies (TABS, natural ventilation, geothermal) through a unified platform that supports multiple control paradigms, making it universally applicable to various building configurations
2Productivity
If rule-based control is used, then operational reliability is maintained, but energy optimization and adaptive control capabilities are limited
Solution Approach 1:
The data-driven server acts as an intermediary between sensor data and control actions, providing predictive modeling and optimization recommendations. It processes operational data to generate optimized control commands that are then executed by the rule-based server, enabling energy efficiency improvements while maintaining the stability of the underlying rule-based control system
Solution Approach 2:
The data-driven server performs preliminary analysis and predictive modeling of building performance before control actions are executed. By pre-processing data and predicting optimal control strategies in advance, the system can improve energy efficiency while the rule-based server ensures reliable execution of control actions based on established rules
3Loss of energy
If integrated low-energy technologies are deployed, then energy consumption is reduced, but control complexity increases
Solution Approach 1:
The control system is segmented into rule-based and data-driven components, each handling specific aspects of controlling integrated low-energy technologies. The rule-based server manages straightforward control logic while the data-driven server handles complex optimization for technologies like TABS and natural ventilation, reducing the control complexity burden on any single component
Solution Approach 2:
The system implements comprehensive feedback loops where sensors continuously monitor building performance and feed data to both servers. The data-driven server uses this feedback for predictive modeling and optimization, while the rule-based server uses it for real-time control adjustments, enabling effective management of integrated low-energy technologies through multi-layered feedback mechanisms
Data Source
AI summary
There is provided a system for environmental control in a building. The system includes a plurality of sensors including operational sensors and data gathering sensors, and a plurality of actuators. The system also includes a rule-based server and a data-driven server coupled to the plurality of sensors and the plurality of actuators. The rule-based server receives operation signals from the operational sensors, and control operation of the plurality of actuators according to one or more rules based on the operation signals. The data-driven server receives or monitors data signals from the data-gathering sensors and the operation signals from the operational sensors, trains and/or applies data-driven models to the data signals and the operation signals to predict performance changes in the building due to a command. In accordance with a determination that the performance changes meet a predetermined criteria, the data-driven server controls operations of the plurality of actuators according to the command.