Air-Conditioning Control Using Multi-Sensor Zoning and Cloud Feedback
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Solution Overview
Problem
Current intelligent air-conditioning systems suffer from inefficiencies due to single sensor placement issues, lack of zone-specific temperature control, and inadequate power management, leading to imbalanced indoor temperatures and excessive energy consumption.
Innovation Solution
An intelligent air-conditioning controlling system that utilizes a cloud server to analyze environmental and user data from multiple sensors, including beacons and mobile devices, to generate precise control commands for air-conditioning units, optimizing temperature distribution and energy usage across zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single sensor is used for temperature sensing, then the system structure is simple, but the temperature control accuracy deteriorates due to sensor position limitations
Solution Approach 1:
The patent divides the temperature sensing function into multiple independent sensors positioned at different locations (ceiling, wall, table height). Each sensor measures temperature in its specific zone, and the controlling device integrates these distributed measurements to achieve comprehensive and accurate temperature monitoring throughout the space.
Solution Approach 2:
The patent adds spatial dimensionality to temperature sensing by placing sensors at multiple heights and positions (ceiling level, wall level, table height) rather than relying on a single point measurement. This multi-dimensional sensing approach captures temperature gradients and provides a more representative measurement of the overall environment.
2Stability of the object's composition
If the air-conditioning controls the entire space temperature, then the temperature distribution becomes uniform, but the power consumption increases when few people are present
Solution Approach 1:
The patent transitions from uniform whole-space temperature control to localized zone-specific control. By deploying multiple sensors at different positions and using detection devices to identify human presence in specific zones, the system adjusts air-conditioning output locally rather than uniformly across the entire space, reducing energy waste in unoccupied areas.
Solution Approach 2:
The patent implements dynamic temperature control that adapts to changing occupancy conditions. The system continuously monitors human presence and location, then dynamically adjusts the air-conditioning control parameters for different zones in real-time, rather than maintaining a static uniform temperature throughout the space.
3Ease of operation
If the fan direction is adjusted without reference to indoor temperature, then the control operation is simple, but the indoor temperature becomes imbalanced and power is wasted
Solution Approach 1:
The patent implements feedback control for fan direction adjustment. The controlling device receives temperature data from multiple sensors positioned throughout the space, analyzes the temperature distribution pattern, and automatically adjusts the fan direction to correct imbalances. This closed-loop feedback mechanism eliminates the need for manual intervention while maintaining temperature equilibrium.
4Device complexity
If a simple controlling device with basic calculating capability is used, then the device cost is low, but the system cannot process complicated information such as multiple temperature data and historical records
Solution Approach 1:
The patent introduces a cloud server as an intermediary between the simple local controlling device and the complex data processing requirements. The controlling device collects temperature data and user information from multiple sensors, then transmits this data to the cloud server which performs sophisticated analysis including historical record comparison and big data processing. The cloud server returns optimized control parameters to the simple local device, enabling advanced information processing without requiring a complex local controller.
Data Source
AI summary
An intelligent air-conditioning controlling system comprises an intelligent controlling device, an air-conditioning, a plurality of sensing devices, and a cloud server. The intelligent controlling device receives environment information and user information from the plurality of sensing devices, and calculates a target temperature. The cloud server retrieves a usage record of a user according to the user information, and executes a big data analysis for generating a historical record and recommended environment temperature according to historical data and the environment information. The intelligent controlling device receives the usage record, the historical record and recommended environment temperature and a control parameter from the cloud server, and generates a control command for the air-conditioning in accordance with the target temperature, the usage record, the historical record and recommended environment temperature and the control parameter.