Indoor air cleaning method
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Solution Overview
Problem
Existing air purification systems struggle to efficiently and cost-effectively achieve clean room-level cleanliness in indoor environments by intelligently determining the optimal number of air cleaning devices and sampling cycles, while maintaining low noise and power consumption.
Innovation Solution
An indoor air cleaning system that combines gas detection modules with a cloud computing service device to form a database for intelligent calculation and comparison of air quality data, determining the required number of air cleaning devices and sampling cycles, and regulating actuation time, airflow volume, and noise level to reach clean room cleanliness levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the number of air cleaning devices is increased to achieve clean room level cleanliness, then the air purification effectiveness is improved, but the installation cost and power consumption increase
Solution Approach 1:
The system dynamically adjusts the operating state of air cleaning devices based on real-time air quality monitoring. The control device receives pollution data from gas detection modules and automatically regulates the number and operation intensity of air cleaning devices, transitioning from static fixed-operation mode to dynamic adaptive operation, thereby reducing energy consumption while maintaining purification effectiveness
Solution Approach 2:
The system changes operational parameters (number of devices, operation intensity, sampling frequency) based on detected air pollution levels. When pollution is high, more devices operate at higher intensity; when pollution is low, fewer devices operate at lower intensity or enter standby mode, optimizing the balance between purification effectiveness and energy consumption
2Reliability
If air cleaning devices operate continuously at high intensity to maintain clean room cleanliness, then the air quality is improved, but the noise level increases
Solution Approach 1:
The system implements periodic sampling of air quality data rather than continuous monitoring, and adjusts air cleaning device operation in periodic cycles based on detected pollution levels. This allows the system to maintain air quality while reducing continuous high-intensity operation that generates noise, switching to lower-intensity or intermittent operation when pollution levels are acceptable
3Measurement precision
If the sampling frequency of air pollution detection is increased to ensure real-time monitoring, then the measurement accuracy is improved, but the power consumption and data processing load increase
Solution Approach 1:
The sampling frequency of gas detection modules is dynamically adjusted based on current air quality conditions and historical data trends. During periods of stable air quality, sampling frequency is reduced to conserve energy. When pollution levels change or exceed thresholds, sampling frequency automatically increases to provide more accurate real-time data, optimizing the balance between measurement precision and power consumption
4Area of stationary object
If multiple air cleaning devices are deployed to cover large indoor areas, then the cleaning coverage is improved, but the device complexity and installation cost increase
Solution Approach 1:
The large indoor space is divided into multiple monitoring zones, each with its own gas detection module and controlled by the central control device. This segmentation allows independent monitoring and control of different areas, enabling the system to scale coverage by adding modular units rather than deploying a complex monolithic system, thereby reducing overall system complexity while expanding coverage
Solution Approach 2:
The control device serves multiple functions: it collects data from multiple gas detection modules, processes air quality information, determines optimal device allocation, and controls multiple air cleaning devices. This multi-functionality reduces the need for separate specialized components for each function, simplifying the overall system architecture while maintaining large-area coverage capability
Data Source
AI summary
An indoor air cleaning method is disclosed and includes following steps: a. providing an indoor air cleaning system for performing air pollution detection and cleaning treatment in an indoor field; b. intelligently calculating and comparing based on a field air quality database to provide reference suspended particulate (PM) air quality data and determine a number of the air cleaning devices in the indoor field and a sampling cycle; c. confirming whether the gas state of the air pollution in the indoor field reaches a cleanliness requirement of clean room level ZAPClean room 6+, 7+, 6, 7, 6− or 7−; d. determining the optimal number of the air cleaning devices and the sampling cycle to implement air pollution cleaning treatment; and e. testing a verification of the air pollution data in the indoor field, and providing the verification for a third-party testing unit to test.