6 results about "Air quality index" patented technology

This invention provides a method for filtering air quality forecast results based on sliding optimal matching, relating to the fields of environmental air quality forecasting and data science technology. The method includes: acquiring multiple predicted air quality index data obtained from various air quality prediction models; acquiring multiple measured air quality index data at multiple times within a past first preset time period; setting a time window; filtering target air quality prediction models from among the multiple air quality prediction models; and obtaining air quality index forecast data. According to this invention, predicted air quality index data and measured air quality index data can be acquired, and error statistics can be performed based on the time window to filter target air quality prediction models. The sliding optimal matching algorithm enables real-time evaluation and automatic filtering of model performance, overcoming the technical bottlenecks of traditional manual operation and static integration, improving the real-time performance and efficiency of air quality prediction model filtering, and providing high-precision and high-efficiency forecast support.

The application discloses an intelligent operating room air quality prediction and supervision system based on AI empowerment, which comprises a multidimensional data perception layer, an AI analysis engine and an intelligent supervision platform. The multidimensional data perception layer comprises a particle monitoring network and a parameter acquisition module. The particle monitoring network is arranged in layers around the operating bed to collect multi-particle size particle concentration data through sensors. The parameter acquisition module acquires environmental parameters. The AI analysis engine comprises a time series database, a multi-factor correlation analysis model and a prediction and early warning module. The time series database constructs a four-dimensional data storage structure. The multi-factor correlation analysis model establishes the correlation between the air quality index and the environmental parameters. The prediction and early warning module predicts the particle concentration trend based on the four-dimensional data storage structure and triggers a hierarchical early warning. The intelligent supervision platform generates control instructions according to the hierarchical early warning and collects data to optimize the model. The application realizes accurate prediction, active control and closed-loop optimization of the air quality in the operating room, and improves the control efficiency and medical safety.

This application relates to an air conditioning control method, device, air conditioning equipment, and storage medium. It involves periodically collecting indoor environmental parameters and outdoor temperature; calculating indoor heat load and indoor air quality index based on the indoor environmental parameters; determining the indoor heat load state based on the indoor heat load and a corresponding first preset value; determining the indoor air quality state based on the air quality index and a corresponding second preset value; and comparing the indoor temperature with the outdoor temperature to obtain a comparison result. Based on the indoor heat load state, indoor air quality state, and comparison result, it performs coordinated control of the air conditioner and the corresponding fresh air system. Therefore, while accurately ensuring indoor thermal comfort and air health, it minimizes energy waste caused by blindly introducing fresh air or excessive cooling in energy-saving air conditioning systems, achieving synergistic optimization of thermal comfort, air quality, and operating energy consumption.

This invention provides a method and system for zoned ventilation control of ventilated curtain walls, relating to the field of air conditioning and ventilation control technology. The invention divides the ventilated curtain wall area into several monitoring zones, collecting real-time data on air temperature, humidity, carbon dioxide concentration, temperature difference, wind speed, air volume, solar irradiance, fan power, and energy consumption parameters. It calculates air quality index, air-temperature synergy optimization index, and energy efficiency index. For unqualified or abnormal zones, it automatically generates ventilation enhancement strategies, adaptive ventilation adjustment strategies, and fan optimization strategies. Through multi-parameter correlation analysis, it establishes zoned temperature field and airflow models, identifies abnormal zones, and generates optimized operation and maintenance strategies, achieving balanced air quality, optimized ventilation effect, and energy consumption control. This system can be used in applications involving air conditioning, humidification, ventilation, and airflow as a shield, improving indoor environmental comfort and energy efficiency.

The proposed solution refers to an air quality prediction system based on data from Internet of Things (IoT) sensors. The system comprises a data collection layer with IoT sensor stations to acquire particulate matter, temperature, and humidity data; a transmission layer to relay environmental data messages; a data reception and processing layer to analyze messages and record data into a time-series database; a storage and visualization layer to store, query, and display data; and an analysis and forecasting layer to exploit historical data using forecasting models to generate Air Quality Index (AQI) forecasts. The AQI forecast results are provided to the user interface to support monitoring current air quality and future air quality trends.

This invention relates to the field of urban governance assessment and decision-making technology, specifically to an intelligent assessment and decision support system and method for urban governance based on machine learning. It includes collecting various governance data to obtain an indicator summary table, extracting the proportional relationships of the indicators to form a probability distribution map, connecting the probability item nodes to obtain a governance deduction chain, dividing the summary table into segments to obtain a level interval table, and finally combining the deduction chain and the interval table for corresponding identification to output the intelligent assessment results of urban governance. This invention unifies the scaling of traffic congestion index, air quality index, public service completion rate, and public security incident frequency, and performs indicator merging to form a consistent set of governance indicators. Based on the proportional relationships of the indicators, a probability distribution structure is constructed, forming a sequentially connected governance deduction chain. Simultaneously, governance level intervals are established by combining the indicator segment distribution, thus establishing a correspondence between the urban governance status and the indicator intervals.