13 results about "Air quality management" patented technology

The invention provides a vehicle air quality management system comprising an air quality detection device which is configured to be suitable for detecting the air quality in a front cabin and the air quality in a passenger cabin of a vehicle; the front cabin ventilation module is configured to be suitable for executing ventilation operation on the interior of the front cabin; the passenger compartment ventilation module is configured to be suitable for executing ventilation operation on the interior of the passenger compartment; and the control device is configured to be suitable for controlling operation of the front cabin ventilation module and / or the passenger cabin ventilation module based on a detection result of the air quality detection device. According to the embodiment of the invention, flammable harmful gases such as propane and the like can be monitored and responded properly in real time aiming at the front cabin and the passenger cabin respectively, the concentration of harmful gases in the front cabin and the passenger cabin is reduced, and the vehicle use safety of a driver and passengers is guaranteed. The invention further provides a corresponding vehicle air quality management method, a computer program product and a vehicle.

The invention belongs to the technical field of environmental protection, and relates to a pollutant emission reduction and concentration response fitting and optimization regulation method and system, and the method comprises the steps: S1, collecting pollutant data and meteorological data of a target region in real time; s2, based on the data, determining a response relationship between emission reduction of precursors in the pollution source and concentration change of pollutants in the air by utilizing a method of combining machine learning and numerical simulation; s3, when the concentration of the pollutants in the air exceeds a threshold value, an air quality optimization regulation and control model is started, and the air quality optimization regulation and control model takes minimization of the total cost of emission reduction as a target function and takes an air quality improvement target as a constraint condition; s4, the air quality optimization regulation and control model is solved through an optimization algorithm, and an optimal emission reduction proportion scheme is obtained; and S5, executing corresponding emission reduction control measures according to the optimal emission reduction proportion scheme. According to the method, accurate prediction and efficient regulation and control of atmospheric pollutants can be realized, the air quality management efficiency is remarkably improved, and the treatment cost is reduced.

1. The name of the design product: air quality management graphical user interface of electronic equipment. 2. The use of the design product: an electronic device. 3. The design points of the design product: the interface content of the graphical user interface in the electronic equipment. 4. The picture or photo that best indicates the design points: design 1 front view. 5. Design 1 is designated as the basic design. 6. The use of the graphical user interface: the graphical user interface is used for users to view real-time air quality data and statistical information of air quality changes in the room. 7. The human-computer interaction mode of the graphical user interface: design 1 front view and design 2 front view are air quality management interfaces, which are used to display air quality information. Design 3 front view is an air quality management interface. The user slides the screen at the right end of design 3 front view to the left, and the interface is switched to design 3 interface change state diagram. At this time, the user can select to switch to view the air quality information of other room equipment on this interface.

The invention provides a fresh air system control method and device and a computer readable storage medium. According to the scheme, under the condition that a fresh air system is started, the number of people, the carbon dioxide concentration, the formaldehyde concentration and the current fresh air ventilator frequency in the current environment are obtained; target air supply volume is determined based on the number of personnel, and initial fresh air ventilator frequency is determined according to the target air supply volume and the current fresh air ventilator frequency; under the condition that the carbon dioxide concentration is larger than a first concentration threshold value and / or the formaldehyde concentration is larger than a second concentration threshold value, the target fresh air ventilator frequency is determined based on the carbon dioxide concentration, the formaldehyde concentration and the initial fresh air ventilator frequency, and the first concentration threshold value and the second concentration threshold value are set based on the human health comfort degree index; and a fresh air ventilator of the fresh air system is controlled based on the target fresh air ventilator frequency. According to the scheme, the problem that in the prior art, the air quality management efficiency of a fresh air system is low is solved.

The invention relates to the technical field of atmospheric environment monitoring, in particular to an air quality index prediction method and system based on decomposition and recombination. According to the method, a multi-source data matrix is constructed by acquiring air quality data and meteorological observation data of a target area; channel decomposition is carried out based on a CEEMDAN decomposition algorithm, through a least square method, channel components are listed, channel component prediction is carried out by adopting a random forest model or a CNN-BiLSTM-Attention model to obtain a weight combination set, the channel component prediction error sum of squares of each weight combination is calculated, an optimal weight parameter is obtained, and the optimal weight parameter is obtained; and performing component prediction on each channel component in the multi-channel component data set to obtain prediction component data of each channel, and summing the prediction component data of each channel to obtain a final air quality index prediction result. A new view angle and method are provided for the field of AQI prediction, and a prediction method which is more accurate, stable in performance and universally applicable is provided for air quality management.

The application provides an intelligent air quality management method and system for an ammonia production plant, which monitors the oxygen concentration and ammonia concentration in the ammonia production plant through a gas monitoring unit; compares the oxygen concentration and ammonia concentration with preset oxygen concentration safety threshold and ammonia concentration safety threshold through a control unit, generates and issues a control instruction according to the comparison result, so as to control the oxygen production unit and the ventilation circulating unit in the ammonia production plant to operate according to the corresponding load of the control instruction; and connects a lightweight breathing terminal with the oxygen output interface of the oxygen production unit, uses the lightweight breathing terminal to obtain oxygen, realizes the establishment and maintenance of a dynamic balance system for the oxygen and ammonia concentrations in the ammonia production plant within the preset safety threshold range, and provides a convenient, sustainable and non-dependent mobile gas cylinder continuous oxygen supply mode for the staff in the ammonia gas leakage emergency state.

The invention discloses an air quality monitoring and purification regulation and control system and method based on a sensor network, and relates to the technical field of environmental data monitoring processing and intelligent control. According to the invention, environmental data are collected through a heterogeneous sensor network, and abnormal values are cleaned; constructing a dynamic air flow field directed weighted graph based on time sequence correlation among sensor nodes, and reconstructing a global air quality thermodynamic diagram and positioning a pollution source by using a flow field corrected Kriging algorithm; introducing a graph neural network to construct a prediction model, and combining historical and real-time data to predict a future air quality trend; based on a prediction result, solving a dynamic cost function containing multiple targets of quality, energy consumption and noise by using a quadratic programming algorithm to obtain an optimal control sequence; fresh air, a purifier and doors and windows are cooperatively dispatched to execute strategies such as positive pressure blocking or negative pressure pollution discharge; according to the method, the problems that blind areas exist in traditional monitoring, control response lags behind and equipment lacks collaboration are solved, and active and comfortable air quality management based on prediction is achieved.

The invention discloses an intelligent management method, device and equipment for the air quality of a refrigeration house and a storage medium, and relates to the technical field of cold-chain logistics environment monitoring. The intelligent management system for the air quality of the refrigeration house comprises a multi-mode smell sensing module, a dynamic pollution modeling and tracking module, an intelligent regulation and control module and a tail gas purification module which are connected with one another; the refrigeration house air quality intelligent management system is integrated with the refrigeration house control system; the method comprises the steps that gas concentration data and environment parameters, collected by the multi-mode smell sensing module, in the refrigeration house are obtained; preprocessing the gas concentration data and the environmental parameters to obtain preprocessed data; constructing a three-dimensional concentration field based on the preprocessed data, predicting a pollution diffusion trend and positioning a pollution source to obtain a pollution source positioning result; according to the pollution source positioning result and the pollution diffusion trend, directional ventilation is conducted on the refrigeration house, the storage period of objects in the refrigeration house is prolonged by precisely regulating and controlling gas components, and the precision of air quality management is improved.

The invention relates to the field of sand and dust prediction, in particular to a sand and dust aerosol concentration prediction method based on a Transform graph, which comprises the following steps: collecting and preprocessing multi-source sand and dust related data, and constructing a feature set; a graph structure is constructed based on spatial distribution of monitoring sites, and a self-adaptive gating feature enhancement module and a global representation learning module for spatial relationship perception are developed for sand and dust characteristic differences of different regions and seasons; the method comprises the following steps: designing a graph Transform encoder and a time sequence enhancement decoder, and constructing a graph Transform; and designing a comprehensive loss function to optimize the model to obtain an optimal model for predicting the dust aerosol concentration. According to the invention, through the organic fusion of the graph structure modeling and the Transform architecture, the spatial dependence characteristic and the time sequence evolution characteristic of the sand and dust transmission can be captured at the same time, the accuracy and the stability of the sand and dust aerosol concentration prediction are improved, the calculation efficiency is optimized, an effective basis is provided for environment monitoring and air quality management, and the method is suitable for popularization and application. The method is of great significance in improving the sand and dust disaster early warning capability and reducing the sand and dust weather influence.

The invention relates to the technical field of ozone concentration prediction, and discloses an urban ozone concentration prediction method based on a multiple linear regression model. The method comprises the following steps: collecting gas parameter data and meteorological parameter data of a preset urban area and constructing a first time sequence characteristic matrix; dividing the first time sequence characteristic matrix into a second time sequence characteristic matrix corresponding to a night static stable period, a morning climbing period, a noon photochemical active period and a dusk subduction period on the basis of a daily change rule of the solar radiation intensity, and solving a partial regression coefficient vector of each period; and obtaining a partial regression coefficient vector and a third time sequence characteristic matrix corresponding to a time period to which the to-be-predicted moment belongs, and performing multiple linear regression operation on the third time sequence characteristic matrix based on the partial regression coefficient vector to obtain an ozone concentration predicted value. According to the method, time-phased high-precision prediction of the urban ozone concentration is realized, and scientific support is provided for urban air quality management and environmental protection policy formulation.

The application discloses a satellite ground measurement data and communication signaling fusion air pollution exposure assessment method. In a unified space-time framework, a regular space grid system and a unified time axis are constructed; multi-source environmental data are collected and preprocessed, a high space-time resolution multi-pollutant concentration field is constructed through a machine learning model; communication operator signaling data are acquired and processed, a user time-activity pattern is constructed through a stay point identification, a residence / work place determination and a path interpolation; individual exposure is calculated by fusing the concentration field and the activity trajectory, a dose-type exposure index is calculated by introducing an activity intensity mapping respiratory rate, a multi-pollutant comprehensive exposure index is constructed and multi-time scale statistical analysis is carried out, and an exposure result confidence interval is acquired through uncertainty modeling and Monte Carlo simulation. The application can finely depict a real exposure process of a population, support multi-pollutant collaborative exposure assessment, and provide a scientific basis for environmental health risk assessment and fine air quality management.

The invention discloses an in-vehicle air quality adjusting method and system and electric equipment, and the method comprises the steps that the driving stage of a vehicle is determined according to the running state of the vehicle and / or the intention of a user; and according to the driving stage and the multi-source environment information, an air quality adjusting strategy corresponding to the driving stage is executed. According to the method, through dynamic division of the driving stages and multi-source environment information fusion, air quality management covering the whole life cycle of vehicle operation is achieved, the real-time performance and the intelligent level of air quality adjustment are achieved, and the health and the comfort level of a user are enhanced. The method has the remarkable advantages in the aspects of real-time responsiveness, user experience, the system intelligence level and the like, and the adaptability of the in-vehicle air quality adjusting method to different driving scenes and the driving comfort degree are greatly improved.

This invention belongs to the field of environmental protection technology and relates to a method and system for fitting and optimizing pollutant emission reduction and concentration response. The method includes: S1: Real-time collection of pollutant data and meteorological data of the target area; S2: Based on the data, using a combination of machine learning and numerical simulation, determining the response relationship between the reduction of precursors in the pollution source and changes in the concentration of pollutants in the air; S3: When the concentration of pollutants in the air exceeds a threshold, activating the air quality optimization and control model, which takes minimizing the total cost of emission reduction as the objective function and achieving the air quality improvement target as the constraint; S4: Solving the air quality optimization and control model using an optimization algorithm to obtain the optimal emission reduction ratio scheme; S5: Implementing corresponding emission reduction control measures according to the optimal emission reduction ratio scheme. This method can achieve accurate prediction and efficient control of air pollutants, significantly improving air quality management efficiency and reducing treatment costs.