16 results about "Air pollutant concentrations" patented technology

The invention relates to the technical field of intelligent traffic and Internet of Vehicles, in particular to a traffic and air pollution bidirectional coupling flow prediction method based on double-path dynamic fusion. Comprising the following steps: collecting traffic flow and air pollutant concentration data, and carrying out space-time alignment and reversible instance normalization; the data is divided into two branches, the first branch extracts time-dependent features through gated convolution and probability sparse self-attention, and the second branch obtains variable interaction features through dimension remodeling, context extraction and reversible coupling transformation; bidirectional feature interaction is carried out through cross attention, weights are dynamically generated based on channel attention, and residual connection is carried out after weighted fusion; and performing linear mapping and inverse normalization on the fused features to obtain a traffic flow predicted value. According to the method, the prediction precision and robustness in a pollution sensitive scene are remarkably improved.

The embodiment of the invention provides an environment data processing method, device and equipment. The method comprises the following steps: acquiring a plurality of environment data packets of each preset grid of a target area in a target time period; wherein each environment data packet comprises at least one kind of air pollutant concentration data collected by the vehicle; for each preset grid, determining initial environment data of the preset grid in the target time period according to the air pollutant concentration data in the environment data packet of the preset grid in the target time period; acquiring environment monitoring data of an environment monitoring station to which the preset grid belongs in a target time period; based on the environment monitoring data of the target time period, performing correction processing on the initial environment data of the preset grid in the target time period to obtain target environment data of the preset grid in the target time period; and determining an environment pollution area of the target area according to the target environment data of each preset grid in the target time period. The method is used for achieving the effect of improving the accuracy of the environmental data.

The invention discloses an air pollutant concentration prediction method and device, equipment and a medium, and relates to the technical field of deep learning, and the method comprises the steps: obtaining site monitoring data and site longitude and latitude, carrying out the missing value filling and normalization processing of the site monitoring data, obtaining a time sequence, and constructing a geographic relation graph; performing trend feature extraction and feature processing on the time sequence by using an exponential moving average method and based on a gating circulation unit to obtain trend component features; performing periodic feature extraction on the time sequence; performing batch normalization processing, function activation and vector splicing on the noise sequence to obtain noise component features; splicing and fusing the trend component feature, the periodic component feature and the noise component feature to obtain a first prediction feature; solving and coding the time sequence to obtain a second prediction feature; and performing gating fusion and graph attention fusion on the first prediction feature and the second prediction feature based on a geographic relation graph to obtain an air pollutant concentration prediction result.

The invention provides a welding fume collecting device which comprises a pipeline truss arranged on a ship body; the first walking mechanism is connected to the pipeline truss in a sliding mode and slides along the pipeline truss in a reciprocating mode; the second walking mechanism is connected to the pipeline truss in a sliding mode, the second walking mechanism and the first walking mechanism are arranged in a spaced mode, and the second walking mechanism slides along the pipeline truss in a reciprocating mode; the environment detection assembly is connected to the first walking mechanism and used for detecting the concentration of pollutants in the air; the dust collection pipeline is connected to the second walking mechanism; and the purification mechanism is connected with the dust collection pipeline and used for absorbing pollutants through the dust collection pipeline and purifying the pollutants. The device is suitable for purifying regional welding fume with unfixed operation points.

A graph attention network-bidirectional recurrent interpolation network (GAI-BRI)-based air pollutant concentration interpolation prediction method, a device, and a medium. The method comprises: on the basis of the extracted air pollutant concentrations, meteorological data and satellite data from multiple distributed sites within a given time range and region, constructing an air pollutant concentration map for describing pollutant conditions within the given time range and region; and inputting numerical values in the air pollutant concentration map into a GAT-BRI prediction model to obtain an air pollutant concentration interpolation prediction result for a future time period, wherein the GAT-BRI prediction model comprises a GAT that is arranged at the bottom layer and used for extracting spatial features from the air pollutant concentration map, a BRI that is arranged at the middle layer and used for extracting temporal features from the spatial features outputted by the GAT, and a feedforward network that is arranged at the top layer and used for outputting an interpolation prediction result. The method fully exploits the spatial and temporal dependencies among multiple cities, achieving high prediction accuracy.

The present disclosure relates to a method, device and electronic equipment for determining a monitoring station position, the method comprising: obtaining first meteorological information and first concentration information of an air pollutant of N target sub-regions at T time, and second meteorological information and second concentration information of an air pollutant of M preset sub-regions at T time; determining the concentration information of the air pollutant of a second target sub-region at a first time according to the first meteorological information and the first concentration information; determining the concentration information of the air pollutant of a first target sub-region at the first time according to the second meteorological information and the second concentration information; and determining a monitoring station of the air pollutant from the N target sub-regions according to the concentration information of the air pollutant of the N target sub-regions at the first time. Through the above technical solution, the influence of the air pollutant outside the target region on the boundary is considered, and the accuracy and rationality of the determined monitoring station are improved.

The application discloses a range hood purification control method and device and a range hood, and belongs to the technical field of kitchen appliances. The method comprises the following steps: acquiring the working state of the range hood; in the case that the working state is a start-up state, acquiring the air pollutant concentration at the current time and predicting the change trend of the air pollutant concentration at a future target time; and controlling the operation mode of the auxiliary air purification device according to the air pollutant concentration at the current time and the change trend. The application further acquires the air pollutant concentration at the current time and predicts the change trend of the pollutant concentration at the future target time in the start-up state, realizes dynamic perception and prediction of the kitchen air quality, makes the purification function no longer dependent on manual operation or fixed timing of the user, but matches the generation rule and diffusion trend of pollutants in the actual cooking process, thereby reducing the technical problem that the purification function is disconnected from the real demand, and improving the air purification effect of the kitchen environment.

This invention discloses a quasi-bi-weekly lifecycle identification method for air pollution based on Fourier filtering, comprising the following steps: S1, acquiring daily observation data of air pollutant concentrations in the target area, and screening and confirming periods where pollutant concentrations continuously exceed a threshold as independent pollution events; S2, performing Fourier transform on the daily observation data and calculating the power spectrum to verify the existence of a significant quasi-bi-weekly periodic signal; S3, based on the confirmation of a significant quasi-bi-weekly periodic signal, performing Fourier filtering on the original concentration sequence to extract the quasi-bi-weekly scale component sequence; S4, for each pollution event, performing phase localization to achieve quasi-bi-weekly lifecycle identification of pollutant events. This invention can objectively extract oscillation signals at the quasi-bi-weekly scale and accurately determine the phase of a single pollution event within its quasi-bi-weekly cycle, thereby achieving quantitative identification of its lifecycle.

The invention relates to a method for determining individual air pollutant levels in specific regions using an electronic device (30) with a processor (32). The method comprises the following steps: - Calculating an individual respiratory volume of a person taking into account the duration of stay and mode of movement of the person in a measurement region (22, 24), - Obtaining a prevailing air pollutant concentration in the measurement region (22, 24) via a network, - Determining the individual air pollutant exposure of the person, taking into account the calculated individual breathing volume and the obtained air pollutant concentration, - Output of a signal based on the individual air pollution level.

The present application relates to the technical field of intelligent transportation and Internet of Vehicles, in particular to a traffic and atmospheric pollution two-way coupling flow prediction method based on double-path dynamic fusion. The method comprises the following steps: collecting traffic flow and air pollutant concentration data, and performing spatio-temporal alignment and reversible instance normalization; dividing the data into two branches, extracting time-dependent features through gated convolution and probabilistic sparse self-attention in the first branch, and obtaining variable interaction features through dimension reshaping, context extraction and reversible coupling transformation in the second branch; performing two-way feature interaction through cross-attention, dynamically generating weights based on channel attention, and performing residual connection after weighted fusion; linearly mapping the fused features and performing inverse normalization to obtain traffic flow prediction values. The present application significantly improves the prediction accuracy and robustness in pollution-sensitive scenarios.

The invention relates to the technical field of intelligent control, and discloses an air purification equipment control method and device, air purification equipment and a medium. After entering a set purification operation time period, a target gear is determined by obtaining the total amount of pollutants in a current closed area and combining the first duration needed by purification of the highest gear; and after a first preset operation duration, the total amount of pollutants is updated, a second duration is calculated, and the gear is updated circularly until the cut-off moment. Therefore, through dynamic and staged gear regulation and control, resource waste or insufficient purification caused by traditional fixed gear operation is avoided. And by matching the total amount of pollutants and the purification gear in real time, rapid purification at a proper gear during high pollution is ensured, timely adjustment can be performed after the pollutants are reduced, the optimal purification efficiency is realized in the purification operation time period, the problem that the concentration of the air pollutants still exceeds the standard after purification is avoided, the actual air purification requirement of a user is met, and the user experience is improved. The purification effect and energy consumption optimization are considered, and resource waste is avoided.

Embodiments of the present disclosure provide a machine learning correction method based on low-cost atmospheric particulate matter sensor measurement, applied to the technical field of meteorological data processing. The method comprises obtaining a CSV file of low-cost atmospheric particulate matter sensor measurement data, and performing data preprocessing and feature engineering to construct an input feature set; dividing the input feature set into a training set and a test set according to the site identification in the CSV file; based on the preset model parameters, using the DART-LightGBM model, performing training according to the training set and early stopping with the early stopping set, evaluating on the test set, and saving the trained air pollutant concentration correction model, performing feature importance analysis and multi-dimensional evaluation on the model; and outputting deployment support files including a site mapping file and a feature list file. Based on this, the DART-LightGBM model can be trained and output, the site mapping and the feature list can be formed, and a closed-loop process from preprocessing to deployment is formed, which is convenient for consistent deployment of multiple sites.

The invention relates to a method and device for determining the position of a monitoring station, and electronic equipment, and the method comprises the steps: obtaining the first meteorological information of N target sub-regions at T time, and the first concentration information of air pollutants, obtaining second meteorological information and second concentration information of air pollutants of the M preset sub-regions at the T moment; according to the first weather information and the first concentration information, determining air pollutant concentration information of the second target sub-region at the first moment; according to the second weather information and the second concentration information, determining air pollutant concentration information of the first target sub-region at the first moment; and according to the air pollutant concentration information of the N target sub-regions at the first moment, determining air pollutant monitoring stations from the N target sub-regions. According to the technical scheme, the influence of air pollutants outside the target area on the boundary is considered, and the accuracy and rationality of the determined monitoring site are improved.

The invention relates to an atmospheric pollutant concentration monitoring and early warning method and system, and belongs to the technical field of environmental protection informatization and environmental pollution prevention and control. The system comprises a multivariate data acquisition module, an analysis and early warning module, a linkage control module and a remote monitoring platform; the multivariate data acquisition module comprises an infrared spectrum absorption type gas sensor, an electrochemical gas sensor, a temperature and humidity sensor and a wind speed and direction sensor, and the multivariate data acquisition module is deployed in a monitoring area in a distributed manner and is used for acquiring pollutant concentration and environmental data. According to the invention, comprehensive and accurate monitoring can be realized, through cooperation of multi-principle sensors and dynamic weight fusion, limitation of a single sensor is overcome, accurate and reliable monitoring of multiple pollutants in a full concentration range is realized, monitoring blind areas are significantly reduced, advanced early warning and efficient closed-loop management and control can be realized, and the system has good application prospects. And the speed and the accurate management and control capability of the environmental pollution emergency response are greatly improved.

The application belongs to the technical field of air pollution assessment, and relates to a city air pollutant change range assessment and ranking method and system, the method comprising: 1) obtaining multiple city air pollutant concentrations in different time dimensions and standardizing the air pollutant concentrations; 2) performing multi-dimensional time series analysis on the air pollutant concentrations to obtain multi-dimensional time series analysis results; 3) calculating the comprehensive score of each city according to the air pollutant concentrations and the multi-dimensional time series analysis results; 4) calculating the dynamic assessment score of each city and dynamically ranking the multiple cities according to the dynamic assessment score; and 5) assessing the change range of the pollutant concentration of each city and ranking the multiple cities according to the multi-dimensional time series analysis results and the change range to obtain the risk level of each city. The application is evaluated based on multi-dimensional time series analysis results and dynamic weights, and the evaluation results are comprehensive and accurate.

The application discloses a multistage waste gas purification device, and belongs to the technical field of waste gas purification, which comprises a spraying tower, an air inlet pipe and an air outlet pipe, a liquid storage cavity is arranged on one side of the spraying tower, a variable speed water pump is arranged between the liquid storage cavity and the spraying tower, a gas quality sensor is arranged in the air inlet pipe, a spraying main pipe is rotatably connected to the bottom end of a spraying frame, a hydraulic drive mechanism for driving the spraying main pipe to rotate is arranged on the spraying frame, the output end of the variable speed water pump is communicated with the hydraulic drive mechanism, a plurality of spraying mechanisms are arranged in the spraying main pipe from top to bottom, the spraying mechanisms are respectively communicated with the spraying main pipe, an adjusting piston is slidably arranged in the spraying main pipe, and a centrifugal self-adjusting drive mechanism for driving the adjusting piston to slide along the spraying main pipe is arranged at the bottom end of the spraying main pipe. The multistage waste gas purification device can monitor the concentration of air pollutants, and a plurality of spraying mechanisms are arranged, the spraying liquid flow and spraying levels are automatically adjusted according to the concentration of waste gas pollutants.