A health guidance system considering the impact of air pollution on user travel

Abstract

The present invention provides a health induction system for user travel taking into account the impact of air pollution, and relates to the technical field of travel induction. The system comprises: obtaining historical air pollution data of a user's travel area according to current user travel needs and performing data aggregation processing; obtaining historical user travel data and current user travel data to determine the user's travel mode in the current period; constructing an air pollution prediction model and performing model training according to the data aggregation processing result, inputting the user's current travel data and travel mode into the air pollution prediction model after model training, and predicting the current air pollution data of the user's travel area; performing risk assessment on the current air pollution data according to the user's travel health needs, planning the user's current travel route according to the risk assessment result, and generating travel health suggestions for the user; and effectively ensuring the health of the user when traveling.

Description

Technical Field

[0001] The present invention relates to the technical field of travel induction, and in particular to a health induction system for users' travel taking into account air pollution. Background Art

[0002] Users' exposure to air pollution during travel will affect their health; however, existing travel planning mainly considers users' travel distance and speed, and lacks consideration for users' travel health; in addition, different groups of people have different sensitivities to air pollution, and users' exposure to air pollution levels under different travel modes are also different.

[0003] Therefore, the present invention provides a health induction system for users' travel taking into account air pollution. Summary of the invention

[0004] The present invention provides a health induction system that takes into account the impact of air pollution on user travel, by obtaining historical air pollution data of a user's travel area according to current user travel needs and performing data aggregation processing; obtaining the user's historical travel data and the user's current travel data to determine the user's travel mode in the current period; constructing an air pollution prediction model and performing model training according to the data aggregation processing result, inputting the user's current travel data and travel mode into the air pollution prediction model after model training, and predicting the current air pollution data of the user's travel area; performing risk assessment on the current air pollution data according to the user's travel health needs, planning the user's current travel route according to the risk assessment result and generating travel health recommendations for the user; and effectively ensuring the user's health when traveling.

[0005] The present invention provides a health guidance system for users' travel taking into account the impact of air pollution, including:

[0006] The air pollution data module is used to obtain the historical air pollution data of the user's travel area according to the current user's travel needs and perform data aggregation processing;

[0007] The user travel mode module is used to obtain the user's historical travel data and the user's current travel data to determine the user's travel mode in the current period;

[0008] The air pollution prediction module is used to build an air pollution prediction model and train the model based on the data aggregation and processing results. The user's current travel data and travel mode are input into the trained air pollution prediction model to predict the current air pollution data of the user's travel area.

[0009] The travel health induction module is used to conduct risk assessment on current air pollution data according to the user's travel health needs, plan the user's current travel route according to the risk assessment results and generate travel health recommendations for the user.

[0010] According to the present invention, a health induction system considering the impact of air pollution on user travel, an air pollution data module, includes:

[0011] A user travel demand unit, used to obtain the current user travel demand according to user input data, wherein the user input data includes: travel starting point data, travel way point data and travel destination data;

[0012] A travel area unit is used to determine the user's current travel area based on the user's current travel demand and the user's travel deviation;

[0013] The historical air pollution data unit is used to select the data source of air pollution data, obtain the historical air pollution data of the user's current travel area and perform data aggregation processing.

[0014] According to the present invention, a health induction system considering the impact of air pollution on user travel is provided, and the user travel mode module includes:

[0015] A travel data unit is used to obtain the user's historical travel data, wherein the user's historical travel data includes: historical travel time data, historical travel mode data and historical travel route data;

[0016] Acquire the user's current travel data, wherein the user's current travel data includes: current travel time data, current travel mode data, and current travel demand data;

[0017] A travel mode unit, used to extract historical travel features of the user's historical travel data and determine the user's travel mode;

[0018] The user's current travel data is matched with the user's travel mode to determine the user's travel mode in the current period.

[0019] A health induction system considering the impact of air pollution on user travel provided by the present invention also includes:

[0020] A data encryption unit, used for performing data encryption processing when obtaining the user's historical travel data and obtaining the user's current travel data;

[0021] A data elimination unit, used for performing data elimination processing on the user's historical travel data before extracting the historical travel features of the user's historical travel data;

[0022] The current travel distance corresponding to the user's current travel data is obtained, and the user's historical travel data whose historical travel distance is not longer than the current travel distance is removed.

[0023] According to the present invention, a health induction system considering the impact of air pollution on user travel, an air pollution prediction module, includes:

[0024] An air pollution prediction model unit is used to select a prediction model, construct an air pollution prediction model, and perform model training on the air pollution prediction model according to the data aggregation and processing results, wherein the prediction model includes: a linear regression prediction model, a random regression prediction model, and a neural network prediction model;

[0025] A model training and evaluation unit, used to randomly extract historical travel data of users from the data aggregation and processing results to evaluate the prediction performance of the air pollution prediction model after model training;

[0026] When the prediction performance of the air pollution prediction model after model training is not lower than the preset prediction performance, the model training is determined to be completed;

[0027] The air pollution prediction unit is used to input the user's current travel data and travel mode into the air pollution prediction model after model training, and predict the current air pollution data of the user's travel area.

[0028] According to the present invention, a health induction system for users' travel considering the effects of air pollution on their travel is provided, and a travel health induction module includes:

[0029] A user travel health demand unit is used to obtain user health data and determine the user's travel health demand, wherein the user health data includes: user age data, user gender data and user health status data;

[0030] A risk assessment unit is used to conduct a risk assessment on the current air pollution data according to the user's travel health needs, and determine the risk level of the user's current travel area, where the risk levels include: low risk level, medium risk level and high risk level;

[0031] A travel route unit is used to set a route planning target for the user's current travel route according to the user's travel health needs and the current user's travel needs, wherein the route planning targets include: travel health planning targets, travel time planning targets, travel mode planning targets, and travel distance planning targets;

[0032] Plan the user's current travel route according to the risk level of the user's current travel area and the route planning target of the user's current travel route;

[0033] The travel route optimization unit is used to set the risk assessment cycle and estimate the user's current travel speed based on the user's current route and travel mode;

[0034] According to the user's current travel speed and risk assessment period, the user's current travel route is divided into routes, the air pollution data of each section of the user's current travel route is re-predicted, and the risk level of each section of the user's current travel route is re-determined;

[0035] Optimize the user's current travel route in real time based on the re-determined risk level of each segment of the user's current travel route;

[0036] The user travel health suggestion unit is used to generate user travel health suggestions based on the user's current travel route optimized in real time.

[0037] A health induction system considering the impact of air pollution on user travel provided by the present invention also includes:

[0038] A travel visualization unit is used to visualize the user's current travel route and the user's travel health recommendations;

[0039] The travel route real-time update unit is used to visualize the optimization results and provide update prompts in real time when it is detected that the user's current travel route has been optimized.

[0040] A health induction system considering the impact of air pollution on user travel provided by the present invention also includes:

[0041] The travel warning module is used to obtain the risk level of the user's current travel route. When the risk level of the user's current travel route is monitored to be high, a travel warning notification is issued to the user.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] By obtaining the historical air pollution data of the user's travel area according to the current user's travel needs and performing data aggregation processing; obtaining the user's historical travel data and the user's current travel data to determine the user's travel mode in the current period; building an air pollution prediction model and training the model based on the data aggregation processing results, inputting the user's current travel data and travel mode into the trained air pollution prediction model to predict the current air pollution data of the user's travel area; conducting a risk assessment of the current air pollution data based on the user's travel health needs, planning the user's current travel route based on the risk assessment results and generating travel health recommendations for the user; effectively ensuring the user's health when traveling.

[0044] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0045] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0047] Figure 1 It is a structural schematic diagram of a health induction system for users' travel that takes into account the effects of air pollution, provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0049] Embodiment 1:

[0050] The embodiment of the present invention provides a health guidance system that considers the impact of air pollution on user travel. Figure 1 As shown, including:

[0051] The air pollution data module is used to obtain the historical air pollution data of the user's travel area according to the current user's travel needs and perform data aggregation processing;

[0052] The user travel mode module is used to obtain the user's historical travel data and the user's current travel data to determine the user's travel mode in the current period;

[0053] The air pollution prediction module is used to build an air pollution prediction model and train the model based on the data aggregation and processing results. The user's current travel data and travel mode are input into the trained air pollution prediction model to predict the current air pollution data of the user's travel area.

[0054] The travel health induction module is used to conduct risk assessment on current air pollution data according to the user's travel health needs, plan the user's current travel route according to the risk assessment results and generate travel health recommendations for the user.

[0055] In this embodiment, the current user travel demand refers to the user travel demand in the current period.

[0056] In this embodiment, the user travel area refers to the area where the user travels during the current period, that is, the area including the user's travel location.

[0057] In this embodiment, the historical air pollution data refers to the air pollution data of the user's travel area during a historical period.

[0058] In this embodiment, the user's historical travel data refers to the user's travel data during a historical period, such as the user's travel route data during a historical period.

[0059] In this embodiment, the user's current travel data refers to the user's travel data in the current period, such as the user's travel time data in the current period and the user's travel mode data in the current period.

[0060] In this embodiment, the travel mode of the user in the current time period refers to the travel method of the user in the current time period, such as walking travel method and car travel method.

[0061] In this embodiment, the travel modes mainly include: travel modes exposed to the air, such as walking travel mode and cycling travel mode; travel modes not exposed to the air, such as car travel mode and subway travel mode.

[0062] In this embodiment, the air pollution prediction model refers to a model used to predict air pollution.

[0063] In this embodiment, the current air pollution data refers to the air pollution data of the user's travel area in the current period predicted by the air pollution prediction model trained by inputting the user's current travel data and travel mode into the model.

[0064] In this embodiment, the current air pollution data of the user's travel area is predicted based on the air pollution prediction model, wherein the user's travel area predicted here mainly refers to predicting the air pollution data of a larger travel area as the current air pollution data of the user's travel area, and the area range of the larger travel area is determined according to the data source of the air pollution data. For example, the more data sources of air pollution data in the travel area, the smaller the travel area that can be accurately predicted can be, thereby realizing air pollution prediction for a small area.

[0065] In this embodiment, different travel modes correspond to different air pollution data, that is, the air pollution quality is different. For example, for travel modes exposed to the air, air pollution can be directly considered, while for travel modes not exposed to the air, such as subway travel, the corresponding air pollution data mainly considers the air pollution quality inside the subway.

[0066] In this embodiment, the user's travel health needs refer to the user's health needs when traveling, and different users have different travel health needs.

[0067] In this embodiment, risk assessment refers to an assessment of current air pollution data based on the user's travel health needs.

[0068] In this embodiment, the user's current travel route refers to the user's travel route in the current period determined according to the risk assessment result and the user's travel demand.

[0069] In this embodiment, the user travel health advice refers to the travel advice generated based on the user's current travel route and the corresponding current air pollution data.

[0070] The working principle and beneficial effects of the above technical solution are: by obtaining the historical air pollution data of the user's travel area according to the current travel needs of the user and performing data aggregation processing; obtaining the user's historical travel data and the user's current travel data to determine the user's travel mode in the current period; building an air pollution prediction model and training the model based on the data aggregation processing results, inputting the user's current travel data and travel mode into the air pollution prediction model after model training, and predicting the current air pollution data of the user's travel area; conducting a risk assessment of the current air pollution data according to the user's travel health needs, planning the user's current travel route according to the risk assessment results and generating travel health recommendations for the user; effectively ensuring the user's health when traveling.

[0071] Embodiment 2:

[0072] The embodiment of the present invention provides a health guidance system considering the impact of air pollution on user travel, and an air pollution data module, including:

[0073] A user travel demand unit, used to obtain the current user travel demand according to user input data, wherein the user input data includes: travel starting point data, travel way point data and travel destination data;

[0074] A travel area unit is used to determine the user's current travel area based on the user's current travel demand and the user's travel deviation;

[0075] The historical air pollution data unit is used to select the data source of air pollution data, obtain the historical air pollution data of the user's current travel area and perform data aggregation processing.

[0076] In this embodiment, the user input data refers to data manually input by the user.

[0077] In this embodiment, the user travel deviation refers to a route deviation that may occur during the user's travel.

[0078] In this embodiment, the user's current travel area refers to the area where the user travels during the current period, which is determined based on the current user's travel demand and the user's travel deviation.

[0079] In this embodiment, the user's current travel area is determined based on the user's current travel needs and the user's travel deviation, so as to effectively ensure health guidance for the user and avoid errors in health guidance caused by user deviations.

[0080] In this embodiment, the air pollution data refers to data representing air pollution, such as data on the concentration of pollutants in the air.

[0081] In this embodiment, the data source of the air pollution data refers to the source from which the air pollution data is obtained, for example, the air pollution data is obtained from public data of an air quality monitoring station.

[0082] In this embodiment, the historical air pollution data refers to the air pollution data of the user's current travel area in a historical period obtained according to a data source of the air pollution data.

[0083] The working principle and beneficial effect of the above technical solution are: by obtaining the historical air pollution data of the user's travel area according to the current user's travel needs and aggregating the data, a data foundation is laid for the subsequent realization of travel health induction.

[0084] Embodiment 3:

[0085] The embodiment of the present invention provides a health guidance system for user travel considering the impact of air pollution on user travel, and a user travel mode module, including:

[0086] A travel data unit is used to obtain the user's historical travel data, wherein the user's historical travel data includes: historical travel time data, historical travel mode data and historical travel route data;

[0087] Acquire the user's current travel data, wherein the user's current travel data includes: current travel time data, current travel mode data, and current travel demand data;

[0088] A travel mode unit, used to extract historical travel features of the user's historical travel data and determine the user's travel mode;

[0089] The user's current travel data is matched with the user's travel mode to determine the user's travel mode in the current period.

[0090] In this embodiment, the user's historical travel data refers to the user's travel data during a historical period.

[0091] In this embodiment, the user's current travel data refers to the user's travel data during the current period.

[0092] In this embodiment, the historical travel features refer to features obtained by extracting features from historical travel data, and are used to simplify the representation of historical travel data.

[0093] In this embodiment, the user travel mode refers to the user's travel method.

[0094] In this embodiment, historical travel features of the user's historical travel data are extracted to determine the user's travel mode. For example, the user travel mode of user a1 is a walking mode, and the user travel mode of user a2 is a cycling mode.

[0095] In this embodiment, the user's current travel data is matched with the user's travel mode. For example, if the user's current travel data shows that the user's travel route is consistent with the historical travel route, the user's travel mode in the current period is determined based on the travel mode corresponding to the historical travel route.

[0096] The working principle and beneficial effect of the above technical solution are: by obtaining the user's historical travel data and the user's current travel data, the user's travel mode in the current period is determined, which is conducive to providing different travel health guidance for different users in the future.

[0097] Embodiment 4:

[0098] An embodiment of the present invention provides a health guidance system for users' travel taking into account the impact of air pollution, and further includes:

[0099] A data encryption unit, used for performing data encryption processing when obtaining the user's historical travel data and obtaining the user's current travel data;

[0100] A data elimination unit, used for performing data elimination processing on the user's historical travel data before extracting the historical travel features of the user's historical travel data;

[0101] The current travel distance corresponding to the user's current travel data is obtained, and the user's historical travel data whose historical travel distance is not longer than the current travel distance is removed.

[0102] In this embodiment, the data elimination process refers to the process of eliminating the historical travel data of users whose historical travel distance is not longer than the current travel distance.

[0103] In this embodiment, the current travel distance refers to the travel distance of the user in the current period determined based on the user's current travel data.

[0104] In this embodiment, the historical travel distance refers to the distance traveled by the user in a historical period.

[0105] In this embodiment, historical travel data of users whose historical travel distance is not higher than the current travel distance are eliminated, that is, historical travel data of users whose historical travel distance is not higher than the current travel distance will not be helpful for subsequent travel health induction.

[0106] The working principle and beneficial effects of the above technical solution are: by encrypting data, the security of user data is ensured; by eliminating the user's historical travel data, the efficiency of subsequent user travel health induction is improved.

[0107] Embodiment 5:

[0108] The embodiment of the present invention provides a health guidance system that considers the impact of air pollution on user travel, and an air pollution prediction module, including:

[0109] An air pollution prediction model unit is used to select a prediction model, construct an air pollution prediction model, and perform model training on the air pollution prediction model according to the data aggregation and processing results, wherein the prediction model includes: a linear regression prediction model, a random regression prediction model, and a neural network prediction model;

[0110] A model training and evaluation unit, used to randomly extract historical travel data of users from the data aggregation and processing results to evaluate the prediction performance of the air pollution prediction model after model training;

[0111] When the prediction performance of the air pollution prediction model after model training is not lower than the preset prediction performance, the model training is determined to be completed;

[0112] The air pollution prediction unit is used to input the user's current travel data and travel mode into the air pollution prediction model after model training, and predict the current air pollution data of the user's travel area.

[0113] In this embodiment, the air pollution prediction model refers to a model used to predict air pollution.

[0114] In this embodiment, the prediction performance refers to the performance of the air pollution prediction model in predicting air pollution.

[0115] In this embodiment, the preset prediction performance refers to the performance that is preset for the user to determine whether the model training is completed.

[0116] In this embodiment, the current air pollution data refers to the air pollution data of the user's travel area in the current period predicted by the air pollution prediction model trained by inputting the user's current travel data and travel mode into the model.

[0117] The working principle and beneficial effects of the above technical solution are: by constructing an air pollution prediction model and training the model based on the data aggregation and processing results, the user's current travel data and travel mode are input into the air pollution prediction model after model training, and the current air pollution data of the user's travel area is predicted, which is conducive to the subsequent realization of healthy induction for the user's travel.

[0118] Embodiment 6:

[0119] The embodiment of the present invention provides a health guidance system for users' travel taking into account the impact of air pollution on their travel, and a travel health guidance module, including:

[0120] A user travel health demand unit is used to obtain user health data and determine the user's travel health demand, wherein the user health data includes: user age data, user gender data and user health status data;

[0121] A risk assessment unit is used to conduct a risk assessment on the current air pollution data according to the user's travel health needs, and determine the risk level of the user's current travel area, where the risk levels include: low risk level, medium risk level and high risk level;

[0122] A travel route unit is used to set a route planning target for the user's current travel route according to the user's travel health needs and the current user's travel needs, wherein the route planning targets include: travel health planning targets, travel time planning targets, travel mode planning targets, and travel distance planning targets;

[0123] Plan the user's current travel route according to the risk level of the user's current travel area and the route planning target of the user's current travel route;

[0124] The travel route optimization unit is used to set the risk assessment cycle and estimate the user's current travel speed based on the user's current route and travel mode;

[0125] According to the user's current travel speed and risk assessment period, the user's current travel route is divided into routes, the air pollution data of each section of the user's current travel route is re-predicted, and the risk level of each section of the user's current travel route is re-determined;

[0126] Optimize the user's current travel route in real time based on the re-determined risk level of each segment of the user's current travel route;

[0127] The user travel health suggestion unit is used to generate user travel health suggestions based on the user's current travel route optimized in real time.

[0128] In this embodiment, user health data refers to health information determined by user personal data. Different people have different sensitivities to air pollution. Therefore, user health data is obtained for subsequent travel health guidance.

[0129] In this embodiment, the user's travel health demand refers to the user's travel health demand. The higher the user's travel health demand, the lower the air pollution corresponding to the travel route should be.

[0130] In this embodiment, the risk level refers to a level determined by performing a risk assessment on current air pollution data according to the user's travel health needs, and is used to indicate the degree of air pollution.

[0131] In this embodiment, the low risk level means that air pollution has no health impact on the user's travel; the medium risk level means that air pollution has a certain health impact on the user's travel, but it is acceptable; the high risk level means that air pollution has a health impact on the user's travel, and the impact is unacceptable, and the user needs to avoid this high risk level area or terminate the trip.

[0132] In this embodiment, the route planning goal refers to the goal of planning a user's travel route, such as a route planning goal with optimal travel time and a route planning goal with optimal travel health.

[0133] In this embodiment, the user's current travel route refers to the planned travel route of the user in the current period, which is determined according to the risk level of the user's current travel area and the route planning target of the user's current travel route.

[0134] In this embodiment, the risk assessment cycle refers to the cycle for conducting risk assessment on current air pollution data according to the user's travel health needs. By setting the risk assessment cycle, it is used to ensure the timely update of travel routes.

[0135] In this embodiment, the current travel speed of the user refers to the speed of the user when traveling in the current period.

[0136] In this embodiment, the user's current travel route is divided according to the user's current travel speed and risk assessment period, that is, the optimal route of the user in each section within each risk assessment period is ensured to avoid affecting the user's travel health due to errors in risk assessment.

[0137] In this embodiment, the user travel health advice refers to the travel advice generated based on the real-time optimized user's current travel route.

[0138] The working principle and beneficial effects of the above technical solution are: by conducting risk assessment on current air pollution data according to the user's travel health needs, planning the user's current travel route according to the risk assessment results and generating travel health recommendations for the user, it effectively achieves health induction for the user and ensures the user's travel health.

[0139] Embodiment 7:

[0140] An embodiment of the present invention provides a health guidance system for users' travel taking into account the impact of air pollution, and further includes:

[0141] A travel visualization unit is used to visualize the user's current travel route and the user's travel health recommendations;

[0142] The travel route real-time update unit is used to visualize the optimization results and provide update prompts in real time when it is detected that the user's current travel route has been optimized.

[0143] In this embodiment, the optimization result refers to the user's current travel route that is optimized in real time according to the re-determined risk levels of each segment of the user's current travel route.

[0144] The working principle and beneficial effect of the above technical solution are: by visualizing the user's current travel route and the user's travel health suggestions, and visually displaying the optimization results in real time and updating prompts, the user's travel health is further ensured.

[0145] Embodiment 8:

[0146] An embodiment of the present invention provides a health guidance system for users' travel taking into account the impact of air pollution, and further includes:

[0147] The travel warning module is used to obtain the risk level of the user's current travel route. When the risk level of the user's current travel route is monitored to be high, a travel warning notification is issued to the user.

[0148] In this embodiment, the travel warning notification refers to a warning notification when a risk level of the user's current travel route is monitored to be at a high risk level, which is used to prompt the user to change the travel route or terminate the travel.

[0149] The working principle and beneficial effect of the above technical solution are: by monitoring the risk level of the user's current travel route to be at a high risk level, a travel warning notification is issued to the user, effectively ensuring the user's travel health.

[0150] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A health guidance system considering the impact of air pollution on user travel, characterized in that: include: The air pollution data module is used to obtain the historical air pollution data of the user's travel area according to the current user's travel needs and perform data aggregation processing; The user travel mode module is used to obtain the user's historical travel data and the user's current travel data to determine the user's travel mode in the current period; The air pollution prediction module is used to build an air pollution prediction model and train the model based on the data aggregation and processing results. The user's current travel data and travel mode are input into the trained air pollution prediction model to predict the current air pollution data of the user's travel area. The travel health induction module is used to conduct risk assessment on current air pollution data according to the user's travel health needs, plan the user's current travel route according to the risk assessment results, and generate travel health recommendations for the user; Among them, the travel health induction module includes: A user travel health demand unit is used to obtain user health data and determine the user's travel health demand, wherein the user health data includes: user age data, user gender data and user health status data; A risk assessment unit is used to conduct a risk assessment on the current air pollution data according to the user's travel health needs, and determine the risk level of the user's current travel area, where the risk levels include: low risk level, medium risk level and high risk level; A travel route unit is used to set a route planning target for the user's current travel route according to the user's travel health needs and the current user's travel needs, wherein the route planning targets include: travel health planning targets, travel time planning targets, travel mode planning targets, and travel distance planning targets; Plan the user's current travel route according to the risk level of the user's current travel area and the route planning target of the user's current travel route; The travel route optimization unit is used to set the risk assessment cycle and estimate the user's current travel speed based on the user's current route and travel mode; According to the user's current travel speed and risk assessment period, the user's current travel route is divided into routes, the air pollution data of each section of the user's current travel route is re-predicted, and the risk level of each section of the user's current travel route is re-determined; Optimize the user's current travel route in real time based on the re-determined risk level of each segment of the user's current travel route; The user travel health suggestion unit is used to generate user travel health suggestions based on the user's current travel route optimized in real time.

2. A health guidance system considering the impact of air pollution on user travel according to claim 1, characterized in that: Air pollution data module, including: A user travel demand unit, used to obtain the current user travel demand according to user input data, wherein the user input data includes: travel starting point data, travel way point data and travel destination data; A travel area unit is used to determine the user's current travel area based on the user's current travel demand and the user's travel deviation; The historical air pollution data unit is used to select the data source of air pollution data, obtain the historical air pollution data of the user's current travel area and perform data aggregation processing.

3. A health guidance system considering the impact of air pollution on user travel according to claim 1, characterized in that: User travel mode module, including: A travel data unit is used to obtain the user's historical travel data, wherein the user's historical travel data includes: historical travel time data, historical travel mode data and historical travel route data; Acquire the user's current travel data, wherein the user's current travel data includes: current travel time data, current travel mode data, and current travel demand data; A travel mode unit, used to extract historical travel features of the user's historical travel data and determine the user's travel mode; The user's current travel data is matched with the user's travel mode to determine the user's travel mode in the current period.

4. A health guidance system considering the impact of air pollution on user travel according to claim 3, characterized in that: Also includes: A data encryption unit, used for performing data encryption processing when obtaining the user's historical travel data and obtaining the user's current travel data; A data elimination unit, used for performing data elimination processing on the user's historical travel data before extracting the historical travel features of the user's historical travel data; The current travel distance corresponding to the user's current travel data is obtained, and the user's historical travel data whose historical travel distance is not longer than the current travel distance is removed.

5. The health guidance system considering the impact of air pollution on user travel according to claim 1, characterized in that: Air pollution prediction module, including: An air pollution prediction model unit is used to select a prediction model, construct an air pollution prediction model, and perform model training on the air pollution prediction model according to the data aggregation and processing results, wherein the prediction model includes: a linear regression prediction model, a random regression prediction model, and a neural network prediction model; A model training and evaluation unit, used to randomly extract historical travel data of users from the data aggregation and processing results to evaluate the prediction performance of the air pollution prediction model after model training; When the prediction performance of the air pollution prediction model after model training is not lower than the preset prediction performance, the model training is determined to be completed; The air pollution prediction unit is used to input the user's current travel data and travel mode into the air pollution prediction model after model training, and predict the current air pollution data of the user's travel area.

6. The health guidance system considering the impact of air pollution on user travel according to claim 1, characterized in that: Also includes: A travel visualization unit is used to visualize the user's current travel route and the user's travel health recommendations; The travel route real-time update unit is used to visualize the optimization results and provide update prompts in real time when it is detected that the user's current travel route has been optimized.

7. A health guidance system considering the impact of air pollution on user travel according to claim 1, characterized in that: Also includes: The travel warning module is used to obtain the risk level of the user's current travel route. When the risk level of the user's current travel route is monitored to be high, a travel warning notification is issued to the user.

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