Environment pollution prediction method and system based on big data

Abstract

The invention discloses an environmental pollution prediction method and system based on big data, and relates to the technical field of big data environmental monitoring, and the system comprises a positioning module, an acquisition module, a detection module, an analysis and statistics module and an alarm module. The information is compared with data in a database, meanwhile, the data can be classified, harmful and harmless components can be divided, the index of environmental pollution can be calculated, and meanwhile, the calculated harmful information can be transmitted to the acquisition module, so that the acquisition module can perform multiple times of sampling at different positions of an acquired place; according to the invention, multi-directional and multi-time detection and analysis can be carried out, the accuracy of environmental pollution prediction can be improved, the alarm module gives prompts to the acquisition module and the terminal, the acquisition module can pay attention to the safety of an acquired place, and the terminal can take measures quickly.

Description

Technical Field

[0001] The present invention belongs to the technical field of big data environmental monitoring, in particular to environmental pollution prediction, and relates to an environmental pollution prediction method and system based on big data. Background Art

[0002] Environmental pollution refers to the harmful behavior caused by natural or man-made addition of certain substances into the environment that exceeds the environment's automatic purification capacity. Environmental pollution is not conducive to the survival of organisms in the environment. In order to provide organisms with a more favorable and healthy living environment, environmental pollution control is an important task. At the same time, environmental pollution prediction is an important task before the environment is polluted. Environmental pollution prediction can detect and analyze substances in the environment, which is conducive to judging the state of the environment and making countermeasures convenient and quick.

[0003] The Chinese invention patent application with publication number "CN116757311A" discloses an ecological environment pollution monitoring method and system based on big data. The method obtains the geographical location information of the atmospheric pollution monitoring base station, and predicts the meteorological characteristic data of the atmospheric pollution monitoring base station based on the geographical location information of the atmospheric pollution monitoring base station, obtains the meteorological characteristic prediction result, further obtains the working characteristic data information of the atmospheric pollution monitoring base station, and determines the pollution monitoring period of the atmospheric monitoring base station in combination with the meteorological characteristic prediction result and the working characteristic data information, thereby constructing a monitoring plan for the atmospheric pollution monitoring base station according to the pollution monitoring period of the atmospheric pollution monitoring base station.

[0004] The above scheme can only improve the accuracy of detection according to seasonal changes, and cannot perform larger-area cyclic detection of different locations in the same place. In the same season, different locations in the same large environment have different concentrations of substances in the air due to different wind directions. Only a single environment is detected, which is prone to large errors in the results, and is not conducive to more accurate prediction of environmental pollution. At the same time, it is impossible to issue prompts to the detection location and the terminal at the same time, which is not conducive to the safety of the detection location, and is not conducive to the terminal to quickly respond.

[0005] In summary, the present invention provides an environmental pollution prediction method and system based on big data to solve the above problems. Summary of the invention

[0006] In view of the shortcomings of the prior art, the purpose of the present invention is to provide an environmental pollution prediction method and system based on big data, which has the advantages of being able to detect the detected environment in a larger range, and being able to conduct more comprehensive cyclic detection, analysis and calculation of the material content in the detected environment, which can be helpful in ensuring the accuracy of the detection, and improving the accuracy of environmental pollution prediction information. At the same time, signal prompts can be sent to the detected location and terminal simultaneously, which can be beneficial to the safety of the detected location and can facilitate the terminal to quickly take corresponding response measures.

[0007] To achieve the above-mentioned purpose, the present invention provides an environmental pollution prediction system based on big data, including a positioning module, a collection module, a detection module, an analysis and statistics module and an alarm module, wherein the positioning module is used to locate the location information of the collected point and send the location information to the collection module, the positioning module is communicatively connected to the collection module, the collection module is used to receive the location information, and according to the location information, gradually collect environmental information at multiple preset collection devices and send it to the detection module, the detection module is wirelessly connected to the collection module, the detection module is used to receive multiple environmental information, and perform pollution component detection on each environmental information to obtain multiple pollutant detection data, the detection module is electrically connected to the analysis and statistics module, the analysis and statistics module is used to process each pollutant detection data to obtain a pollution detection value, and analyze and judge the pollution degree of the collection point according to the pollution detection value, the analysis and statistics module is communicatively connected to the alarm module, and the alarm module is used to issue an alarm prompt according to the pollution degree.

[0008] Preferably, the acquisition module includes a collection module, an output module, a receiving module, a cruise module and an alarm module, the collection module is connected to the output module and the cruise module through communication, and the receiving module is connected to the cruise module and the alarm module through communication.

[0009] Preferably, the analysis and statistics module includes an analysis module, a classification module, a calculation module and a return module that are communicatively connected to the output module. The analysis module is communicatively connected to the classification module and the calculation module, and the return module is communicatively connected to the calculation module and the receiving module.

[0010] Preferably, the alarm module includes a first prompt module and a second prompt module, the first prompt module is communicatively connected to the receiving module and the returning module, and the second prompt module is communicatively connected to the returning module.

[0011] The present invention also provides an environmental pollution prediction method based on big data, comprising the following steps: Step 1: Locate the location information of the collected point and send the location information to the collection module; Step 2: receiving the location information, and gradually collecting environmental information at multiple preset collection devices according to the location information and sending the collected environmental information to the detection module; Step 3: receiving a plurality of the environmental information, and performing pollution component detection on each of the environmental information to obtain a plurality of pollutant detection data; Step 4: Process each of the pollutant detection data to obtain a pollution detection value, and analyze and determine the pollution degree of the collection point according to the pollution detection value; Step 5: Issue an alarm based on the pollution level.

[0012] Preferably, the step of gradually collecting environmental information at multiple preset collection devices according to the location information and then sending the collected environmental information to the detection module comprises the following steps: S201: The collection module collects substances in the atmosphere of the environment and transmits the information to the output module; S202: uniformly transmitting the information of different substances collected by the collection module to the detection module through the output module; S203: the receiving module receives the returned information transmitted from the returning module, and the receiving module transmits the received returned information to the cruise module; S204: the cruise module controls the collection module to enable the collection module to collect fixed-point data of the detected environment in a larger range, thereby expanding the collection range of the collection module; S205: While the collection module is collecting information, the warning module issues a reminder to pay attention to the surrounding environment.

[0013] Preferably, the processing of each of the pollutant detection data to obtain a pollution detection value, and analyzing and judging the pollution degree of the collection point according to the pollution detection value comprises the following steps: S401: the analysis module uniformly transmits the information detected by the detection module to the database, and can analyze and confirm the components of the received information and the information in the resource library, and at the same time transmit the information to the classification module; S402: the classification module classifies the information received from the analysis module into harmful information and harmless information, and transmits the classified information to the calculation module; S403: The calculation module calculates the ratio of the harmful information to the harmless information, calculates the pollution detection value using the formula pollution index W(R)=(C1 / Q1)x*W1+(C2 / Q2)x*W2+ ...+(Cn / Qn)x*Wn, and transmits the harmful information to the return module; S404: the returning module transmits the harmful information back to the receiving module, and the returning module transmits the environmental pollution prediction information to the first warning module and the second warning module; S405: The analysis module determines whether the pollution detection value is greater than a preset detection value; If the pollution detection value is greater than the preset detection value, it is determined that the collection point is seriously polluted; If the pollution detection value is not greater than the preset detection value, it is determined that the collection point is less polluted.

[0014] Preferably, issuing an alarm according to the pollution degree comprises the following steps: S501: After receiving harmful information, the first warning module transmits the information to the receiving module; S502: After receiving the harmful information, the second warning module transmits the information to relevant personnel of the terminal.

[0015] In summary, the beneficial technical effects of the present invention are: The collection module of the present invention collects air at the detected location, and the detection module can detect the components of the collected air and transmit the information to the analysis and statistics module. The analysis and statistics module analyzes the received information and compares each information with the data in the database. At the same time, it can classify the data, divide harmful and harmless components, and calculate the environmental pollution index. At the same time, it can transmit the calculated harmful information to the collection module, so that the collection module can perform multiple sampling at different positions of the collected location, can perform multi-directional and multiple detection and analysis, which can be beneficial to improve the accuracy of environmental pollution prediction. At the same time, the alarm module sends prompts to the collection module and the terminal, which is beneficial for the collection module to pay attention to the safety of the collected location and is beneficial for the terminal to take measures quickly.

[0016] The specific implementation modes of the present invention are further described in detail below in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described below are only some embodiments. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. In the drawings: Figure 1 FIG. 1 is a schematic diagram of a system structure according to an embodiment of the present invention.

[0018] Figure 2 The figure is a schematic diagram of a method flow according to an embodiment of the present invention.

[0019] Figure 3 A schematic diagram of the internal structure of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0020] The present invention is further described in detail below in conjunction with the accompanying drawings.

[0021] Reference Figure 1-Figure 3 As shown, the present invention provides an environmental pollution prediction system based on big data, including a positioning module, a collection module, a detection module, an analysis and statistics module and an alarm module, wherein the positioning module is used to locate the position information of the collected point and send the position information to the collection module, the positioning module is communicatively connected to the collection module, the collection module is used to receive the position information, and according to the position information, gradually collect environmental information at multiple preset collection devices and send it to the detection module, the detection module is wirelessly connected to the collection module, the detection module is used to receive multiple environmental information, and perform pollution component detection on each environmental information to obtain multiple pollutant detection data, the detection module is electrically connected to the analysis and statistics module, the analysis and statistics module is used to process each pollutant detection data to obtain a pollution detection value, and analyze and judge the pollution degree of the collection point according to the pollution detection value, the analysis and statistics module is communicatively connected to the alarm module, and the alarm module is used to issue an alarm prompt according to the pollution degree. The collection module collects air at the detected location. The detection module can detect the composition of the collected air and pass the information to the analysis and statistics module. The analysis and statistics module analyzes the received information and compares each information with the data inside the database. At the same time, it can classify the data, divide harmful and harmless components, and calculate the environmental pollution index. At the same time, it can pass the calculated harmful information to the collection module, so that the collection module can perform multiple sampling at different locations of the collected location, and can perform multi-directional and multiple detection and analysis, which can help improve the accuracy of environmental pollution prediction. At the same time, the alarm module sends prompts to the collection module and the terminal, which is helpful for the collection module to pay attention to the safety of the collected location and for the terminal to take quick measures.

[0022] Furthermore, the collection module of the present embodiment includes a collection module, an output module, a receiving module, a cruise module and an alarm module. The collection module can collect air in the environment, the output module can transmit the collected air to the detection module, the receiving module can conveniently receive signals from the analysis and statistics module and the alarm module, the cruise module can control the collection module to collect substances in the environment at different locations, the alarm module can conveniently prompt the collected locations, the collection module is connected to the output module and the cruise module through communication, and the receiving module is connected to the cruise module and the alarm module through communication.

[0023] Furthermore, the analysis and statistics module of this embodiment includes an analysis module, a classification module, a calculation module and a return module that are communicatively connected to the output module. The analysis module can analyze the information after detection, the classification module can conveniently classify different material information, the calculation module can calculate the material information to facilitate the judgment of the environmental pollution situation, and the return module can conveniently transmit information to the receiving module and the alarm module. The analysis module is connected to the classification module and the calculation module through communication, and the return module is connected to the calculation module and the receiving module through communication.

[0024] The alarm module of this embodiment includes a first prompt module and a second prompt module. The first prompt module can conveniently pass the information received from the return module to the receiving module, and the second prompt module can receive the information transmitted by the return module. The first prompt module is communicatively connected to the receiving module and the return module, and the second prompt module is communicatively connected to the return module.

[0025] The present invention also provides an environmental pollution prediction method based on big data, comprising the following steps: Step 1: Locate the location information of the collected point and send the location information to the collection module; Step 2: receiving the location information, and gradually collecting environmental information at multiple preset collection devices according to the location information and sending the collected environmental information to the detection module; Step 3: receiving a plurality of the environmental information, and performing pollution component detection on each of the environmental information to obtain a plurality of pollutant detection data; Step 4: Process each of the pollutant detection data to obtain a pollution detection value, and analyze and determine the pollution degree of the collection point according to the pollution detection value; Step 5: Issue an alarm based on the pollution level.

[0026] Specifically, through step 1, "locating the location information of the collected point", this is the key to accurately locate the pollution source. By combining location information with environmental data, the system can more accurately determine the distribution of pollution sources, which helps to find hot spots with poor air quality in the region, thereby improving the effectiveness of pollution monitoring. Step 2, "gradually collecting environmental information and sending it to the detection module", helps the system to monitor and compare in different regions. By gradually collecting environmental information from different locations, the air pollution situation in the region can be more accurately reflected, avoiding the problem of large errors in centralized monitoring areas. Step 3, "detecting the pollutant components of each environmental information", helps to analyze the air pollution components more carefully. For example, different pollutants have different effects on health and the environment. By detecting the pollutant components one by one, the system helps to more comprehensively grasp the type and concentration of pollution sources, thereby avoiding the errors caused by the detection of a single pollution source. The pollution data processing and alarm issuance mechanism mentioned in steps 4 and 5 provide guarantees for real-time monitoring and emergency response. Once the pollution concentration is detected to reach a dangerous level, the system can respond quickly and send an alarm to relevant personnel or terminal devices, thereby reducing the potential threat of air pollution to human health and the environment. Step 5 can be used to issue an alarm based on the degree of pollution, which can remind relevant personnel to take timely response measures, such as turning on air purification equipment, adjusting traffic routes, etc., to prevent further spread of pollution. For terminal equipment, corresponding control measures can also be taken in a timely manner to improve the efficiency of pollution response. Therefore, by decentralized monitoring of environmental information at different locations, errors caused by centralized monitoring can be avoided, which helps to more accurately reflect the pollution situation. Timely pollution detection and alarm mechanisms can enable relevant personnel and system terminals to respond quickly and take response measures to reduce the impact of environmental pollution on the human body and the environment. The system can collect multi-dimensional pollution data and conduct comprehensive analysis, which helps to provide more scientific data support for the governance and prevention of pollution sources.

[0027] Furthermore, the step of gradually collecting environmental information at multiple preset collection devices according to the location information and then sending the collected environmental information to the detection module includes the following steps: S201: The collection module collects substances in the atmosphere of the environment and transmits the information to the output module; S202: uniformly transmitting the information of different substances collected by the collection module to the detection module through the output module; S203: the receiving module receives the returned information transmitted from the returning module, and the receiving module transmits the received returned information to the cruise module; S204: the cruise module controls the collection module to enable the collection module to collect fixed-point data of the detected environment in a larger range, thereby expanding the collection range of the collection module; S205: While the collection module is collecting information, the warning module issues a reminder to pay attention to the surrounding environment.

[0028] When the collection module collects the air at the detected location, it is transmitted to the detection module through the output module, so that the detection module can detect various substances in the environment. When the analysis and statistics module transmits harmful information to the receiving module, the receiving module can transmit the information to the cruise module, and the cruise module starts to control the movement of the collection module. The collection module can collect air from more locations, which can facilitate the collection of more samples, increase the number of control groups, and facilitate more accurate environmental pollution predictions. At the same time, the warning module issues a prompt after receiving the warning information, prompting relevant personnel entering the collected location to take protective measures to prevent harm to the body by harmful substances. In step S204, it is mentioned that the cruise module controls the collection module to enable it to detect The system can collect fixed-point data in a wider range by expanding the collection range, so that the system can cover more monitoring points, thereby comprehensively monitoring a wider area, avoiding the error caused by single environmental point data, and multi-point collection helps to more accurately reflect the pollution status of the entire area, especially for the situation where the concentration of air pollutants varies greatly in different locations, expanding the collection range helps to reduce the result error caused by local data distortion. The system combines the collection module, output module, detection module, receiving module, and cruise module organically through steps S201, S202, and S203. Each module has its specific function, and information can be transmitted and processed layer by layer, reducing the error caused by distortion during data transmission. In addition, the unified transmission and feedback mechanism of information ensures the timely update and feedback of the detection data, thereby improving the accuracy of the overall data and the response speed of the system. In step S205, the warning module issues a prompt to the surrounding environment to remind the surrounding personnel to pay attention to environmental changes. This mechanism is crucial to enhancing the emergency response capability of the environmental monitoring system. Real-time warning can ensure that once the pollution concentration reaches a dangerous level, the relevant personnel will be immediately alerted and can take measures quickly. This real-time feedback system not only increases the rapid response to the pollution source, but also ensures that the surrounding personnel can avoid the polluted area in time and reduce health risks. The "unified transmission of information" in step S202 and the "receiving and transmitting return information" in step S203 ensure that the information of all monitoring points can be collected and fed back to the detection module in time, which enables pollution detection and data analysis to be updated in real time. In addition, by centrally processing this information, the system can identify and judge the pollution level more quickly, thereby improving the system's response speed to environmental changes. The instant prompt function of the warning module can also provide instant warnings to the polluted area and the surrounding environment, ensuring that the dynamic monitoring and emergency response of pollution can keep pace with the changes in the pollution source, further avoiding the potential risks caused by single-location detection. The cruise module in step S204 controls the collection module to expand the collection range, so that the monitoring can be dynamically adjusted as needed at any time, especially when the pollution source is unevenly distributed.Through this flexible monitoring mechanism, the system can respond to different environmental changes and pollution diffusion situations, further reducing the errors caused by local monitoring blind spots or environmental data deviations. Therefore, through the combination of the above steps, the system can not only be limited to the monitoring of a single environment, but also form a multi-point, dynamic environmental data collection and early warning system. In scenarios where the concentration of environmental pollution varies greatly, it can more accurately reflect the overall pollution situation, rather than relying solely on the data of a single detection point. Therefore, by expanding the collection range and dynamically adjusting the detection area, the system can avoid errors caused by a single monitoring point and ensure that the monitoring results of environmental pollution are more comprehensive and accurate. Through real-time alarm prompts, personnel and terminal systems at the detection site can be informed of environmental changes in a timely manner and take quick action to reduce the threat of pollution diffusion to health and safety. Through information interconnection and interoperability of various modules, real-time feedback, dynamic adjustment and optimized decision-making can be achieved to ensure that the monitoring system can respond quickly to various environmental changes and emergencies. By controlling the collection range through the cruise module, the system can flexibly adjust to different situations of environmental pollution, thereby ensuring that a wider range of pollution sources can be detected.

[0029] Furthermore, the processing of each of the pollutant detection data to obtain a pollution detection value, and analyzing and judging the pollution degree of the collection point according to the pollution detection value includes the following steps: S401: the analysis module uniformly transmits the information detected by the detection module to the database, and can analyze and confirm the components of the received information and the information in the resource library, and at the same time transmit the information to the classification module; S402: the classification module classifies the information received from the analysis module into harmful information and harmless information, and transmits the classified information to the calculation module; S403: The calculation module calculates the ratio of the harmful information to the harmless information, calculates the pollution detection value using the formula pollution index W(R)=(C1 / Q1)x*W1+(C2 / Q2)x*W2+ ...+(Cn / Qn)x*Wn, and transmits the harmful information to the return module; S404: the returning module transmits the harmful information back to the receiving module, and the returning module transmits the environmental pollution prediction information to the first warning module and the second warning module; S405: The analysis module determines whether the pollution detection value is greater than a preset detection value; If the pollution detection value is greater than the preset detection value, it is determined that the collection point is seriously polluted; If the pollution detection value is not greater than the preset detection value, it is determined that the collection point is less polluted.

[0030] The analysis module transmits the received information to the database, and compares it with the data in the database to analyze the composition of each substance, and can confirm whether the substance is harmful or harmless. At the same time, it can transmit the information to the classification component. The classification component classifies the received information into harmful and harmless information. At the same time, the calculation module uses the formula: pollution index W(R)=(C1 / Q1)x*W1+(C2 / Q2)x*W2+ ...+(Cn / Qn)x*Wn to calculate the substances in the environment, and can obtain the environmental pollution situation. Then, the harmful information is returned to the receiving module through the return module, which is convenient for the receiving module to transmit. At the same time, the return module transmits the harmful information to the alarm module, which is convenient for the alarm module to send a prompt signal. Among them, C1, C2,…, Cn are the concentrations of each pollutant; Q1, Q2,…, Qn is the environmental quality standard for the concentration of each pollutant; W1, W2, …, Wn are the weights of each pollutant. The analysis module uniformly processes the detected information and compares it with the information in the resource library. The system can more accurately analyze the composition of pollutants in the environment, which helps to identify different pollution sources in the air and improve the understanding of environmental pollution conditions. The calculation module quantifies the degree of pollution through the pollution index formula, making the air quality monitoring data more quantitative. The calculation of the pollution index can provide a reference for pollution conditions at different times and places, helping decision makers to better assess pollution risks. The return module provides early warnings for pollution conditions at different levels by transmitting harmful information to the first and second warning modules. For example, when the pollution detection value exceeds the preset threshold, the system can respond in time, trigger an alarm, and help relevant personnel take emergency measures. Harmful information is promptly fed back to the receiving module, which can provide data support for relevant units, enabling on-site staff to take countermeasures more quickly to avoid further deterioration of pollution incidents. This helps to improve response speed and reduce potential damage. By continuously analyzing and calculating the pollution index, the system can dynamically track changes in environmental pollution, provide more real-time and continuous monitoring, and help environmental protection personnel understand the dynamic changes of pollution sources and adjust response strategies in a timely manner.

[0031] Furthermore, the issuing of an alarm according to the pollution degree comprises the following steps: S501: After receiving harmful information, the first warning module transmits the information to the receiving module; S502: After receiving the harmful information, the second warning module transmits the information to relevant personnel of the terminal.

[0032] The first prompt module transmits harmful information to the receiving module, which makes it convenient for the receiving module to send information to the warning module, which is conducive to the warning module to make prompts. The second prompt module can transmit harmful information to the terminal, which is convenient for relevant personnel at the terminal to quickly take countermeasures, which is conducive to improving environmental safety. By setting up multiple warning modules, the system can ensure that when harmful information is detected in the environment, relevant personnel can be notified in time, which means that both on-site detection equipment and terminal personnel can receive warnings as early as possible and respond. Through the cooperation of the first warning module and the second warning module, the system can not only transmit information to the equipment at the detection location, but also issue warnings to relevant personnel through the terminal. This dual mechanism can ensure that information is spread more effectively. Extensive, reducing the risk of omissions and improving response speed. Through multiple detections of harmful information (including coordination between different modules), the system can reduce the errors that may occur in single environmental detection, which helps to monitor pollutants in the air more accurately, thereby improving the accuracy of environmental pollution predictions. If harmful information is detected, timely warnings can help the detection site take necessary safety measures to avoid possible health risks or safety accidents. This safety early warning mechanism can effectively enhance the practical significance and effectiveness of environmental monitoring. After receiving the warning through the second warning module, the terminal-related personnel can quickly respond according to the specific situation (such as initiating emergency treatment, notifying other departments, etc.), thereby avoiding further deterioration of the pollution situation.

[0033] The embodiments of this specific implementation method are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An environmental pollution prediction system based on big data, comprising a positioning module, a collection module, a detection module, an analysis and statistics module and an alarm module, characterized in that: The positioning module is used to locate the position information of the collected point and send the position information to the collection module; The positioning module is in communication connection with the acquisition module, and the acquisition module is used to receive the position information, and gradually acquire environmental information at multiple preset acquisition devices according to the position information and then send it to the detection module; The detection module is wirelessly connected to the acquisition module, the detection module is used to receive a plurality of the environmental information, and perform pollution component detection on each of the environmental information to obtain a plurality of pollutant detection data, and the detection module is electrically connected to the analysis and statistics module; The analysis and statistics module is used to process each of the pollutant detection data to obtain a pollution detection value, and analyze and determine the pollution degree of the collection point based on the pollution detection value. The analysis and statistics module is communicatively connected with the alarm module, and the alarm module is used to issue an alarm prompt based on the pollution degree.

2. The environmental pollution prediction system based on big data according to claim 1 is characterized in that: The acquisition module includes a collection module, an output module, a receiving module, a cruise module and an alarm module. The collection module is connected to the output module and the cruise module through communication, and the receiving module is connected to the cruise module and the alarm module through communication.

3. The environmental pollution prediction system based on big data according to claim 2 is characterized in that: The analysis and statistics module includes an analysis module, a classification module, a calculation module and a return module which are communicatively connected to the output module. The analysis module is communicatively connected to the classification module and the calculation module, and the return module is communicatively connected to the calculation module and the receiving module.

4. The environmental pollution prediction system based on big data according to claim 3 is characterized in that: The alarm module includes a first prompt module and a second prompt module. The first prompt module is communicatively connected to the receiving module and the returning module. The second prompt module is communicatively connected to the returning module.

5. A method for predicting environmental pollution based on big data, characterized in that: The environmental pollution prediction system based on big data according to any one of claims 1 to 4 comprises the following steps: Step 1: Locate the location information of the collected point and send the location information to the collection module; Step 2: receiving the location information, and gradually collecting environmental information at multiple preset collection devices according to the location information and sending the collected environmental information to the detection module; Step 3: receiving a plurality of the environmental information, and performing pollution component detection on each of the environmental information to obtain a plurality of pollutant detection data; Step 4: Process each of the pollutant detection data to obtain a pollution detection value, and analyze and determine the pollution degree of the collection point according to the pollution detection value; Step 5: Issue an alarm based on the pollution level.

6. The method for predicting environmental pollution based on big data according to claim 5, characterized in that: The step of gradually collecting environmental information at multiple preset collection devices according to the location information and then sending the collected environmental information to the detection module comprises the following steps: S201: The collection module collects substances in the atmosphere of the environment and transmits the information to the output module; S202: uniformly transmitting the information of different substances collected by the collection module to the detection module through the output module; S203: the receiving module receives the returned information transmitted from the returning module, and the receiving module transmits the received returned information to the cruise module; S204: the cruise module controls the collection module to enable the collection module to collect fixed-point data of the detected environment in a larger range, thereby expanding the collection range of the collection module; S205: While the collection module is collecting information, the warning module issues a reminder to pay attention to the surrounding environment.

7. The method for predicting environmental pollution based on big data according to claim 6, characterized in that: The processing of each of the pollutant detection data to obtain a pollution detection value, and analyzing and judging the pollution degree of the collection point according to the pollution detection value comprises the following steps: S401: the analysis module uniformly transmits the information detected by the detection module to the database, and can analyze and confirm the components of the received information and the information in the resource library, and at the same time transmit the information to the classification module; S402: the classification module classifies the information received from the analysis module into harmful information and harmless information, and transmits the classified information to the calculation module; S403: The calculation module calculates the ratio of the harmful information to the harmless information, calculates the pollution detection value using the formula pollution index W(R)=(C1 / Q1)x*W1+(C2 / Q2)x*W2+ ...+(Cn / Qn)x*Wn, and transmits the harmful information to the return module; S404: the returning module transmits the harmful information back to the receiving module, and the returning module transmits the environmental pollution prediction information to the first warning module and the second warning module; S405: The analysis module determines whether the pollution detection value is greater than a preset detection value; If the pollution detection value is greater than the preset detection value, it is determined that the collection point is seriously polluted; If the pollution detection value is not greater than the preset detection value, it is determined that the collection point is less polluted.

8. The method for predicting environmental pollution based on big data according to claim 7, characterized in that: The step of issuing an alarm according to the pollution degree comprises the following steps: S501: After receiving harmful information, the first warning module transmits the information to the receiving module; S502: After receiving the harmful information, the second warning module transmits the information to relevant personnel of the terminal.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 5 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 5 to 8 are implemented.

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