A method for monitoring litter moisture, an electronic device, a storage medium, and a product

Abstract

The present application relates to the technical field of humidity monitoring, and particularly to a method for monitoring the humidity of litter, an electronic device, a storage medium, and a product. The method includes obtaining a monitoring image and identifying the litter feature information of the monitoring image; based on the litter feature information and preset hidden danger feature information, determining a hidden danger area and hidden danger area feature information from the monitoring image, and determining the humidity value of the litter in the hidden danger area based on the hidden danger area feature information; obtaining the influence feature information corresponding to the hidden danger area in a first preset time period, and determining the predicted hidden danger influence value corresponding to the hidden danger area in the first preset time period based on the influence feature information; updating the humidity value of the litter in the hidden danger area based on the predicted hidden danger influence value to obtain the humidity value of the litter in the target hidden danger area, and when the humidity value of the litter in the target hidden danger area is lower than the preset warning threshold, generating a prompt information based on the hidden danger area and the humidity value of the target hidden danger area. The present application is convenient for improving the accuracy of monitoring the humidity of litter.

Description

Technical Field

[0001] The present application relates to the technical field of humidity monitoring, and in particular, to a method for monitoring the humidity of litter, an electronic device, a storage medium, and a product. Background Art

[0002] A forest fire refers to a forest fire behavior that gets out of human control, spreads and expands freely in the forest land, and causes certain harm and losses to the forest, the forest ecosystem, and humans. As an important cover on the forest floor, the composition and characteristics of litter directly affect the fire risk of the forest. Litter with higher humidity is relatively less flammable, while dry litter is extremely easy to be ignited. By monitoring the humidity change of litter, its flammability can be evaluated in real time, so as to predict the occurrence risk of fire.

[0003] In the related art, generally, a sensor is directly used to monitor the humidity of litter. However, due to the insufficient accuracy and stability of some sensors, the humidity situation of litter may not be accurately reflected. Moreover, the forest environment is complex and changeable, including changes in various factors such as temperature, humidity, and light. Some sensor monitoring devices may not be able to fully adapt to these changes, which may affect the accuracy of the monitoring results, and further may reduce the precision when determining fire warnings based on the humidity of litter. Summary of the Invention

[0004] In order to improve the accuracy of monitoring the humidity of litter and thus improve the accuracy of fire warnings, the present application provides a method for monitoring the humidity of litter, an electronic device, a storage medium, and a product.

[0005] In a first aspect, the present application provides a method for monitoring the humidity of litter, adopting the following technical solution:

[0006] A method for monitoring the humidity of litter includes:

[0007] Obtain a monitoring image, and identify the litter feature information in the monitoring image, where the litter feature information includes litter color feature, litter texture feature, and litter shape feature;

[0008] Based on the litter feature information and the preset hidden danger feature information, determine the hidden danger area and the hidden danger area feature information from the monitoring image, and determine the humidity value of the litter in the hidden danger area based on the hidden danger area feature information, where the litter feature information corresponding to the hidden danger area satisfies the preset hidden danger feature information;

[0009] Obtain the influence feature information corresponding to the hidden danger area in a first preset time period, and determine the predicted hidden danger influence value corresponding to the hidden danger area in the first preset time period based on the influence feature information, where the influence feature information includes soil humidity information and animal activity information;

[0010] Update the litter humidity value of the potential hazard area based on the predicted potential hazard impact value to obtain the litter humidity value of the target potential hazard area. When the litter humidity value of the target potential hazard area is lower than the preset warning threshold, generate a prompt message based on the potential hazard area and the humidity value of the target potential hazard area.

[0011] By adopting the above technical solution, through feature recognition of the monitoring image, it is convenient to timely discover the potential hazard situation in the monitoring area. When the potential hazard area is determined, instead of directly giving a warning prompt, the humidity change situation of the litter in the potential hazard area in a future period of time is analyzed and predicted, so as to facilitate reducing false alarms or missed alarms. Among them, since the soil humidity and animal activities in the potential hazard area will directly affect the humidity change of the litter, therefore, by comprehensively considering the soil humidity information and animal activity information of the potential hazard area in a future period of time for the humidity change situation of the litter in the potential hazard area, it is convenient to improve the adaptability between the prediction result and the actual situation, thereby facilitating improving the accuracy of monitoring and warning the litter humidity.

[0012] In a possible implementation manner, the determining the predicted potential hazard impact value corresponding to the potential hazard area in the first preset time period based on the impact feature information includes:

[0013] Identify the soil humidity information and determine the soil humidity change information of the potential hazard area in the first preset time period;

[0014] Identify the animal behavior types included in the animal activity information, and determine the morphological change information of the potential hazard litter in the potential hazard area in the first preset time period based on the animal behavior types;

[0015] Obtain the regional simulation model corresponding to the potential hazard area, and import the potential hazard area feature information, the soil humidity change information, and the morphological change information into the regional simulation model for simulation to obtain the simulated litter change image corresponding to the first preset time period;

[0016] Identify the simulated litter feature information included in the simulated litter change image, and determine the predicted potential hazard impact value corresponding to the potential hazard area in the first preset time period based on the simulated litter feature information.

[0017] By adopting the above technical solution, since soil humidity and animal behavior types can directly affect litter humidity, therefore, by importing the soil humidity change information corresponding to the hidden danger area within the first preset time period and the morphological change information caused by animal behavior types into the area simulation model for simulation, it is convenient to improve the matching degree between the change of litter humidity in the simulated change image of litter and the actual change situation, thereby facilitating the improvement of the accuracy when determining the predicted hidden danger influence value corresponding to the hidden danger area.

[0018] In a possible implementation manner, the method further includes:

[0019] Obtain the weather characteristic information corresponding to the hidden danger area within the first preset time period, and based on the weather characteristic information, determine the weather change type corresponding to the hidden danger area within the first preset time period. The weather change type includes a stable type and an unstable type, and the weather characteristic information includes wind level and rainfall;

[0020] When the weather change type is unstable, determine the weather influence level based on the weather characteristic information;

[0021] Based on the morphological change information of the hidden danger litter within the first preset time period and the weather influence level, determine the first litter humidity influence value caused by the weather characteristic information on the hidden danger area within the first preset time period;

[0022] Optimize the predicted hidden danger influence value corresponding to the hidden danger area within the first preset time period based on the first litter humidity influence value.

[0023] By adopting the above technical solution, by analyzing the weather characteristic information of the hidden danger area within the preset time period, it is convenient to analyze the weather change situation faced by the hidden danger area within the preset time period. When it is determined that the weather change type is unstable, the possible humidity influence degree on the hidden danger litter can be analyzed by analyzing the morphological change information and humidity level, and the predicted hidden danger influence value is optimized based on the affected degree, which is convenient to improve the accuracy of the predicted hidden danger influence value.

[0024] In a possible implementation manner, when the influence characteristic information corresponding to the hidden danger area does not include animal activity information, the method further includes:

[0025] Based on the weather characteristic information, determine the influence area of the hidden danger area and the influence interval between the hidden danger area and the influence area from the monitoring image, and determine whether there is corresponding influence animal activity information in the influence area;

[0026] If so, determine the information on the change in the influencing form of the litter within the first preset time period in the influencing area according to the information on the animal activities affecting the litter;

[0027] Based on the information on the change in the influencing form and the influencing interval, determine the second litter humidity influence value caused by the influencing area on the potential hazard area within the first preset time period;

[0028] Optimize the predicted hazard influence value corresponding to the potential hazard area within the first preset time period based on the second litter humidity influence value.

[0029] By adopting the above technical solution, since animal activities may affect the form of litter, which may in turn affect the litter humidity, it is necessary to analyze the animal activities in the potential hazard area. However, since the animal activity routes and ranges may change, when there are no animal activities in the potential hazard area, the possible impacts on the potential hazard area can be indirectly analyzed by analyzing the information on the animal activities affecting the influencing area, which is convenient for improving the accuracy when determining the predicted hazard influence value.

[0030] In a possible implementation manner, the determining the second litter humidity influence value caused by the influencing area on the potential hazard area within the first preset time period based on the information on the change in the influencing form and the influencing interval includes:

[0031] Determine an influence range wave diagram based on the information on the change in the influencing form, where the influence range wave diagram contains multiple range wave dimensions, and different range wave dimensions correspond to different influence rates;

[0032] Determine the target influence rate caused by the influencing area on the potential hazard area within the first preset time period from the influence range wave diagram based on the influencing interval, and determine the second litter humidity influence value based on the target influence rate.

[0033] By adopting the above technical solution, different information on the change in the influencing form has different impacts on the potential hazard area under different influencing intervals. Therefore, different influence range wave diagrams are divided by the information on the change in the influencing form, and then the corresponding influence degree is determined from the range wave diagram based on the influencing interval between the potential hazard area and the influencing area, that is, the influence of the influencing area on the potential hazard area is refined by the influencing interval, which is convenient for improving the accuracy when determining the litter humidity influence value.

[0034] In a possible implementation manner, it further includes:

[0035] If no response information is detected within the second preset time period, determine the litter spraying amount based on the humidity difference between the litter humidity value of the target potential hazard area and the preset warning threshold;

[0036] Determine the spraying moment based on the second preset time period, and generate spraying instruction information based on the spraying moment and the litter spraying amount.

[0037] By adopting the above technical solution, if the relevant staff do not respond to abnormal situations for a long period of time, appropriate spraying operations can be performed on the potential hazard area according to the humidity difference at this time to increase the humidity of the litter, thereby facilitating the reduction of the probability of fire hazards.

[0038] In a second aspect, the present application provides an electronic device, adopting the following technical solution:

[0039] An electronic device, the electronic device includes:

[0040] At least one processor;

[0041] A memory;

[0042] At least one application program, wherein the at least one application program is stored in the memory and is configured to be executed by the at least one processor, and the at least one application program is configured to: execute the above-mentioned litter humidity monitoring method.

[0043] In a third aspect, the present application provides a computer-readable storage medium, adopting the following technical solution:

[0044] A computer-readable storage medium, including: a computer program that can be loaded and executed by a processor to execute the above-mentioned litter humidity monitoring method.

[0045] In a fourth aspect, the present application provides a computer program product, adopting the following technical solution:

[0046] A computer program product, including a computer program, and when the computer program is executed by a processor, it implements the above-mentioned litter humidity monitoring method.

[0047] In summary, the present application includes at least one of the following beneficial technical effects:

[0048] By performing feature recognition on the monitoring image, it is convenient to timely discover potential hazard situations in the monitoring area. When a potential hazard area is determined, instead of directly giving a warning prompt, the humidity change situation of the litter in the potential hazard area within a future period of time is analyzed and predicted, thereby facilitating the reduction of false alarms or missed alarms. Among them, since the soil humidity and animal activities in the potential hazard area will directly affect the humidity change of the litter, therefore, by comprehensively considering the soil humidity information and animal activity information of the potential hazard area within a future period of time for the humidity change situation of the litter in the potential hazard area, it is convenient to improve the adaptability between the prediction result and the actual situation, thereby facilitating the improvement of the accuracy of monitoring and warning the litter humidity.

[0049] Since animal activities may affect the form of litter, which may in turn affect litter humidity, it is necessary to analyze the animal activities present in the potential hazard area. However, since the routes and ranges of animal activities may change, when there are no animal activities in the potential hazard area, the potential impacts on the potential hazard area can be indirectly analyzed by analyzing the information on animal activities in the affected area, which helps to improve the accuracy when determining the predicted hazard impact value. Description of the Drawings

[0050] Figure 1 is a schematic flowchart of a method for monitoring litter humidity in an embodiment of the present application;

[0051] Figure 2 is a schematic flowchart of an optimization process for predicting hazard impact values in an embodiment of the present application;

[0052] Figure 3 is a schematic structural diagram of an electronic device in an embodiment of the present application. Detailed Embodiments

[0053] The following will further elaborate on the present application in conjunction with the Figures 1 to 3 drawings for a more detailed description.

[0054] Those skilled in the art can make modifications to this embodiment without creative contributions as needed after reading this specification, but as long as they are within the scope of the claims of the present application, they are protected by the patent law.

[0055] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts fall within the scope of protection of the present application.

[0056] It should be noted that in the alternative embodiments of the present application, for relevant data such as object information, when the embodiments in the present application are applied to specific products or technologies, object permission or consent needs to be obtained, and the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions. That is to say, if the embodiments in the present application involve data related to an object, it needs to be obtained under the authorization and consent of the object, the authorization and consent of relevant departments, and compliance with the relevant laws, regulations, and standards of the country and region. In the embodiments, if personal information is involved, the acquisition of all personal information requires the consent of the individual. If sensitive information is involved, the separate consent of the information subject needs to be obtained, and the embodiments also need to be implemented under the authorization and consent of the object.

[0057] Specifically, the embodiment of the present application provides a litter humidity monitoring method, which is executed by an electronic device. The electronic device can be a server or a terminal device. Among them, the server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected through wired or wireless communication methods, and the embodiments of the present application do not limit this here.

[0058] Reference Figure 1 , Figure 1 is a schematic flowchart of a litter humidity monitoring method in the embodiment of the present application. The method includes steps S110 - S140, where:

[0059] Step S110: Obtain a monitoring image and identify the litter feature information in the monitoring image. The litter feature information includes litter color features, litter texture features, and litter shape features.

[0060] Specifically, the monitoring image is an environmental image corresponding to the area to be monitored, which can be collected by an image acquisition device set in the environment to be monitored and then uploaded to the electronic device. The area to be monitored is the area where litter humidity needs to be monitored, which can be an area containing litter such as a forest or a grassland. Litter is the organic matter naturally shed from vegetation in the natural ecosystem. For example, fallen leaves, fallen fruits, bark fragments, etc. The litter in the area to be monitored is often continuously distributed. If the litter humidity is low, once a certain piece of litter is ignited, the flame generated by the combustion will spread rapidly along the continuous litter. However, the probability of high-humidity litter catching fire is low, and even if it is ignited, it will inhibit the spread of the fire. Therefore, litter humidity is a key indicator for evaluating the fire risk of the area to be monitored.

[0061] Since the color of litter changes with its own humidity. For example, when the humidity of litter is high, water makes the pigments in the litter more saturated, so the color presented is usually darker. Correspondingly, when the humidity of litter is low, the pigment concentration in the litter decreases, so the color presented is generally lighter. The texture of litter also changes with its own humidity. When the humidity of litter is high, water makes the cell structure expand, so the litter usually has a soft and deformable texture when the humidity is high. When the humidity of litter is low, the cell structure shrinks due to water loss. Therefore, it may cause the litter to become hard and have a rough texture, making it easy to break. In addition, the change in the shape of litter can also indirectly reflect humidity. For example, litter with high humidity tends to maintain its original shape and is not easily deformed or broken, but litter with low humidity may be in a state of curling, shrinking or fragmentation. Therefore, in the embodiments of the present application, the humidity of litter is preliminarily analyzed and confirmed by analyzing the color characteristics, texture characteristics and shape characteristics of litter.

[0062] The feature information of litter contained in the monitoring image can be directly identified by using a preset feature recognition algorithm. Among them, a color histogram or a color matrix can be used to quantify the color characteristics of litter in the monitoring image, a gray-level co-occurrence matrix can be used to describe the texture characteristics of litter in the monitoring image, and an edge detection algorithm can be used to identify the shape characteristics of litter in the monitoring image. The specific preset feature recognition algorithm is not specifically limited in the embodiments of the present application, as long as the feature information of litter can be determined from the monitoring image.

[0063] Step S120: Based on the litter feature information and the preset hidden danger feature information, determine the hidden danger area and the hidden danger area feature information from the monitoring image, and determine the humidity value of the litter in the hidden danger area based on the hidden danger area feature information. The litter feature information corresponding to the hidden danger area satisfies the preset hidden danger feature information.

[0064] Specifically, the preset potential hazard feature information is used as the potential hazard judgment condition. For example, the preset potential hazard feature information may be that the color depth of the litter is lower than the preset depth value, the texture of the litter is the preset potential hazard texture, and the shape of the litter is the preset potential hazard shape. The specific preset depth, preset potential hazard texture, and preset potential hazard shape are not specifically limited in the embodiments of the present application and can be determined by relevant staff based on historical experimental data and then uploaded to the electronic device. When determining the potential hazard area, the monitoring image can be first divided into regions. Correspondingly, the litter feature information corresponding to the monitoring image is also divided to obtain multiple divided regions and the region feature information corresponding to each divided region. Each region feature information is compared with the preset potential hazard feature information to determine whether the region feature information meets the potential hazard judgment condition, and the divided region that meets the potential hazard judgment condition is determined as the potential hazard area. The number of potential hazard areas can be 0, 1, or multiple, and the specific number is not specifically limited in the embodiments of the present application.

[0065] The litter humidity values corresponding to different potential hazard area features are different. Among them, the first humidity value corresponding to the litter color feature, the second humidity value corresponding to the litter texture feature, and the third humidity value corresponding to the litter texture feature can be first determined respectively, and then the first humidity value, the second humidity value, and the third humidity value are summarized to obtain the litter humidity value of the potential hazard area. Specifically, the first humidity value corresponding to the litter color depth can be determined according to the preset color mapping relationship, and the preset color mapping relationship includes the first humidity values corresponding to different color depth intervals; the second humidity value corresponding to the litter texture can be determined according to the preset texture mapping relationship, and the preset texture mapping relationship includes the second humidity values corresponding to different texture features; the third humidity value corresponding to the litter shape can be determined according to the preset shape mapping relationship, and the preset shape mapping relationship includes the third humidity values corresponding to different shape features. Among them, the specific contents of the preset color mapping relationship, the preset texture mapping relationship, and the preset shape mapping relationship are not specifically limited in the embodiments of the present application and can be determined by relevant staff based on historical experimental data and then uploaded to the electronic device.

[0066] Step S130: Obtain the impact feature information corresponding to the potential hazard area in the first preset time period, and determine the predicted potential hazard impact value corresponding to the potential hazard area in the first preset time period based on the impact feature information. The impact feature information includes soil humidity information and animal activity information.

[0067] Specifically, the litter humidity value of the potential hazard area determined based on the potential hazard area characteristic information is the initial value, that is, the humidity value determined by analyzing the characteristics of the litter itself, such as color, texture, and shape. However, the litter humidity is also extremely susceptible to the influence of the surrounding environment. For example, the soil in direct or indirect contact with the litter, and the animal activity information in direct or indirect contact with the litter. Among them, due to the water exchange between the soil and the litter, the water in the soil can rise into the litter through capillary action, and the water in the litter can also seep into the soil. Therefore, the change in soil humidity will directly affect the humidity of the litter. When animals graze, build nests, or move above the litter, it will cause a certain degree of loosening or accumulation of the litter, thereby affecting the structure and humidity of the litter. The first preset time period is a period of time after the current moment. The corresponding duration of the first preset time period can be 1 hour or 2 hours. The specific duration is not specifically limited in the embodiments of the present application. By comprehensively considering the soil humidity information and animal activity information of the potential hazard area in the future period of time, the adaptability between the prediction result and the actual situation can be improved. Among them, the soil humidity information can be collected by a soil humidity collection device set in the area to be monitored and then uploaded to the electronic device. The animal activity information can be obtained by performing action recognition on the activity images collected by an image collection device set in the area to be monitored, or can be collected by a tracking device set in the area to be monitored and then uploaded to the electronic device.

[0068] Further, determining the predicted potential hazard influence value corresponding to the first preset time period based on the influence characteristic information specifically may include:

[0069] Identifying the soil humidity information and determining the soil humidity change information of the potential hazard area within the first preset time period; identifying the animal behavior types included in the animal activity information, and determining the morphological change information of the potential hazard litter in the potential hazard area within the first preset time period based on the animal behavior types; obtaining the area simulation model corresponding to the potential hazard area, and importing the potential hazard area characteristic information, soil humidity change information, and morphological change information into the area simulation model for simulation to obtain the simulated change image of the litter corresponding to the first preset time period; identifying the simulated litter characteristic information included in the simulated litter change image, and determining the predicted potential hazard influence value corresponding to the potential hazard area within the first preset time period based on the simulated litter characteristic information.

[0070] Specifically, the soil change information is the soil humidity value corresponding to each moment within the first preset time period. The types of animal behaviors included in the animal activity information include a loosening behavior type and a piling behavior type. Among them, the loosening behavior refers to a behavior that causes the original litter structure to change and become loose after animal activities. For example, insects nibble or turn over dropped food above the litter. The piling behavior type refers to a behavior that causes the original litter structure to change and become piled up after animal activities. For example, birds or insects pile up the litter when building nests or seeking shelters. The morphological change information is the litter morphological edge value corresponding to each moment within the first preset time period.

[0071] When obtaining the regional simulation model corresponding to the hidden danger area, it can be intercepted from the preset simulation model based on the regional characteristics corresponding to the hidden danger area. Among them, the preset simulation model has the same basic biological data as the area to be monitored. Based on the preset simulation model, the change situation of the litter humidity occurring within the area to be monitored can be simulated. The method for determining the regional simulation model is not specifically limited in the embodiments of this application. The simulated change image of the litter corresponding to the first preset time period is the simulated change situation of the litter humidity under the influence of the soil humidity change information and the morphological change information.

[0072] The simulated litter characteristic information includes the simulated litter color characteristic, the simulated litter texture characteristic, and the simulated litter shape characteristic. The method for identifying the simulated litter characteristic information from the simulated litter change image can refer to the method for identifying the litter characteristic information from the monitoring image in the above embodiments. The method for determining the predicted hidden danger influence value corresponding to the hidden danger area within the first preset time period based on the simulated litter characteristic information can refer to the method for determining the predicted hidden danger influence value corresponding to the hidden danger area within the first preset time period based on the influence characteristic information in the above embodiments, and will not be elaborated here.

[0073] Step S140: Update the litter humidity value of the hidden danger area based on the predicted hidden danger influence value to obtain the litter humidity value of the target hidden danger area. When the litter humidity value of the target hidden danger area is lower than the preset warning threshold, generate a prompt message based on the humidity values of the hidden danger area and the target hidden danger area.

[0074] Specifically, the litter humidity value of the target hidden danger area is the optimized result of the litter humidity value of the hidden danger area, which may be higher than the litter humidity value of the hidden danger area or lower than the litter humidity value of the hidden danger area. However, the accuracy of the updated or optimized litter humidity value of the target hidden danger area is higher. When the litter humidity value of the target hidden danger area is lower than the preset warning threshold, a prompt message needs to be generated to remind the relevant responsible personnel to check and eliminate the abnormal hidden danger situation in the hidden danger area. Among them, the specific preset warning threshold is not specifically limited in the embodiments of this application and can be set by technical personnel.

[0075] For the embodiments of the present application, by performing feature recognition on the monitoring images, it is convenient to timely discover potential hazards in the monitoring area. When the potential hazard area is determined, instead of directly giving a warning prompt, the humidity change of the litter in the potential hazard area within a future period of time is analyzed and predicted, so as to reduce the situation of false alarms or missed alarms. Among them, since the soil humidity and animal activities in the potential hazard area will directly affect the humidity change of the litter, therefore, by comprehensively considering the soil humidity information and animal activity information of the potential hazard area within a future period of time for the humidity change of the litter in the potential hazard area, it is convenient to improve the adaptability between the prediction result and the actual situation, and thus convenient to improve the accuracy of monitoring and warning the humidity of the litter.

[0076] Further, in order to improve the accuracy of predicting the potential hazard impact value, the method provided by the embodiments of the present application further includes:

[0077] Obtain the weather characteristic information corresponding to the potential hazard area in the first preset time period. Based on the weather characteristic information, determine the weather change type corresponding to the potential hazard area in the first preset time period. The weather change type includes a stable type and an unstable type. The weather characteristic information includes wind level and rainfall; when the weather change type is unstable, determine the weather impact level based on the weather characteristic information; based on the morphological change information of the potential hazard litter and the weather impact level within the first preset time period, determine the first litter humidity impact value caused by the weather characteristic information on the potential hazard area within the first preset time period; optimize the predicted potential hazard impact value corresponding to the potential hazard area in the first preset time period based on the first litter humidity impact value.

[0078] Specifically, the weather change situation of the potential hazard area within a future period of time can be obtained through satellite remote sensing data or radar data, etc. Among them, the weather characteristic information includes, but is not limited to, wind direction and rainfall. By analyzing the weather characteristic information corresponding to the first time period, it is convenient to judge whether the weather change is stable within the first preset time period. When the weather change is relatively stable, the impact of the weather change on the litter humidity can be ignored; when the weather change is unstable, it is necessary to further analyze the impact of the weather characteristic information on the litter humidity.

[0079] When determining the type of weather change based on weather feature information, the weather feature information corresponding to the first preset time period can be compared with the preset judgment conditions. When the weather feature information meets the preset judgment conditions, the type of weather change can be determined as the stable type; when the weather feature information does not meet the preset judgment conditions, the type of weather change can be determined as the unstable type. Among them, the preset judgment conditions may include that the wind level is not higher than the preset level and the rainfall is not higher than the preset rainfall. The specific preset level and preset rainfall are not specifically limited in the embodiments of the present application. When there is a wind level higher than the preset level or a rainfall higher than the preset rainfall in the weather feature information, it is necessary to further analyze the impact of different wind levels and rainfall on the litter humidity. Different wind levels and different rainfall amounts have different weather impact levels on the litter humidity in the hidden danger area.

[0080] Since the change in the litter morphology will affect the contact area between the litter and the surrounding air and moisture, when facing different litter morphologies, the same wind level and rainfall will have different effects on the litter humidity. That is, when determining the first litter humidity impact value, it is necessary to consider both the weather impact level and the morphology change information. Different wind levels and rainfall amounts correspond to different weather impact levels, which can be determined according to the preset level mapping relationship. The preset level mapping relationship includes the weather impact levels corresponding to different combinations of wind levels and rainfall amounts. The specific content of this mapping relationship is not specifically limited in the embodiments of the present application. When determining the first litter humidity impact value, the moment humidity impact value corresponding to each moment within the first preset time period in the morphology change information can be determined based on the litter morphology edge value corresponding to each moment, and finally the first litter humidity impact value is determined by summarizing the moment humidity impact values corresponding to each moment. Among them, the humidity impact values corresponding to different weather impact levels under different litter morphology edge values can be determined according to the preset comparison impact mapping relationship. The preset comparison impact mapping relationship includes the humidity impact values corresponding to different weather impact levels when facing different litter morphology edge values, which can be determined by relevant staff based on historical experimental data and then uploaded to the electronic device. The specific content is not specifically limited in the embodiments of the present application.

[0081] Optimize the predicted hidden danger impact value corresponding to the hidden danger area in the first preset time period based on the first litter humidity impact value, that is, update the predicted hidden danger impact value based on the first litter humidity impact value, so as to improve the accuracy of the predicted hidden danger impact value.

[0082] Furthermore, when the impact feature information corresponding to the hidden danger area does not include animal activity information, the method provided in the embodiments of the present application further includes:

[0083] Determine the influence area of the potential hazard area and the influence interval between the potential hazard area and the influence area from the monitoring image based on weather feature information, and determine whether there is corresponding animal activity information in the influence area; if so, determine the influence morphological change information of the influence litter in the influence area within the first preset time period according to the animal activity information; based on the influence morphological change information and the influence interval, determine the second litter humidity influence value caused by the influence area on the potential hazard area within the first preset time period; optimize the predicted hazard influence value corresponding to the potential hazard area within the first preset time period based on the second litter humidity influence value.

[0084] Specifically, since animal activities may affect the morphology of litter, which may in turn affect the litter humidity, it is necessary to analyze the animal activity conditions in the potential hazard area. However, since the animal activity routes and ranges may change, when there are no animal activities in the potential hazard area, the possible impacts on the potential hazard area can be indirectly analyzed by analyzing the animal activity information in the influence area. When determining the influence area corresponding to the potential hazard area, the wind direction included in the weather feature information can be identified first. The influence area is the area where the air flow range can cover the potential hazard area under the action of the wind direction. For example, there are two existing areas, namely area a and area b in sequence from west to east, and the wind direction is from west to east. At this time, it can be determined that area a is the influence area of area b. When determining the influence interval between the influence area and the potential hazard area, the potential hazard center point of the potential hazard area and the influence center point of the influence area can be determined first from the monitoring image, and then the influence interval can be determined by calculating the pixel distance between the potential hazard center point and the influence center point. The method for determining the influence interval is not specifically limited in the embodiments of the present application.

[0085] The method for determining the influence morphological change information corresponding to the influence area according to the animal activity information can refer to the method for determining the corresponding morphological change information according to the animal activity information in the above embodiments, which will not be elaborated here. When there are animal activities in the influence area, the animal activities may cause changes in the humidity of the influence litter in the influence area, thereby causing changes in the air humidity corresponding to the influence area. Under the influence of the weather feature information, the change in the air humidity in the influence area may cause changes in the air humidity in the potential hazard area, thereby causing changes in the litter humidity in the potential hazard area.

[0086] Different influence morphological change information results in different degrees of influence on the litter humidity in the potential hazard area by the influence area. Further, the specific process of determining the second litter humidity influence value caused by the influence area on the potential hazard area within the first preset time period based on the influence morphological change information and the influence interval includes step S1 and step S2, as Figure 2 shown, where:

[0087] Step S1: Determine the influence range wave map based on the information of influencing morphological changes. The influence range wave map contains multiple range wave dimensions, and the corresponding influence rates of different range wave dimensions are different.

[0088] Specifically, obtain the influencing weather characteristic information corresponding to the influencing area in the first preset time period, and then determine the target influence value corresponding to the influencing area based on the influencing weather characteristic information and the information of influencing morphological changes. The specific method for determining the influence value can refer to the method in the above-mentioned embodiment for determining the first litter humidity influence value caused by the weather characteristic information on the potential hazard area in the first preset time period based on the morphological change information of the potential hazard litter and the weather influence level, which will not be elaborated here. After determining the influence rate, it is necessary to divide the influence interval into multiple range wave dimensions. The interval difference between different range wave dimensions can be the same or show an increasing trend, which is not specifically limited in the embodiments of the present application. The influence range wave map contains multiple range wave dimensions and the corresponding influence rate of each range wave dimension. For example, the influence rate corresponding to the range wave dimension a is 100%, the influence rate corresponding to the range wave dimension b is 80%, and the influence rate corresponding to the range wave dimension c is 60%.

[0089] Step S2: Determine the target influence rate caused by the influencing area on the potential hazard area in the first preset time period from the influence range wave map based on the influence interval, and determine the second litter humidity influence value based on the target influence rate.

[0090] Specifically, after determining the influence range wave map, it is necessary to first determine the corresponding target influence rate from the influence range wave map according to the influence interval, and then determine the corresponding second litter humidity influence value according to the target influence rate and the target influence value. By refining the influence of the influencing area on the potential hazard area through the influence interval, it is convenient to improve the accuracy when determining the second litter humidity influence value, and then optimize the predicted potential hazard influence value corresponding to the potential hazard area in the first preset time period through the second litter humidity influence value, which is convenient to further improve the accuracy when determining the predicted potential hazard influence value.

[0091] Furthermore, in order to facilitate reducing the probability of fire hazard occurrence, the method provided in the embodiments of the present application further includes:

[0092] If no response information is detected in the second preset time period, then determine the litter spraying amount based on the humidity difference between the litter humidity value of the target potential hazard area and the preset warning threshold; determine the spraying moment based on the second preset time period, and generate spraying instruction information based on the spraying moment and the litter spraying amount.

[0093] Specifically, the second preset time period is a period of time after the generation of the prompt message. The specific duration is not specifically limited in the embodiments of the present application. The generation of the prompt message indicates that the humidity of the litter in the potential hazard area is relatively low, and the probability of a fire hazard is relatively high. At this time, the generated prompt message is used to prompt the relevant staff to increase the humidity of the litter in the potential hazard area or to check for ignition points in the potential hazard area to prevent a fire from occurring in the potential hazard area. If the relevant staff fails to respond in a timely manner, the spraying device set in the area to be monitored can be controlled to perform a spraying operation on the potential hazard area.

[0094] When performing a spraying treatment on the potential hazard area, a specific spraying amount can be set or the spraying operation can be performed randomly, as long as it can increase the humidity of the litter in the spraying area. Among them, the litter spraying amount can be determined based on the humidity difference between the humidity value of the litter in the target potential hazard area and the preset warning threshold, that is, after the spraying is completed, the humidity value of the litter in the target potential hazard area is not lower than the preset warning threshold. The specific preset warning threshold is not specifically limited in the embodiments of the present application.

[0095] An electronic device is provided in the embodiments of the present application, such as Figure 3 shown. Figure 3 The electronic device 300 shown includes: a processor 301 and a memory 303. Among them, the processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 300 may further include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation to the embodiments of the present application.

[0096] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logical blocks, modules, and circuits described in combination with the disclosure of the present application. The processor 301 may also be a combination that implements a computing function, such as a combination including one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0097] The bus 302 may include a path for transmitting information among the above components. The bus 302 can be a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus 302 can be divided into an address bus, a data bus, a control bus, etc. For the sake of simplicity of representation, Figure 3 only one line is shown in Figure 3 , but it does not mean that there is only one bus or one type of bus.

[0098] The memory 303 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or it can also be an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0099] The memory 303 is used to store the application program code for executing the solution of this application, and is controlled by the processor 301 for execution. The processor 301 is used to execute the application program code stored in the memory 303 to implement the content shown in the foregoing method embodiments.

[0100] Among them, the electronic device includes but is not limited to: mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The electronic device shown is only an example and should not impose any limitations on the functions and usage scope of the embodiments of this application.

[0101] The embodiments of this application provide a computer-readable storage medium on which a computer program is stored. When it runs on a computer, it enables the computer to execute the corresponding content in the foregoing method embodiments.

[0102] An embodiment of the present application provides a computer program product, which includes a computer program that, when executed by a processor, implements the method in any of the above embodiments. Compared with the related art, in the embodiment of the present application, by performing feature recognition on the monitoring image, it is convenient to timely discover potential hazards in the monitoring area. When the potential hazard area is determined, instead of directly giving a warning prompt, the humidity change of litter in the potential hazard area within a certain period of time in the future is analyzed and predicted, so as to facilitate reducing false alarms or missed alarms. Among them, since the soil humidity and animal activities in the potential hazard area will directly affect the humidity change of litter, therefore, by comprehensively considering the soil humidity information and animal activity information of the potential hazard area within a certain period of time in the future for the humidity change of litter in the potential hazard area, it is convenient to improve the adaptability between the prediction result and the actual situation, and thus convenient to improve the accuracy of monitoring and warning the humidity of litter.

[0103] It should be understood that although the steps in the flowchart of the accompanying drawings are shown in sequence according to the indication of the arrows, these steps do not necessarily have to be executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages. These sub-steps or stages do not necessarily have to be executed at the same time, but can be executed at different times, and their execution order does not necessarily have to be sequential, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

[0104] The above are only some embodiments of the present application. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present application.

Claims

1. A method for monitoring litter humidity, characterized in that: include: Acquire a monitoring image, and identify litter feature information in the monitoring image, wherein the litter feature information includes litter color features, litter texture features, and litter shape features; Based on the litter feature information and the preset hidden danger feature information, determine the hidden danger area and the hidden danger area feature information from the monitoring image, and determine the litter humidity value of the hidden danger area based on the hidden danger area feature information, and the litter feature information corresponding to the hidden danger area meets the preset hidden danger feature information; Acquire impact characteristic information corresponding to the hidden danger area in a first preset time period, and determine a predicted hidden danger impact value corresponding to the hidden danger area in the first preset time period based on the impact characteristic information, wherein the impact characteristic information includes soil moisture information and animal activity information; Based on the predicted hidden danger impact value, the litter humidity value of the hidden danger area is updated to obtain the litter humidity value of the target hidden danger area, and when the litter humidity value of the target hidden danger area is lower than a preset warning threshold, a prompt message is generated based on the hidden danger area and the litter humidity value of the target hidden danger area; Wherein, determining the predicted hidden danger impact value corresponding to the hidden danger area in the first preset time period based on the impact characteristic information includes: Identifying the soil moisture information, and determining soil moisture change information of the hidden danger area within the first preset time period; Identifying the animal behavior type contained in the animal activity information, and determining the morphological change information of the hidden danger fallen objects in the hidden danger area within the first preset time period based on the animal behavior type; Acquire a regional simulation model corresponding to the hidden danger area, and import the characteristic information of the hidden danger area, the soil moisture change information, and the morphological change information into the regional simulation model for simulation, so as to obtain a litter simulation change image corresponding to the first preset time period; Identifying the simulated litter feature information contained in the simulated litter change image, and determining the predicted hidden danger impact value corresponding to the hidden danger area in the first preset time period based on the simulated litter feature information; The method further includes: Acquire weather characteristic information corresponding to the hidden danger area in the first preset time period, and determine the weather change type corresponding to the hidden danger area in the first preset time period based on the weather characteristic information, wherein the weather change type includes a stable type and an unstable type, and the weather characteristic information includes a wind level and a rainfall amount; When the weather change type is unstable, determining a weather impact level based on the weather characteristic information; Determine a first litter humidity impact value caused by the weather characteristic information on the hidden danger area within the first preset time period based on the morphological change information of the hidden danger litter within the first preset time period and the weather impact level; Optimizing the predicted hidden danger impact value corresponding to the hidden danger area in the first preset time period based on the first litter humidity impact value; When the impact feature information corresponding to the potential danger area does not include animal activity information, it also includes: Determine the impact area of ​​the hidden danger area and the impact interval between the hidden danger area and the impact area from the monitoring image based on the weather characteristic information, and judge whether there is corresponding animal activity information affecting the impact area; If yes, determining the morphological change information of the litter in the affected area within the first preset time period according to the affected animal activity information; Based on the impact morphological change information and the impact interval, determining a second litter humidity impact value caused by the impact area on the hidden danger area within the first preset time period; The predicted hidden danger impact value corresponding to the hidden danger area in the first preset time period is optimized based on the second litter humidity impact value.

2. A method for monitoring litter humidity according to claim 1, characterized in that: The determining, based on the impact morphological change information and the impact interval, a second litter humidity impact value caused by the impact area on the hidden danger area within the first preset time period includes: Determine an impact range wave diagram based on the impact morphology change information, wherein the impact range wave diagram includes multiple range wave dimensions, and different range wave dimensions correspond to different impact rates; The target impact rate of the impact area on the hidden danger area within the first preset time period is determined from the impact range wave diagram based on the impact interval, and the second litter humidity impact value is determined based on the target impact rate.

3. A method for monitoring litter humidity according to claim 1, characterized in that: Also includes: If no response information is detected within the second preset time period, determining the litter spraying amount based on the humidity difference between the litter humidity value in the target hidden danger area and the preset warning threshold; A spraying time is determined based on the second preset time period, and spraying instruction information is generated based on the spraying time and the litter spraying amount.

4. An electronic device, characterized in that: The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute a litter moisture monitoring method according to any one of claims 1-3.

5. A computer-readable storage medium, characterized in that: include: A computer program is stored which can be loaded by a processor and execute a method for monitoring the moisture content of litter as described in any one of claims 1 to 3.

6. A computer program product, characterized in that It comprises a computer program, which, when executed by a processor, implements the steps of a litter moisture monitoring method according to any one of claims 1 to 3.

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