Camping guardian method, system and vehicle based on fusion algorithm for detecting dangerous conditions

Abstract

The application discloses a camping guardian method and system based on a fusion algorithm for detecting dangerous conditions and a vehicle, comprising acquiring wild animal data corresponding to a current area, generating corresponding alarm strategies and setting guardian alarm levels based on the wild animal data, and simultaneously, presetting a geographic fence monitoring range; during operation of the camping guardian mode, acquiring wild animal vital sign data and activity trajectory data within the preset geographic fence monitoring range and performing fusion calculation to generate a threat assessment result; comparing the threat assessment result with a preset alarm threshold, and when the threat assessment result exceeds the preset alarm threshold, triggering the alarm strategy. The application solves the problems in the prior art that the vehicle guard mode or the sentinel mode has a small monitoring range, the effective detection distance is limited to the vicinity of the vehicle body, the wild animal threats in a long-distance range cannot be continuously identified and warned, and the vehicle is prone to frequent false triggering due to environmental vibrations and other factors.

Description

Technical Field

[0001] This invention relates to the field of vehicle intelligent sensing technology, and in particular to a camping protection method, system, and vehicle based on a fusion algorithm for detecting dangerous situations. Background Technology

[0002] With vehicle camping becoming increasingly common, when drivers and passengers camp in the wild, they are vulnerable to attacks from wild animals because they are no longer in the safe and isolated environment of their vehicles, which can lead to personal and property safety issues.

[0003] Currently, the guard mode or sentry mode of ordinary vehicles usually monitors the area around the vehicle for scratches or collisions after being activated by sensors. Its monitoring range is limited and it is prone to false triggering.

[0004] Current technologies monitor events involving vehicle contact or close-range collisions, with effective detection distance limited to the vicinity of the vehicle body, failing to cover a large area around it. Furthermore, existing methods rely on physical contact or vibration as triggers, failing to provide effective warnings for organisms continuously approaching from a distance before reaching the vehicle, and are prone to false triggers due to environmental vibrations. When occupants are camping in the wild or away from the vehicle, current technologies cannot continuously monitor and identify potential threats at long distances, creating blind spots in occupant safety. Summary of the Invention

[0005] To address the aforementioned issues, this invention proposes a camping protection method, system, and vehicle based on a fusion algorithm for detecting dangerous situations. This invention solves the problems of existing technologies where vehicle guard mode or sentry mode has a small monitoring range, the effective detection distance is limited to the vicinity of the vehicle body, it cannot continuously identify and warn of threats from wild animals at long distances, and it is prone to frequent false triggering due to environmental vibrations and other factors.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a camping protection method based on a fusion algorithm for detecting dangerous situations, comprising the following steps: When the vehicle is in camping protection mode, it acquires wildlife data corresponding to the current area, generates corresponding alarm strategies and sets protection alarm levels based on the wildlife data, and presets the geofence monitoring range. During the operation of the camping protection mode, the system acquires and integrates data on the vital signs and activity trajectories of wild animals within the preset geofence monitoring range to generate a threat assessment result. The threat assessment result is compared with a preset alarm threshold. When the threat assessment result exceeds the preset alarm threshold, the vehicle triggers an alarm strategy.

[0007] A further technical solution is that the wildlife data includes wildlife types, wildlife vital sign parameters, wildlife activity patterns, and wildlife movement models.

[0008] A further technical solution is that the alarm strategy includes at least one of the protection alarm levels; the protection alarm level includes sound alarm, sound and light alarm, and sound and light alarm plus dialing emergency contact numbers.

[0009] In a further technical solution, the sound alarm is a repulsion audio, which is determined according to the type of wild animal. The repulsion audio is the sound of a natural enemy or a repulsion sound corresponding to the type of wild animal.

[0010] A further technical solution is that the specific method of the fusion calculation is as follows: the acquired wildlife vital signs data and activity trajectory data within the preset geofence monitoring range are spatiotemporally aligned and weighted and fused, matched and compared with the wildlife action model, and the threat assessment result is output.

[0011] In a further technical solution, the preset geofence monitoring range is the range within which the vehicle-mounted sensor group monitors wild animals entering.

[0012] Secondly, this invention provides a camping protection system based on a fusion algorithm for detecting dangerous situations, comprising the following modules: The data acquisition and processing module is configured to: when the vehicle is in camping protection mode, acquire wildlife data corresponding to the current area, generate corresponding alarm strategies and set protection alarm levels based on wildlife data, and preset the geofence monitoring range. The fusion computing module is configured to: during the operation of the camping guardian mode, acquire wildlife vital signs data and activity trajectory data within the preset geofence monitoring range and perform fusion computing to generate threat assessment results; The alarm module is configured to compare the threat assessment result with a preset alarm threshold, and when the threat assessment result exceeds the preset alarm threshold, the vehicle triggers an alarm strategy.

[0013] Thirdly, the present invention provides a vehicle including a memory and a processor, and computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the camping protection method based on a fusion algorithm for detecting dangerous conditions as described in any one of the first aspects.

[0014] Fourthly, the present invention provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the camping protection method based on a fusion algorithm for detecting dangerous situations as described in any one of the first aspects.

[0015] Fifthly, the present invention provides a computer program product comprising executable instructions stored in a computer-readable storage medium; wherein, when the processor of a vehicle reads the executable instructions from the computer-readable storage medium and executes the executable instructions, it completes the camping protection method based on fusion algorithm for detecting dangerous conditions as described in any one of the first aspects.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention achieves real-time and accurate perception of the vital signs and activity trajectories of wild animals within a pre-defined geofence monitoring area by switching the vehicle-mounted sensor array to a non-driving monitoring mode and combining spatiotemporal alignment and weighted fusion calculations from multiple sensor types. This effectively overcomes the shortcomings of existing sentry-mode monitoring, such as short monitoring distance and limited sensing capabilities. Furthermore, by acquiring data on local wild animal types, vital sign parameters, activity patterns, and movement models, and generating targeted alarm strategies, it can play corresponding predator sounds or scare sounds for different wild animals, significantly improving the scare effect and reducing the probability of false triggers. Attached Figure Description

[0017] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0018] Figure 1 This is a flowchart illustrating the camping protection method based on a fusion algorithm for detecting dangerous situations, as described in this invention. Detailed Implementation

[0019] Embodiments of this application will now be described in more detail with reference to the accompanying drawings. While some embodiments of this application are shown in the drawings, it should be understood that this application can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this application. It should be understood that the drawings and embodiments of this application are for illustrative purposes only and are not intended to limit the scope of protection of this application. In the description of the embodiments of this application, the term "comprising" and similar terms should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "one embodiment" or "this embodiment" should be understood as "at least one embodiment".

[0020] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0021] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0022] Terminology Explanation: Camping Guard Mode is an active safety protection mode that is activated when the vehicle is not in a driving state. It uses the vehicle's sensor array to continuously monitor the surrounding environment, identify potential wildlife threats, and trigger corresponding alarm strategies.

[0023] A geofence is a virtual monitoring boundary defined with the vehicle as the center and a preset distance as the radius, used to define the effective monitoring range of a sensor.

[0024] The Intelligent Guard Controller is the core control unit responsible for receiving sensor data, performing fusion calculations, generating threat assessment results, and controlling alarm execution.

[0025] Multi-sensor fusion is a technical means of improving the accuracy and reliability of perception by performing spatiotemporal alignment and weighted fusion processing on data collected by multiple types of sensors such as lidar, millimeter-wave radar, infrared detection sensors, and cameras.

[0026] Threat assessment results refer to the quantitative scores output by the intelligent guardian controller based on the fused wildlife vital signs and activity trajectory data, matched and compared with the cloud-based action model. These scores are used to compare with preset alarm thresholds to decide whether to trigger an alarm.

[0027] The cloud platform is a remote service platform that stores and maintains data on wildlife types, vital signs parameters, activity patterns, and movement models, and receives measured data uploaded by vehicles to continuously update the models.

[0028] Example 1 In existing technologies, vehicle guard or sentry modes monitor physical contact or vibration events using sensors around the vehicle. Their core drawback is that the monitoring range is limited to the vicinity of the vehicle, making it unable to identify the vital signs and behavioral patterns of wild animals, unable to predict threats approaching from a distance, and prone to frequent false triggers due to environmental vibrations and other factors. When occupants leave the vehicle to camp in the wild, these modes create blind spots for occupant safety.

[0029] Based on the aforementioned shortcomings, this embodiment proposes a camping protection method based on fusion algorithms to detect dangerous situations. By switching the vehicle-mounted sensor group to a non-driving monitoring mode and combining it with cloud-based wildlife model data, a threat assessment result is generated using multi-sensor fusion calculation. When the threshold is exceeded, a graded alarm strategy is triggered, and the data is sent back to the cloud to form a closed-loop optimization. This method is significantly different from the existing technology that relies solely on physical contact to trigger the alarm.

[0030] like Figure 1 As shown in the figure, the specific technical solution of the camping protection method based on fusion algorithm for detecting dangerous situations provided in this embodiment is as follows: S1: Obtain wildlife data for the current area, generate corresponding alarm strategies and set protection alarm levels based on the wildlife data, and preset the geofence monitoring range.

[0031] In step S1, in response to the command to activate the camping guardian mode, the vehicle sensor group is switched from driving mode to non-driving monitoring mode, and wildlife data corresponding to the current area is obtained through the cloud platform. The wildlife data includes, but is not limited to, wildlife type, wildlife vital signs parameters, wildlife activity patterns, and wildlife movement models.

[0032] Specifically, the vehicle uses its built-in off-road map to determine whether its current location is within a preset wildlife activity area. When the determination is yes, the vehicle automatically triggers the camping protection mode activation command, without requiring manual operation from the user, thus achieving automated activation of the mode.

[0033] In response to the activation command, the onboard sensor array, originally used for driving purposes, including LiDAR, 4D millimeter-wave radar, ultrasonic radar, infrared detection sensors, cameras, Bluetooth antennas, and UWB antennas, is switched to non-driving monitoring mode to continuously monitor the vehicle's surroundings. Simultaneously, the vehicle obtains information on the types of wildlife, vital signs, activity patterns, and movement models of the wildlife in the current area via a cloud platform, and configures these parameters to the intelligent guardian controller. This dynamic acquisition of localized wildlife data via the cloud solves the problem of traditional fixed-parameter solutions being unable to adapt to the differences in wildlife species across different regions.

[0034] In step S1, the preset geofence monitoring range is the range within which the vehicle-mounted sensor group monitors wild animals entering, and the preset geofence monitoring range is determined based on the effective detection distance of the vehicle-mounted sensor group, with a monitoring range of 5 meters to 200 meters.

[0035] Based on the existing sensor monitoring accuracy, the effective range can be set to a maximum of 200 meters and a minimum of 5 meters, covering the complete threat perception range from near to far. The effective detection range characteristics of various sensors in the vehicle-mounted sensor group are as follows: the effective detection range of lidar can reach 150 to 200 meters, suitable for long-distance target localization and body contour recognition; the effective detection range of 4D millimeter-wave radar can reach 100 to 200 meters, suitable for all-weather, all-time target movement speed and distance detection; the effective detection range of infrared detection sensors is 30 to 80 meters, suitable for thermal imaging detection of vital signs at night or in obscured environments; the effective detection range of ultrasonic radar is 0.2 to 5 meters, suitable for accurate ranging of near-range targets; and the camera combined with image recognition algorithms can achieve an effective detection range of 50 to 100 meters under sufficient lighting conditions, suitable for visual recognition of target shape features. Geofencing can be configured into a single-layer or multi-layer nested structure according to user needs. For example, an outer warning zone (50 meters to 200 meters) and an inner alert zone (5 meters to 50 meters) can be set. When a target enters the outer warning zone, the system enters a high-frequency acquisition state. When the target enters the inner alert zone, the system immediately performs a threat assessment and prepares to trigger an alarm, thereby achieving a gradient response from far to near.

[0036] Users can manually adjust the geofence monitoring range on the vehicle's main unit's large screen according to the actual camping environment. The system automatically verifies whether the user's setting value is within the effective detection distance range of the sensor based on the currently activated sensor type. If the setting value exceeds the upper limit of the sensor's effective detection distance, the system will automatically correct the monitoring range to the maximum effective detection distance of the current sensor combination and prompt the user through a pop-up window on the large screen.

[0037] Alarm policies include at least one of the following levels: sound alarm only, sound and light combined alarm, and sound and light alarm with simultaneous dialing of emergency contacts. The default setting is sound and light alarm with simultaneous dialing of emergency contacts. The alarm policy level is configured and stored by the user via the vehicle before activating Camping Guardian Mode; the user can exit the configuration interface after clicking "remember".

[0038] The audible alarm plays a scare audio signal, which is determined based on the type of wild animal identified. The scare audio is either the sound of a predator or a scare signal corresponding to that type of wild animal. For example, when a wild boar is detected, the vehicle's audio system plays a simulated predator's call; when a wolf is detected, it plays a simulated shotgun sound, thus achieving precise scare-away for different wild animals.

[0039] S2: During the operation of the camping guardian mode, acquire and merge data on the vital signs and activity trajectory of wild animals within the preset geofence monitoring range to generate a threat assessment result.

[0040] In step S2, during the operation of the camping protection mode, the vehicle-mounted sensor group collects real-time data on the vital signs and activity trajectories of wild animals within the preset geofence monitoring range. The intelligent protection controller performs fusion calculations on the collected data to generate a threat assessment result, and compares the threat assessment result with a preset alarm threshold.

[0041] The fusion computing specifically includes: the intelligent guardian controller performs spatiotemporal alignment and weighted fusion processing on the wildlife vital signs and activity trajectory data collected by the vehicle-mounted sensor group, matches and compares the fused data with the wildlife action model issued by the cloud platform, and outputs threat assessment results.

[0042] Spatiotemporal alignment processing eliminates errors caused by differences in sampling times and spatial coordinate systems between different sensors, while weighted fusion processing dynamically allocates weights based on the reliability of each sensor in the current environment, significantly improving perception accuracy.

[0043] Specifically, the intelligent guardian controller extracts features from the fused data, generating vital sign feature vectors and trajectory feature vectors. The vital sign feature vectors include the target object's body temperature distribution, body shape, respiratory rate, and other vital signs. The trajectory feature vectors include the target object's direction of movement, speed, and distance changes from the vehicle. The intelligent guardian controller combines these two feature vectors into a comprehensive feature vector, and calculates its similarity with the standard feature templates for corresponding wild animal types in the wild animal motion model provided by the cloud platform. The similarity calculation uses a feature distance method, comparing the degree of matching between the current monitored target and known wild animal types by calculating the Euclidean distance or cosine similarity between the comprehensive feature vector and the standard feature template.

[0044] The intelligent guardian controller further incorporates dynamic trend characteristics such as whether the target object's movement direction is towards the vehicle, whether its movement speed is continuously increasing, and whether the distance to the vehicle is continuously decreasing. It then performs a comprehensive weighted calculation of the scores for each dimension, ultimately outputting a normalized threat assessment score. This score ranges from 0 to 1, with a higher score indicating a greater threat to the vehicle and personnel. The intelligent guardian controller compares this threat assessment score with a preset alarm threshold: if the threat assessment score exceeds the preset alarm threshold, a valid threat is determined, triggering subsequent alarm strategies; if the threat assessment score does not exceed the preset alarm threshold, the intelligent guardian controller continues to collect sensor data and execute the aforementioned fusion calculation and assessment process, achieving continuous dynamic monitoring of potential threats within the preset geofence monitoring range.

[0045] To reduce the overall vehicle power consumption during extended operation of the Camping Guardian Mode, the vehicle's power management controller manages the system via a local network, supplying power only to controllers and network units related to the monitoring functions of the onboard sensor group, while shutting down other controllers and network units unrelated to monitoring. This effectively reduces overall vehicle power consumption and extends the continuous operation time of the Camping Guardian Mode.

[0046] S3: Compare the threat assessment result with the preset alarm threshold. If the threat assessment result exceeds the preset alarm threshold, trigger the alarm strategy.

[0047] In step S3, when the threat assessment result exceeds the preset alarm threshold, the intelligent guardian controller triggers the alarm strategy, controls the sound system to play a drive-away audio, controls the lighting system to execute a light alarm, and initiates a call to the preset emergency contact through the communication module.

[0048] Specifically, after the alarm is triggered, the intelligent guardian controller actively prompts the user with a pop-up window on the vehicle's large screen. Simultaneously, it sends a signal to the audio system controller to activate the in-vehicle or external audio system to play a scare audio message corresponding to the identified type of wild animal. At the same time, the intelligent guardian controller sends a command to the lighting controller to activate the hazard lights as a warning.

[0049] Simultaneously with the sound and light alarms, the communication module proactively initiates a call to the preset emergency contacts based on their information, ensuring that external assistance can still be obtained even if the user cannot respond in a timely manner. This multi-dimensional linkage alarm mechanism effectively solves the problem of insufficient deterrence effect of single alarm methods in existing technologies.

[0050] S4: In response to the user's confirmation to close this alarm, upload the collected data on the type of wild animal, activity trajectory, and behavior pattern to the cloud platform to update the wild animal model data on the cloud platform.

[0051] In step S4, after the user confirms that the alarm is turned off through the vehicle's large screen, the intelligent guardian controller automatically uploads the data collected, such as the type of wild animal, its activity range and trajectory, and its behavior patterns, to the cloud platform. The cloud platform then improves the cloud data on the type of wild animal and publishes the updated wild animal model data to the off-road map system for subsequent use by other vehicles.

[0052] Example 2 This embodiment provides a camping protection system based on a fusion algorithm for detecting dangerous situations, including the following modules: The data acquisition and processing module is configured to: when the vehicle is in camping protection mode, acquire wildlife data corresponding to the current area, generate corresponding alarm strategies and set protection alarm levels based on wildlife data, and preset the geofence monitoring range. The fusion computing module is configured to: during the operation of the camping guardian mode, acquire wildlife vital signs data and activity trajectory data within the preset geofence monitoring range and perform fusion computing to generate threat assessment results; The alarm module is configured to compare the threat assessment result with a preset alarm threshold, and when the threat assessment result exceeds the preset alarm threshold, the vehicle triggers an alarm strategy.

[0053] The system also includes vehicles, onboard sensor arrays, intelligent protection controllers, vehicle main units, and a cloud platform. The vehicles are off-road or camping vehicles equipped with various types of onboard sensors, enabling a camping protection mode in outdoor camping scenarios.

[0054] The vehicle-mounted sensor suite includes, but is not limited to, lidar, 4D millimeter-wave radar, ultrasonic radar, infrared detection sensors, cameras, Bluetooth antennas, and UWB antennas, used to collect data on wildlife vital signs and activity trajectories. The intelligent guardian controller communicates with the vehicle-mounted sensor suite via a local area network to perform data fusion calculations and threat assessments. The vehicle's main unit communicates with a cloud platform via a wireless network to acquire wildlife model data and upload measured data. The cloud platform stores and updates wildlife types, vital sign parameters, activity patterns, and movement models, and publishes the updated data to the off-road map.

[0055] Based on the above system configuration, the specific steps of the method to be executed are as follows: S1: Obtain wildlife data for the current area, generate corresponding alarm strategies and set protection alarm levels based on the wildlife data, and preset the geofence monitoring range.

[0056] In step S1, in response to the command to activate the camping guardian mode, the vehicle sensor group is switched from driving mode to non-driving monitoring mode, and wildlife data corresponding to the current area is obtained through the cloud platform. The wildlife data includes, but is not limited to, wildlife type, wildlife vital signs parameters, wildlife activity patterns, and wildlife movement models.

[0057] Specifically, the vehicle uses its built-in off-road map to determine whether its current location is within a preset wildlife activity area. When the determination is yes, the vehicle automatically triggers the camping protection mode activation command, without requiring manual operation from the user, thus achieving automated activation of the mode.

[0058] In response to the activation command, the onboard sensor array, originally used for driving purposes, including LiDAR, 4D millimeter-wave radar, ultrasonic radar, infrared detection sensors, cameras, Bluetooth antennas, and UWB antennas, is switched to non-driving monitoring mode to continuously monitor the vehicle's surroundings. Simultaneously, the vehicle obtains information on the types of wildlife, vital signs, activity patterns, and movement models of the wildlife in the current area via a cloud platform, and configures these parameters to the intelligent guardian controller. This dynamic acquisition of localized wildlife data via the cloud solves the problem of traditional fixed-parameter solutions being unable to adapt to the differences in wildlife species across different regions.

[0059] In step S1, the preset geofence monitoring range is the range within which the vehicle-mounted sensor group monitors wild animals entering, and the preset geofence monitoring range is determined based on the effective detection distance of the vehicle-mounted sensor group, with a monitoring range of 5 meters to 200 meters.

[0060] Based on the existing sensor monitoring accuracy, the effective range can be set to a maximum of 200 meters and a minimum of 5 meters, covering the complete threat perception range from near to far. The effective detection range characteristics of various sensors in the vehicle-mounted sensor group are as follows: the effective detection range of lidar can reach 150 to 200 meters, suitable for long-distance target localization and body contour recognition; the effective detection range of 4D millimeter-wave radar can reach 100 to 200 meters, suitable for all-weather, all-time target movement speed and distance detection; the effective detection range of infrared detection sensors is 30 to 80 meters, suitable for thermal imaging detection of vital signs at night or in obscured environments; the effective detection range of ultrasonic radar is 0.2 to 5 meters, suitable for accurate ranging of near-range targets; and the camera combined with image recognition algorithms can achieve an effective detection range of 50 to 100 meters under sufficient lighting conditions, suitable for visual recognition of target shape features. Geofencing can be configured into a single-layer or multi-layer nested structure according to user needs. For example, an outer warning zone (50 meters to 200 meters) and an inner alert zone (5 meters to 50 meters) can be set. When a target enters the outer warning zone, the system enters a high-frequency acquisition state. When the target enters the inner alert zone, the system immediately performs a threat assessment and prepares to trigger an alarm, thereby achieving a gradient response from far to near.

[0061] Users can manually adjust the geofence monitoring range on the vehicle's main unit's large screen according to the actual camping environment. The system automatically verifies whether the user's setting value is within the effective detection distance range of the sensor based on the currently activated sensor type. If the setting value exceeds the upper limit of the sensor's effective detection distance, the system will automatically correct the monitoring range to the maximum effective detection distance of the current sensor combination and prompt the user through a pop-up window on the large screen.

[0062] Alarm policies include at least one of the following levels: sound alarm only, sound and light combined alarm, and sound and light alarm with simultaneous dialing of emergency contacts. The default setting is sound and light alarm with simultaneous dialing of emergency contacts. The alarm policy level is configured and stored by the user via the vehicle before activating Camping Guardian Mode; the user can exit the configuration interface after clicking "remember".

[0063] The audible alarm plays a scare audio signal, which is determined based on the type of wild animal identified. The scare audio is either the sound of a predator or a scare signal corresponding to that type of wild animal. For example, when a wild boar is detected, the vehicle's audio system plays a simulated predator's call; when a wolf is detected, it plays a simulated shotgun sound, thus achieving precise scare-away for different wild animals.

[0064] S2: During the operation of the camping guardian mode, acquire and merge data on the vital signs and activity trajectory of wild animals within the preset geofence monitoring range to generate a threat assessment result.

[0065] In step S2, during the operation of the camping protection mode, the vehicle-mounted sensor group collects real-time data on the vital signs and activity trajectories of wild animals within the preset geofence monitoring range. The intelligent protection controller performs fusion calculations on the collected data to generate a threat assessment result, and compares the threat assessment result with a preset alarm threshold.

[0066] The fusion computing specifically includes: the intelligent guardian controller performs spatiotemporal alignment and weighted fusion processing on the wildlife vital signs and activity trajectory data collected by the vehicle-mounted sensor group, matches and compares the fused data with the wildlife action model issued by the cloud platform, and outputs threat assessment results.

[0067] Spatiotemporal alignment processing eliminates errors caused by differences in sampling times and spatial coordinate systems between different sensors, while weighted fusion processing dynamically allocates weights based on the reliability of each sensor in the current environment, significantly improving perception accuracy.

[0068] Specifically, the intelligent guardian controller extracts features from the fused data, generating vital sign feature vectors and trajectory feature vectors. The vital sign feature vectors include the target object's body temperature distribution, body shape, respiratory rate, and other vital signs. The trajectory feature vectors include the target object's direction of movement, speed, and distance changes from the vehicle. The intelligent guardian controller combines these two feature vectors into a comprehensive feature vector, and calculates its similarity with the standard feature templates for corresponding wild animal types in the wild animal motion model provided by the cloud platform. The similarity calculation uses a feature distance method, comparing the degree of matching between the current monitored target and known wild animal types by calculating the Euclidean distance or cosine similarity between the comprehensive feature vector and the standard feature template.

[0069] The intelligent guardian controller further incorporates dynamic trend characteristics such as whether the target object's movement direction is towards the vehicle, whether its movement speed is continuously increasing, and whether the distance to the vehicle is continuously decreasing. It then performs a comprehensive weighted calculation of the scores for each dimension, ultimately outputting a normalized threat assessment score. This score ranges from 0 to 1, with a higher score indicating a greater threat to the vehicle and personnel. The intelligent guardian controller compares this threat assessment score with a preset alarm threshold: if the threat assessment score exceeds the preset alarm threshold, a valid threat is determined, triggering subsequent alarm strategies; if the threat assessment score does not exceed the preset alarm threshold, the intelligent guardian controller continues to collect sensor data and execute the aforementioned fusion calculation and assessment process, achieving continuous dynamic monitoring of potential threats within the preset geofence monitoring range.

[0070] To reduce the overall vehicle power consumption during extended operation of the Camping Guardian Mode, the vehicle's power management controller manages the system via a local network, supplying power only to controllers and network units related to the monitoring functions of the onboard sensor group, while shutting down other controllers and network units unrelated to monitoring. This effectively reduces overall vehicle power consumption and extends the continuous operation time of the Camping Guardian Mode.

[0071] S3: Compare the threat assessment result with the preset alarm threshold. If the threat assessment result exceeds the preset alarm threshold, trigger the alarm strategy.

[0072] In step S3, when the threat assessment result exceeds the preset alarm threshold, the intelligent guardian controller triggers the alarm strategy, controls the sound system to play a drive-away audio, controls the lighting system to execute a light alarm, and initiates a call to the preset emergency contact through the communication module.

[0073] Specifically, after the alarm is triggered, the intelligent guardian controller actively prompts the user with a pop-up window on the vehicle's large screen. Simultaneously, it sends a signal to the audio system controller to activate the in-vehicle or external audio system to play a scare audio message corresponding to the identified type of wild animal. At the same time, the intelligent guardian controller sends a command to the lighting controller to activate the hazard lights as a warning.

[0074] Simultaneously with the sound and light alarms, the communication module proactively initiates a call to the preset emergency contacts based on their information, ensuring that external assistance can still be obtained even if the user cannot respond in a timely manner. This multi-dimensional linkage alarm mechanism effectively solves the problem of insufficient deterrence effect of single alarm methods in existing technologies.

[0075] S4: In response to the user's confirmation to close this alarm, upload the collected data on the type of wild animal, activity trajectory, and behavior pattern to the cloud platform to update the wild animal model data on the cloud platform.

[0076] In step S4, after the user confirms that the alarm is turned off through the vehicle's large screen, the intelligent guardian controller automatically uploads the data collected, such as the type of wild animal, its activity range and trajectory, and its behavior patterns, to the cloud platform. The cloud platform then improves the cloud data on the type of wild animal and publishes the updated wild animal model data to the off-road map system for subsequent use by other vehicles.

[0077] Example 3 This embodiment provides a vehicle, including a memory and a processor, as well as computer instructions stored in the memory and running on the processor. When the processor executes the computer instructions, it completes the camping protection method based on fusion algorithm for detecting dangerous situations as described in Embodiment 1.

[0078] The vehicle implements a camping protection method based on a fusion algorithm to detect dangerous situations, specifically as follows: S1: Obtain wildlife data for the current area, generate corresponding alarm strategies and set protection alarm levels based on the wildlife data, and preset the geofence monitoring range.

[0079] In step S1, in response to the command to activate the camping guardian mode, the vehicle sensor group is switched from driving mode to non-driving monitoring mode, and wildlife data corresponding to the current area is obtained through the cloud platform. The wildlife data includes, but is not limited to, wildlife type, wildlife vital signs parameters, wildlife activity patterns, and wildlife movement models.

[0080] Specifically, the vehicle uses its built-in off-road map to determine whether its current location is within a preset wildlife activity area. When the determination is yes, the vehicle automatically triggers the camping protection mode activation command, without requiring manual operation from the user, thus achieving automated activation of the mode.

[0081] In response to the activation command, the onboard sensor array, originally used for driving purposes, including LiDAR, 4D millimeter-wave radar, ultrasonic radar, infrared detection sensors, cameras, Bluetooth antennas, and UWB antennas, is switched to non-driving monitoring mode to continuously monitor the vehicle's surroundings. Simultaneously, the vehicle obtains information on the types of wildlife, vital signs, activity patterns, and movement models of the wildlife in the current area via a cloud platform, and configures these parameters to the intelligent guardian controller. This dynamic acquisition of localized wildlife data via the cloud solves the problem of traditional fixed-parameter solutions being unable to adapt to the differences in wildlife species across different regions.

[0082] In step S1, the preset geofence monitoring range is the range within which the vehicle-mounted sensor group monitors wild animals entering, and the preset geofence monitoring range is determined based on the effective detection distance of the vehicle-mounted sensor group, with a monitoring range of 5 meters to 200 meters.

[0083] Based on the existing sensor monitoring accuracy, the effective range can be set to a maximum of 200 meters and a minimum of 5 meters, covering the complete threat perception range from near to far. The effective detection range characteristics of various sensors in the vehicle-mounted sensor group are as follows: the effective detection range of lidar can reach 150 to 200 meters, suitable for long-distance target localization and body contour recognition; the effective detection range of 4D millimeter-wave radar can reach 100 to 200 meters, suitable for all-weather, all-time target movement speed and distance detection; the effective detection range of infrared detection sensors is 30 to 80 meters, suitable for thermal imaging detection of vital signs at night or in obscured environments; the effective detection range of ultrasonic radar is 0.2 to 5 meters, suitable for accurate ranging of near-range targets; and the camera combined with image recognition algorithms can achieve an effective detection range of 50 to 100 meters under sufficient lighting conditions, suitable for visual recognition of target shape features. Geofencing can be configured into a single-layer or multi-layer nested structure according to user needs. For example, an outer warning zone (50 meters to 200 meters) and an inner alert zone (5 meters to 50 meters) can be set. When a target enters the outer warning zone, the system enters a high-frequency acquisition state. When the target enters the inner alert zone, the system immediately performs a threat assessment and prepares to trigger an alarm, thereby achieving a gradient response from far to near.

[0084] Users can manually adjust the geofence monitoring range on the vehicle's main unit's large screen according to the actual camping environment. The system automatically verifies whether the user's setting value is within the effective detection distance range of the sensor based on the currently activated sensor type. If the setting value exceeds the upper limit of the sensor's effective detection distance, the system will automatically correct the monitoring range to the maximum effective detection distance of the current sensor combination and prompt the user through a pop-up window on the large screen.

[0085] Alarm policies include at least one of the following levels: sound alarm only, sound and light combined alarm, and sound and light alarm with simultaneous dialing of emergency contacts. The default setting is sound and light alarm with simultaneous dialing of emergency contacts. The alarm policy level is configured and stored by the user via the vehicle before activating Camping Guardian Mode; the user can exit the configuration interface after clicking "remember".

[0086] The audible alarm plays a scare audio signal, which is determined based on the type of wild animal identified. The scare audio is either the sound of a predator or a scare signal corresponding to that type of wild animal. For example, when a wild boar is detected, the vehicle's audio system plays a simulated predator's call; when a wolf is detected, it plays a simulated shotgun sound, thus achieving precise scare-away for different wild animals.

[0087] S2: During the operation of the camping guardian mode, acquire and merge data on the vital signs and activity trajectory of wild animals within the preset geofence monitoring range to generate a threat assessment result.

[0088] In step S2, during the operation of the camping protection mode, the vehicle-mounted sensor group collects real-time data on the vital signs and activity trajectories of wild animals within the preset geofence monitoring range. The intelligent protection controller performs fusion calculations on the collected data to generate a threat assessment result, and compares the threat assessment result with a preset alarm threshold.

[0089] The fusion computing specifically includes: the intelligent guardian controller performs spatiotemporal alignment and weighted fusion processing on the wildlife vital signs and activity trajectory data collected by the vehicle-mounted sensor group, matches and compares the fused data with the wildlife action model issued by the cloud platform, and outputs threat assessment results.

[0090] Spatiotemporal alignment processing eliminates errors caused by differences in sampling times and spatial coordinate systems between different sensors, while weighted fusion processing dynamically allocates weights based on the reliability of each sensor in the current environment, significantly improving perception accuracy.

[0091] Specifically, the intelligent guardian controller extracts features from the fused data, generating vital sign feature vectors and trajectory feature vectors. The vital sign feature vectors include the target object's body temperature distribution, body shape, respiratory rate, and other vital signs. The trajectory feature vectors include the target object's direction of movement, speed, and distance changes from the vehicle. The intelligent guardian controller combines these two feature vectors into a comprehensive feature vector, and calculates its similarity with the standard feature templates for corresponding wild animal types in the wild animal motion model provided by the cloud platform. The similarity calculation uses a feature distance method, comparing the degree of matching between the current monitored target and known wild animal types by calculating the Euclidean distance or cosine similarity between the comprehensive feature vector and the standard feature template.

[0092] The intelligent guardian controller further incorporates dynamic trend characteristics such as whether the target object's movement direction is towards the vehicle, whether its movement speed is continuously increasing, and whether the distance to the vehicle is continuously decreasing. It then performs a comprehensive weighted calculation of the scores for each dimension, ultimately outputting a normalized threat assessment score. This score ranges from 0 to 1, with a higher score indicating a greater threat to the vehicle and personnel. The intelligent guardian controller compares this threat assessment score with a preset alarm threshold: if the threat assessment score exceeds the preset alarm threshold, a valid threat is determined, triggering subsequent alarm strategies; if the threat assessment score does not exceed the preset alarm threshold, the intelligent guardian controller continues to collect sensor data and execute the aforementioned fusion calculation and assessment process, achieving continuous dynamic monitoring of potential threats within the preset geofence monitoring range.

[0093] To reduce the overall vehicle power consumption during extended operation of the Camping Guardian Mode, the vehicle's power management controller manages the system via a local network, supplying power only to controllers and network units related to the monitoring functions of the onboard sensor group, while shutting down other controllers and network units unrelated to monitoring. This effectively reduces overall vehicle power consumption and extends the continuous operation time of the Camping Guardian Mode.

[0094] S3: Compare the threat assessment result with the preset alarm threshold. If the threat assessment result exceeds the preset alarm threshold, trigger the alarm strategy.

[0095] In step S3, when the threat assessment result exceeds the preset alarm threshold, the intelligent guardian controller triggers the alarm strategy, controls the sound system to play a drive-away audio, controls the lighting system to execute a light alarm, and initiates a call to the preset emergency contact through the communication module.

[0096] Specifically, after the alarm is triggered, the intelligent guardian controller actively prompts the user with a pop-up window on the vehicle's large screen. Simultaneously, it sends a signal to the audio system controller to activate the in-vehicle or external audio system to play a scare audio message corresponding to the identified type of wild animal. At the same time, the intelligent guardian controller sends a command to the lighting controller to activate the hazard lights as a warning.

[0097] Simultaneously with the sound and light alarms, the communication module proactively initiates a call to the preset emergency contacts based on their information, ensuring that external assistance can still be obtained even if the user cannot respond in a timely manner. This multi-dimensional linkage alarm mechanism effectively solves the problem of insufficient deterrence effect of single alarm methods in existing technologies.

[0098] S4: In response to the user's confirmation to close this alarm, upload the collected data on the type of wild animal, activity trajectory, and behavior pattern to the cloud platform to update the wild animal model data on the cloud platform.

[0099] In step S4, after the user confirms that the alarm is turned off through the vehicle's large screen, the intelligent guardian controller automatically uploads the data collected, such as the type of wild animal, its activity range and trajectory, and its behavior patterns, to the cloud platform. The cloud platform then improves the cloud data on the type of wild animal and publishes the updated wild animal model data to the off-road map system for subsequent use by other vehicles.

[0100] Example 4 This embodiment provides a computer-readable storage medium for storing computer instructions. When the computer instructions are executed by a processor, they complete the camping protection method based on a fusion algorithm for detecting dangerous situations as described in Embodiment 1.

[0101] Example 5 This embodiment provides a computer program product, which includes executable instructions stored in a computer-readable storage medium. When the vehicle's processor reads and executes the executable instructions from the computer-readable storage medium, it completes the camping protection method based on fusion algorithm for detecting dangerous situations as described in Embodiment 1.

[0102] The present invention also provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer-executable instructions, such as instructions included in program modules, which execute in a device on a target real or virtual processor to perform the processes / methods described above. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc., that perform specific tasks or implement specific abstract data types. In various embodiments, the functionality of program modules can be combined or divided among program modules as needed. The machine-executable instructions for the program modules can execute within a local or distributed device. In a distributed device, the program modules can reside in both local and remote storage media.

[0103] The computer program code used to implement the methods of the present invention may be written in one or more programming languages. This computer program code may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the computer or other programmable data processing device, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a computer, partially on a computer, as a stand-alone software package, partially on a computer and partially on a remote computer, or entirely on a remote computer or server.

[0104] In the context of this invention, computer program code or related data may be carried by any suitable carrier to enable a device, apparatus, or processor to perform the various processes and operations described above. Examples of carriers include signals, computer-readable media, and the like. Examples of signals may include electrical, optical, radio, sound, or other forms of propagation signals, such as carrier waves, infrared signals, etc.

[0105] Those skilled in the art will recognize that the units and algorithm steps described in conjunction with the embodiments herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0106] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

[0107] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0108] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A camping protection method based on a fusion algorithm for detecting dangerous situations, characterized in that, include: When the vehicle is in camping protection mode, it acquires wildlife data corresponding to the current area, generates corresponding alarm strategies and sets protection alarm levels based on the wildlife data, and presets the geofence monitoring range. During the operation of the camping protection mode, the system acquires and integrates data on the vital signs and activity trajectories of wild animals within the preset geofence monitoring range to generate a threat assessment result. The threat assessment result is compared with a preset alarm threshold. When the threat assessment result exceeds the preset alarm threshold, the vehicle triggers an alarm strategy.

2. The camping protection method based on fusion algorithm for detecting dangerous situations as described in claim 1, characterized in that, The wildlife data includes wildlife types, wildlife vital signs parameters, wildlife activity patterns, and wildlife movement models.

3. The camping protection method based on fusion algorithm for detecting dangerous situations as described in claim 1, characterized in that, The alarm strategy includes at least one of the protection alarm levels; the protection alarm levels include sound alarm, sound and light alarm, and sound and light alarm plus dialing emergency contact numbers.

4. The camping protection method based on fusion algorithm for detecting dangerous situations as described in claim 3, characterized in that, The sound alarm is a drive-away audio message, which is determined based on the type of wild animal. The drive-away audio message is either the sound of a predator or a drive-away sound that corresponds to the type of wild animal.

5. The camping protection method based on fusion algorithm for detecting dangerous situations as described in claim 1, characterized in that, The specific method of the fusion calculation is as follows: the acquired wildlife vital signs data and activity trajectory data within the preset geographic fence monitoring range are spatiotemporally aligned and weighted and fused, matched and compared with the wildlife action model, and the threat assessment result is output.

6. The camping protection method based on fusion algorithm for detecting dangerous situations as described in claim 1, characterized in that, The preset geofence monitoring range is the area within which the vehicle-mounted sensor array monitors wild animals entering.

7. A camping protection system based on a fusion algorithm for detecting dangerous situations, characterized in that, Includes the following modules: The data acquisition and processing module is configured to: when the vehicle is in camping protection mode, acquire wildlife data corresponding to the current area, generate corresponding alarm strategies and set protection alarm levels based on wildlife data, and preset the geofence monitoring range. The fusion computing module is configured to: during the operation of the camping guardian mode, acquire wildlife vital signs data and activity trajectory data within the preset geofence monitoring range and perform fusion computing to generate threat assessment results; The alarm module is configured to compare the threat assessment result with a preset alarm threshold, and when the threat assessment result exceeds the preset alarm threshold, the vehicle triggers an alarm strategy.

8. A vehicle, characterized in that, The method includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, which, when executed by the processor, perform the camping protection method based on a fusion algorithm for detecting dangerous situations as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, Used to store computer instructions, which, when executed by a processor, complete the camping protection method based on a fusion algorithm for detecting dangerous situations as described in any one of claims 1-6.

10. A computer program product comprising executable instructions stored in a computer-readable storage medium; wherein, When the vehicle's processor reads executable instructions from a computer-readable storage medium and executes the executable instructions, it completes the camping protection method based on a fusion algorithm for detecting dangerous situations as described in any one of claims 1-6.

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