Automobile anti-theft alarm method and system based on weight coefficient algorithm

Abstract

The application discloses a kind of automobile theftproof alarm method and system based on weight coefficient algorithm, method includes the following steps: lock car state, the situation in the car and locking mechanism situation are inducted to obtain relevant situation index parameter, each index parameter is given corresponding weight coefficient and is calculated, whether it is judged to enter theftproof state according to result, to more accurately judge whether there is theft car situation;In theftproof state, the identity of driver in the car is identified, whether it is judged to enter alarm state according to identity recognition structure, effectively avoids misjudgment situation;In alarm state, the position information of vehicle is collected in real time and alarm signal is sent simultaneously, and the position information and alarm information are responded by the mobile terminal of the owner to determine whether to generate processing data;Vehicle terminal responds processing data to carry out safe parking and alarm, to ensure that the owner can find the position of vehicle terminal.

Description

Technical Field

[0001] This invention relates to the field of automotive technology, and in particular to a method and system for automotive anti-theft alarms based on a weighted coefficient algorithm. Background Technology

[0002] Intelligent vehicles are ordinary vehicles with the addition of advanced sensors (such as radar and cameras), controllers, actuators, and other devices. Through onboard environmental perception systems and information terminals, they exchange information with people, vehicles, and roads, enabling the vehicle to have intelligent environmental perception capabilities. They can automatically analyze the safety and danger status of the vehicle and guide it to the destination according to the driver's wishes, ultimately replacing human operation. It is a comprehensive system integrating environmental perception, planning and decision-making, and multi-level assisted driving functions. It integrates computer, modern sensing, information fusion, communication, artificial intelligence, and automatic control technologies, and is a typical high-tech complex.

[0003] Car anti-theft technology is designed to prevent the theft of the car itself and the items inside. Existing car anti-theft technologies typically use mechanical or electronic locks to lock the car and trigger alarms. However, this type of technology is relatively basic, often resulting in false alarms and vulnerabilities that can be exploited by damaging the locking or alarm mechanisms. Therefore, it cannot provide truly robust and effective intelligent anti-theft protection for cars. Consequently, there is an urgent need for a more reasonable car anti-theft alarm solution to address the shortcomings of existing technologies. Summary of the Invention

[0004] In view of the fact that existing vehicle anti-theft technologies are not reasonable enough and are often accompanied by false alarms and misreporting, thus failing to effectively prevent theft, this invention provides a solution.

[0005] To achieve the above objectives, this invention provides a car anti-theft alarm method based on a weighted coefficient algorithm, comprising the following steps:

[0006] When the car is locked, the system senses the situation inside the car and the status of the locking mechanism to obtain relevant indicator parameters. Each indicator parameter is assigned a corresponding weight coefficient for calculation, and the system determines whether to enter the anti-theft state based on the result.

[0007] In anti-theft mode, the driver inside the vehicle is identified, and the alarm state is determined based on the identification structure.

[0008] In alarm mode, the vehicle's location information is collected in real time and an alarm signal is issued simultaneously. The vehicle owner's mobile device responds with location information and alarm information to determine whether to generate processing data; the vehicle responds with processing data to perform safe parking and alarm.

[0009] As an improvement of the present invention, the sensing step of the in-vehicle situation is as follows:

[0010] A1: Obtain the pressure parameters of the driver's seat;

[0011] A2: Determine whether the pressure parameter is within the pressure range formed by the owner's weight. If not, generate the first indicator parameter based on the threshold of the pressure parameter and the pressure range.

[0012] Determine whether the pressure parameter is within the range of the car owner's weight. If not, generate the first indicator parameter based on the threshold between the pressure parameter and the weight range.

[0013] The sensing steps of the locking mechanism are as follows:

[0014] B1: The unlocking method of the sensor-locking mechanism, and the unlocking time corresponding to the unlocking method;

[0015] B2: Determine whether the unlocking time is within the unlocking time range of the corresponding vehicle owner. If not, generate a second indicator parameter based on the threshold between the unlocking time and the unlocking time range.

[0016] As an improvement of the present invention, the calculation formula for assigning a corresponding weight coefficient to each index parameter is as follows:

[0017] M1 = First indicator parameter × First weighting coefficient + Second indicator parameter × Second weighting coefficient;

[0018] When the value M1 is greater than 10, the vehicle will be controlled to enter the anti-theft state.

[0019] As an improvement of the present invention, the first weighting coefficient is 0.3-0.5, the second weighting coefficient is 0.5-0.7, and the sum of the first weighting coefficient and the second weighting coefficient is 1.

[0020] As an improvement of the present invention, the steps for identifying the driver inside the vehicle are as follows:

[0021] C1: Issue identification command;

[0022] C2: Collect identification elements of people inside the vehicle and match them with whitelist information in the database;

[0023] C3: Output the matching results.

[0024] As an improvement of the present invention, the identification element is one or more of voiceprint ID, fingerprint ID, face ID, or matching password.

[0025] As an improvement to the present invention, the specific steps for vehicle-side response data processing are as follows:

[0026] Safe parking procedures:

[0027] D1: Generate autonomous driving permissions and collect and analyze the external environment of the vehicle;

[0028] D2: Issues anti-theft driving commands to control the vehicle to avoid obstacles and achieve safe parking;

[0029] Call the police:

[0030] E3: Generate alarm information;

[0031] E4: Broadcast alarm information.

[0032] As an improvement to the present invention, the safe docking step further includes:

[0033] D3: In the safe parking state, generate locking information and window opening information;

[0034] D4: Respond to the lock message and lock the steering wheel;

[0035] D5: In response to window opening information, the window partially opens to create a ventilation gap.

[0036] As an improvement to the present invention, the safe docking step further includes:

[0037] D6: Collect the outside temperature and the inside temperature of the vehicle, compare the results of the outside temperature and the inside temperature of the vehicle to determine whether to start the air conditioning module.

[0038] A car anti-theft alarm system based on a weighted coefficient algorithm is also provided to control the vehicle terminal to execute the above-mentioned method.

[0039] The beneficial effects of this invention are as follows: Compared with the prior art, this invention provides a car anti-theft alarm method and system based on a weighted coefficient algorithm. The method includes the following steps: In the locked state, the system senses the situation inside the vehicle and the status of the locking mechanism to obtain relevant indicator parameters. Each indicator parameter is assigned a corresponding weighted coefficient for calculation, and the system determines whether to enter the anti-theft state based on the result. In the anti-theft state, the system identifies the driver inside the vehicle and determines whether to enter the alarm state based on the identification structure. In the alarm state, the system collects the vehicle's location information in real time and simultaneously sends an alarm signal. The vehicle owner's mobile terminal responds with location information and alarm information to determine whether to generate processing data. The vehicle responds with the processing data to perform safe parking and alarm activation. By assigning weighted coefficients to the situation inside the vehicle and the working status of the locking mechanism for calculation, the system can more accurately determine whether there is a car theft, preventing the anti-theft system from failing to respond. Furthermore, the system verifies the driver again through the identification function, effectively avoiding misjudgments. Attached Figure Description

[0040] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0041] To more clearly illustrate the present invention, the invention will be further described below with reference to the accompanying drawings.

[0042] In the following description, specific examples of general elections are given to provide a more in-depth understanding of the invention. It is obvious that the described embodiments are merely some, not all, of the embodiments of the invention. It should be understood that the specific embodiments described are for illustrative purposes only and are not intended to limit the invention.

[0043] It should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of the said feature, integral, step, operation, element, or component, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, or combinations thereof.

[0044] Existing car anti-theft technologies aim to prevent the theft of the car itself and items inside. These technologies typically use mechanical or electronic locks to lock the car and trigger alarms. However, this approach is relatively rudimentary, often resulting in false alarms and vulnerabilities that allow for disruption of the locking and alarm mechanisms. Consequently, it fails to provide robust and effective intelligent anti-theft protection for cars. Therefore, a more reasonable car anti-theft alarm solution is urgently needed to address the shortcomings of existing technologies.

[0045] To address the aforementioned technical problems, this application provides a car anti-theft alarm method based on a weighted coefficient algorithm. Please refer to the appendix. Figure 1 This includes the following steps:

[0046] When the car is locked, the system senses the situation inside the car and the status of the locking mechanism to obtain relevant indicator parameters. Each indicator parameter is assigned a corresponding weight coefficient for calculation, and the system determines whether to enter the anti-theft mode based on the result. The addition of weight coefficients to calculate the situation at the vehicle end can more accurately determine whether to enter the anti-theft mode, preventing the anti-theft system from failing and causing serious losses to the car owner.

[0047] In anti-theft mode, the system identifies the driver inside the vehicle and determines whether to activate the alarm mode based on the identification structure. Further identification is performed to prevent false alarms. If the identification result is correct, the alarm mode is not activated.

[0048] In alarm mode, the system collects the vehicle's location information in real time and simultaneously sends an alarm signal. The owner's mobile device responds with the location information and alarm information to determine whether to generate processing data. The vehicle responds with the processing data to safely park and trigger the alarm. By sending alarm information to the owner's mobile device, the system can also record the in-vehicle video. Ultimately, the owner decides whether to enter alarm mode, further avoiding false alarms. Once alarm mode is activated, the vehicle enters safe parking and triggers the alarm, facilitating subsequent processing by the owner.

[0049] Among the vast amount of crime data, thieves exhibit significant differences in weight parameters and lock-picking habits. Therefore, in this embodiment, the sensing steps for the situation inside the vehicle are as follows:

[0050] A1: Obtain the pressure parameters of the driver's seat;

[0051] A2: Determine whether the pressure parameter is within the pressure range formed by the owner's weight. If not, generate the first index parameter based on the threshold of the pressure parameter and the pressure range. The pressure range is the parameter recorded over a period of time. For example, if the owner's weight is 120 catties, due to the shift in the center of gravity and the support formed by the feet, the detected pressure on the driver's seat is 90 catties. Record this pressure over 30 times to obtain 30 pressure data points for calculation and plotting into a discrete model. The pressure range can then be obtained as 86-92 catties. The above units are only for the purpose of illustrating this scheme. Of course, more accurate international weight units can be used to record the above weight. The same applies below.

[0052] The sensing steps of the locking mechanism are as follows:

[0053] B1: The unlocking method of the sensor-locking mechanism, and the unlocking time corresponding to the unlocking method;

[0054] B2: Determine if the unlocking time is within the corresponding owner's unlocking time range. If not, generate a second indicator parameter based on the threshold between the unlocking time and the unlocking time range. For example, by using the method described above to obtain the pressure range, the unlocking time can be obtained, and the unlocking time range can be determined. Often, thieves use tools to open the mechanical lock structure of the car door and enter the car. The time required is far greater than the normal opening speed of the car owner using a car key or electronic key. Therefore, it can effectively determine whether theft has occurred. A specific solution is to use an infrared detector to detect whether a tool has entered the mechanical keyhole, and record the time of entry into the mechanical keyhole and the time when the mechanical lock is fully opened. This is the unlocking time that needs to be determined.

[0055] In a further proposed solution, since the weight of the thief might be similar to that of the car owner, a higher weighting is applied to the unlocking time. The formula for calculating the weighting coefficient for each indicator parameter is as follows:

[0056] M1 = First indicator parameter × First weighting coefficient + Second indicator parameter × Second weighting coefficient;

[0057] When the value M1 is greater than 10, the vehicle will be controlled to enter the anti-theft state.

[0058] In the defined scheme, the first weighting coefficient is 0.3-0.5, the second weighting coefficient is 0.5-0.7, and the sum of the first and second weighting coefficients is 1. Naturally, the first and second weighting coefficients can be adjusted by the car owner to better suit their usage.

[0059] For a specific example, if a thief weighs 130 catties and enters the vehicle in 40 seconds, the pressure exerted on the driver by the thief is 106 catties, and the pressure exerted on the vehicle owner ranges from 84 to 96 catties. A threshold of 96 is selected, and the first indicator parameter is calculated to be 10. The vehicle owner's unlocking time ranges from 1.2 to 2 seconds, so 2 is selected as the unlocking time threshold parameter, and the second indicator parameter is 38. Using a first weighting coefficient of 0.3 and a second weighting coefficient of 0.7, M1 = 29.3, which corresponds to the vehicle entering anti-theft mode.

[0060] In this embodiment, the steps for identifying the driver inside the vehicle are as follows:

[0061] C1: Issues an identification command; instructs the occupants of the vehicle to perform identity verification;

[0062] C2: Collect identification elements of occupants inside the vehicle and match these elements with whitelist information in the database; first, a whitelist of identities is built for the vehicle owner and trusted users, and corresponding identity information is pre-recorded.

[0063] C3: Output the matching result; if the person in the vehicle cannot be matched with the whitelist information, then output that the vehicle should enter an alarm state; otherwise, it should not.

[0064] In a more specific scheme, the identification elements are one or more of voiceprint ID, fingerprint ID, face ID, or matching password. All of these can be achieved through sensor technology, so we will not go into details.

[0065] In this embodiment, the specific steps for vehicle-side response data processing are as follows:

[0066] Safe parking procedures:

[0067] D1: Generate autonomous driving permissions and collect and analyze the external environment of the vehicle;

[0068] D2: Issues anti-theft driving commands to control the vehicle to avoid obstacles and achieve safe parking;

[0069] First, by obtaining autonomous driving permissions, the system gains control of the vehicle from thieves. It also uses radar to obtain information about obstacles in the surrounding environment, enabling the vehicle to stop automatically.

[0070] Call the police:

[0071] E3: Generate alarm information;

[0072] E4: Broadcasts alarm information;

[0073] The system warns pedestrians and vehicles in the vicinity of the vehicle that theft has occurred and warns them to avoid the vehicle to prevent collisions with obstacles during autonomous driving.

[0074] Further plans include safe docking procedures that include:

[0075] D3: In the safe parking state, generate locking information and window opening information;

[0076] D4: In response to a locking signal, the steering wheel and doors are locked to prevent thieves from taking control of the vehicle and escaping.

[0077] D5: In response to the window opening signal, the window partially opens to create a ventilation gap; since the space inside the car is limited, thieves waiting for law enforcement officers and the car owner to arrive may experience insufficient oxygen. Therefore, creating a certain ventilation gap ensures the oxygen needs of the thieves.

[0078] In a further step, the safe docking procedures also include:

[0079] D6: Collect outside and inside vehicle temperatures, compare the results to determine whether to activate the air conditioning module; In hot weather, safe parking locations are often uncertain, and thieves are at risk of heatstroke while waiting for law enforcement and the vehicle owner to arrive due to excessive heat; Therefore, activating the air conditioning module improves the temperature inside the vehicle, ensuring that thieves can maintain the desired temperature.

[0080] A car anti-theft alarm system based on a weighted coefficient algorithm is also provided to control the vehicle terminal to execute the aforementioned method. It includes a main control module, a locking mechanism, an identification module, and a communication module that are interconnected. The main control module calculates the status of the vehicle interior and the locking mechanism, and determines whether the vehicle should enter anti-theft mode based on the calculation results. The identification module identifies the driver to determine whether to activate the alarm mode. The communication module communicates with the vehicle owner's mobile terminal to determine whether to initiate emergency safe parking and alarm broadcasting.

[0081] The advantages of this invention are:

[0082] By sending alarm information to the car owner's mobile device, the system can also record the in-vehicle video. The car owner can then decide whether to activate the alarm mode, further preventing false alarms. Once the alarm mode is activated, the vehicle will enter a safe parking state and trigger the alarm, making it easier for the car owner to take subsequent actions.

[0083] The above-disclosed embodiments are merely a few specific examples of the present invention, but the present invention is not limited thereto. Any variations that can be conceived by those skilled in the art should fall within the protection scope of the present invention.

Claims

1. A car burglar alarm method based on weight coefficient algorithm, characterized in that, Includes the following steps: When the car is locked, the system senses the situation inside the car and the status of the locking mechanism to obtain relevant indicator parameters. Each indicator parameter is assigned a corresponding weight coefficient for calculation, and the system determines whether to enter the anti-theft state based on the result. In anti-theft mode, the driver inside the vehicle is identified, and the alarm state is determined based on the identification structure. In alarm mode, the vehicle's location information is collected in real time and an alarm signal is issued simultaneously. The vehicle owner's mobile device responds with location information and alarm information to determine whether to generate processing data. The vehicle-side response processes data to enable safe parking and issue alarms; The sensing steps for the situation inside the vehicle are as follows: A1: Obtain the pressure parameters of the driver's seat; A2: Determine whether the pressure parameter is within the pressure range formed by the owner's weight. If not, generate the first indicator parameter based on the threshold of the pressure parameter and the pressure range. The sensing steps of the locking mechanism are as follows: B1: The unlocking method of the sensor-locking mechanism, and the unlocking time corresponding to the unlocking method; B2: Determine whether the unlocking time is within the unlocking time range of the corresponding car owner. If not, generate a second indicator parameter based on the threshold between the unlocking time and the unlocking time range. The formula for calculating each indicator parameter by assigning a corresponding weight coefficient is as follows: M1 = First indicator parameter × First weighting coefficient + Second indicator parameter × Second weighting coefficient; When the value M1 is greater than 10, the vehicle will be controlled to enter the anti-theft state.

2. The automobile burglar alarm method based on the weight coefficient algorithm according to claim 1, characterized in that, The first weighting coefficient is 0.3-0.5, the second weighting coefficient is 0.5-0.7, and the sum of the first weighting coefficient and the second weighting coefficient is 1.

3. The automobile burglar alarm method based on weight coefficient algorithm according to claim 1, characterized in that, The steps for identifying the driver inside the vehicle are as follows: C1: Issue identification command; C2: Collect identification elements of people inside the vehicle and match them with whitelist information in the database; C3: Output the matching results.

4. The car anti-theft alarm method based on weighted coefficient algorithm according to claim 3, characterized in that, The identification elements are one or more of the following: voiceprint ID, fingerprint ID, face ID, or matching password.

5. The car anti-theft alarm method based on weighted coefficient algorithm according to claim 1, characterized in that, The specific steps for vehicle-side response data processing are as follows: Safe parking procedures: D1: Generate autonomous driving permissions and collect and analyze the external environment of the vehicle; D2: Issues an anti-theft driving command to control the vehicle to avoid obstacles and achieve a safe stop; Call the police: E3: Generate alarm information; E4: Broadcast alarm information.

6. The car anti-theft alarm method based on weighted coefficient algorithm according to claim 5, characterized in that, The safe docking procedure also includes: D3: In the safe parking state, generate locking information and window opening information; D4: Respond to the lock message and lock the steering wheel; D5: In response to window opening information, the window partially opens to create a ventilation gap.

7. The car anti-theft alarm method based on weighted coefficient algorithm according to claim 6, characterized in that, The safe docking procedure also includes: D6: Collect the outside temperature and the inside temperature of the vehicle, compare the results of the outside temperature and the inside temperature of the vehicle to determine whether to start the air conditioning module.

8. A car anti-theft alarm system based on a weighted coefficient algorithm, characterized in that, To control the vehicle terminal to execute the car anti-theft alarm method based on the weighted coefficient algorithm as described in any one of claims 1-7.

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