Detection region adjustment method and apparatus, electronic device, and storage medium

Abstract

The application discloses a detection area adjustment method and device, electronic equipment and a storage medium, wherein the detection area adjustment method comprises the following steps: when it is detected that the elevator door of an elevator is in an open state, determining a target floor where a car of the elevator is currently stopped; acquiring floor data of the target floor; determining a target detection area of the target floor based on the floor data; and adjusting the detection area of a sensor of the elevator in a waiting hall of the target floor to the target detection area. The problem that the detection area of each floor is fixed and the collected image contains too much interference information, leading to misjudgment of the passenger movement trend, is solved. The sensor can collect images according to the target detection area determined according to the floor data when the car stops at different floors, so that the invalid information in the image is reduced, on the one hand, the accuracy of identifying the passenger movement trend can be improved, and on the other hand, the data amount processed can be reduced, and the identification efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of elevator passenger detection technology, and in particular to a detection area adjustment method, device, electronic device, and storage medium. Background Technology

[0002] With the development of intelligent elevators, a technology has emerged that uses sensors to sense the movement trends of passengers in the waiting hall and controls the opening or closing of elevator doors based on these trends. This is achieved by installing cameras on the door lintels of the elevator car, where there can be one or more sensors, and the installation angle can be fixed or adjustable.

[0003] like Figure 1 As shown, sensor 3 is installed on the lintel of car 1. Sensor 3 can collect images of the area inside car 1 and the area of ​​waiting hall 2. By analyzing the movement trends of passengers in the car and waiting hall through these images, the opening and closing times of the doors after the car reaches the target floor can be controlled.

[0004] However, currently for the waiting hall 2, the detection area 5 of sensor 3 (the area outside the elevator door 4 facing the waiting hall 2) is fixed when the elevator door 4 is fully open. Pedestrians passing by the elevator door are also in the detection area 5. Pedestrians passing by the elevator door do not have a need to take the elevator, resulting in a lot of interference information in the images collected through this fixed detection area, which can easily lead to misjudgments of the movement trend of passengers in the waiting hall. Summary of the Invention

[0005] This invention provides a detection area adjustment method, device, electronic device, and storage medium to solve the problem that the detection area of ​​the acquired images of the elevator lobby is fixed and there is a lot of image interference information, which leads to misjudgment of the movement trend of passengers in the elevator lobby.

[0006] In a first aspect, the present invention provides a detection area adjustment method, comprising:

[0007] When the elevator door is detected to be open, the target floor where the elevator car is currently stopped is determined;

[0008] Obtain the floor data of the target floor;

[0009] The target detection area for the target floor is determined based on the floor data.

[0010] The detection area of ​​the elevator's sensor in the waiting hall of the target floor is adjusted to the target detection area.

[0011] In a second aspect, the present invention provides a detection area adjustment device, comprising:

[0012] The floor determination module is used to determine the target floor where the elevator car is currently stopped when the elevator door is detected to be open.

[0013] The floor data acquisition module is used to acquire the floor data of the target floor;

[0014] The target detection area determination module is used to determine the target detection area of ​​the target floor based on the floor data.

[0015] The detection area adjustment module is used to adjust the detection area of ​​the elevator sensor in the waiting hall of the target floor to the target detection area.

[0016] Thirdly, the present invention provides an electronic device, the electronic device comprising:

[0017] At least one processor; and

[0018] A memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the detection area adjustment method described in the first aspect of the present invention.

[0020] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the detection area adjustment method described in the first aspect of the present invention.

[0021] In this embodiment of the invention, when the elevator door is detected to be open, the target floor where the elevator car is currently stopped is determined, the floor data of the target floor is acquired, and the target detection area of ​​the target floor is determined based on the floor data. The detection area of ​​the elevator sensor in the waiting hall of the target floor is adjusted to the target detection area, so that the elevator sensor can determine the target detection area of ​​the floor where the car is stopped based on the floor data of the floor where the car is stopped. This can be done by determining whether the target floor is a public or private floor, whether the current time is within a preset time period of the target floor, or by dynamically acquiring the number of passengers in the waiting hall of the target floor. This solves the problem that a fixed detection area for each floor leads to too much interference information in the collected images, resulting in misjudgment of passenger movement trends. The sensor can determine the target detection area according to different floor data when the car is stopped at different floors and then collect images, reducing invalid information in the images. On the one hand, this can improve the accuracy of recognizing passenger movement trends; on the other hand, it can reduce the amount of data processed and improve recognition efficiency.

[0022] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram of the sensor installation and detection area;

[0025] Figure 2 This is a flowchart of a detection area adjustment method provided in Embodiment 1 of the present invention;

[0026] Figure 3A This is a flowchart of a detection area adjustment method provided in Embodiment 2 of the present invention;

[0027] Figure 3B This is a schematic diagram of the detection area of ​​the sensor at different installation angles in an embodiment of the present invention;

[0028] Figure 4 This is a schematic diagram of the structure of a detection area adjustment device provided in Embodiment 3 of the present invention;

[0029] Figure 5 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0031] Example 1

[0032] Figure 2This is a flowchart of a detection area adjustment method provided in Embodiment 1 of the present invention. This embodiment is applicable to situations where the detection area of ​​the sensor is adjusted when the elevator car stops at different floors. The method can be executed by a detection area adjustment device, which can be implemented in hardware and / or software. This detection area adjustment device can be configured in an electronic device, such as in the elevator controller. Figure 2 As shown, the method for adjusting the detection area includes:

[0033] S201. When the elevator door is detected to be open, determine the target floor where the elevator car is currently stopped.

[0034] like Figure 1 As shown, in this embodiment, a sensor 3 is installed on the elevator car. The sensor can be a regular camera, such as a black and white camera or an RGB camera, or an active light sensor, such as a TOF (Time of Flight) depth sensor or a structured light sensor, which is a sensor that senses depth by emitting and receiving light. Of course, the sensor can also be a radar, etc. This embodiment does not limit the type of sensor.

[0035] In one example, the sensor in this embodiment can be an active light sensor 3, which can be installed on the car 1 so that the detection area of ​​the sensor 3 covers the area inside the car 1 and the area of ​​the waiting hall 2. Optionally, the sensor 3 can be installed on the lintel of the car door of the car 1, for example, in the middle position of the lintel of the car door, so that the detection area of ​​the sensor 3 covers the area inside the car 1 and the area of ​​the waiting hall 2.

[0036] In one example, the number of sensors 3 can be one, that is, the sensor 3 can be an active light sensor with a large field of view. Furthermore, when the number of sensors 3 is one, the angle of the sensor 3 can be adjusted or fixed, or the angle between the light emission axis of the sensor 3 and the vertical direction is variable, that is, the sensor 3 can adjust the angle so that the detection area 5 of the sensor 3 in the waiting hall 2 can be expanded or reduced.

[0037] like Figure 1As shown, in another example, there can be two sensors 3. One sensor 3 has its light emission axis facing the inside of the car 1 to capture images of the area inside the car 1, while the other sensor 3 has its light emission axis facing the waiting hall 2 to capture images of the area in the waiting hall 2. Optionally, the detection ranges of the two sensors 3 overlap to ensure that images of the entire area from the car 1 to the waiting hall 2 can be captured, while avoiding overexposure problems that occur after the elevator doors close when the sensors are active light sensors with a single vertical light emission axis and simultaneously capturing images of the entire area from the car 1 to the waiting hall 2. Exemplarily, the angle between the light emission axes of the two sensors 3 and the vertical direction can be adjusted to adjust the detection area of ​​the two sensors 3. Of course, the angle between the light emission axes of the two sensors 3 and the vertical direction can also remain fixed.

[0038] In practical applications, sensor 3 can collect depth images at a preset frame rate and send the depth images to the elevator controller. The elevator usually opens the elevator door when it reaches a certain target floor. At this time, sensor 3 collects depth images of the area inside the car 1 and the area of ​​the waiting hall 2. In order to determine the target detection area of ​​the floor where the car 1 stops, the floor where the car 1 stops can be determined first, such as determining the floor number of the floor where the car 1 stops.

[0039] S202. Obtain the floor data of the target floor.

[0040] Floor data can include at least one of the following: the floor number of the target floor, a preset time period, the total number of people waiting in the elevator lobby within a preset time period, and the number of people taking the elevator. The floor number can indicate whether the target floor is a public floor, such as the lobby floor or a dining floor, which are public floors with high elevator demand. The preset time period is the time period with high elevator usage on the target floor, such as working hours, off-hours, meal times, and rest times. The total number of people waiting in the elevator lobby and the number of people taking the elevator within the preset time period can be the total number of people waiting in the elevator lobby within the preset time period before the current time. The total number of people waiting in the elevator lobby can include the number of pedestrians passing through the elevator lobby and the number of people waiting for the elevator within the preset time period. The number of people taking the elevator is the number of people taking the elevator within the preset time period.

[0041] In this embodiment, the controller can respond to the elevator call request and control the car to stop. The controller can obtain the target floor where the car is currently stopped. In addition, the controller can store the preset time period for each floor in advance, and use sensors to count the number of passengers during the preset time period, as well as count the total number of people in the waiting hall and the number of passengers in the waiting hall within the preset time period.

[0042] S203. Determine the target detection area of ​​the target floor based on the floor data.

[0043] In one example, a target detection area can be pre-set for each floor, and the corresponding detection area can be found based on the floor number of the target floor as the target detection area for the target floor.

[0044] In another example, at least one preset time period can be set for each floor. Different time periods correspond to different detection areas. For example, larger detection areas can be set for work hours, off-get off work hours, and meal times, while smaller detection areas can be set for nighttime or non-work hours. The target preset time period to which the current time belongs can be determined, and the detection area corresponding to the target preset time period can be found as the target detection area.

[0045] In another example, the number of passengers taking the elevator within a preset time period before the current time can be counted, and the detection area corresponding to that number of passengers can be obtained as the detection area of ​​the target floor. Alternatively, the total number of people in the waiting hall of the target floor and the number of passengers taking the elevator within a preset time period can be counted, and the ratio of the number of passengers taking the elevator to the total number of people can be calculated to determine the detection area.

[0046] Of course, in practical applications, those skilled in the art can also use floor data such as the number of times the car stops, the average duration of the stops, and the number of outbound calls within a preset time period to determine the target detection area. This embodiment does not limit the method of determining the target detection area through floor data.

[0047] S204. Adjust the elevator sensor's detection area in the waiting hall of the target floor to the target detection area.

[0048] In an optional embodiment, the sensor's detection area can be adjusted to the target detection area by adjusting the sensor. For example, the sensor's installation position, current angle, and parameters such as the sensor's field of view and focal length can be obtained to calculate the mapping relationship between the target detection area and the sensor's angle, thereby obtaining the target angle of the sensor corresponding to different target detection areas, and thus adjusting the sensor's angle to the target angle.

[0049] In another optional embodiment, the installation position and current angle of the sensor can be obtained, as well as parameters such as the field of view and focal length of the sensor. Then, the boundary of the target detection area in the acquired image can be calculated using the imaging principle. This yields the boundary of different target detection areas in the image. The acquired image is then cropped according to the boundary to obtain the target image corresponding to the target detection area, thereby achieving the adjustment of the detection area.

[0050] In this embodiment of the invention, when the elevator door is detected to be open, the target floor where the elevator car is currently stopped is determined, the floor data of the target floor is acquired, and the target detection area of ​​the target floor is determined based on the floor data. The detection area of ​​the elevator sensor in the waiting hall of the target floor is adjusted to the target detection area, so that the elevator sensor can determine the target detection area of ​​the floor where the car is stopped based on the floor data of the floor where the car is stopped. This can be done by determining whether the target floor is a public or private floor, whether the current time is within a preset time period of the target floor, or by dynamically acquiring the number of passengers in the waiting hall of the target floor. This solves the problem that a fixed detection area for each floor leads to a lot of interference information in the collected images, resulting in misjudgment of passenger movement trends. The sensor can determine the target detection area according to the different floor data when the car is stopped at different floors and then collect images, reducing invalid information in the images. On the one hand, this can improve the accuracy of recognizing passenger movement trends; on the other hand, it can reduce the amount of data processed and improve recognition efficiency.

[0051] Example 2

[0052] Figure 3A This is a flowchart of a detection area adjustment method provided in Embodiment 2 of the present invention. This embodiment optimizes Embodiment 1 as described above. Figure 3A As shown, the method for adjusting the detection area includes:

[0053] S301. When the elevator door is detected to be open, determine the target floor where the elevator car is currently stopped.

[0054] In this embodiment, the main function of the sensor is to collect images of the elevator car and the waiting hall when the car stops at a floor, so as to detect the movement trend of passengers in the car and waiting people in the waiting hall through the images, and to determine whether to close the elevator door or extend the opening time of the elevator door based on the movement trend. That is, the elevator usually opens the elevator door when it reaches a certain target floor, so the car can be determined to stop when the car door opens, and the target floor where the car is currently stopped can be determined.

[0055] S302, Obtain the floor number of the target floor.

[0056] In an elevator system, each floor is assigned a floor number. The elevator controller can control the car to stop at each floor, and the controller can determine the floor number of the target floor where the car is currently stopped.

[0057] S303. Find the detection area that matches the floor number in the pre-set floor number-detection range lookup table, and use it as the target detection area for the target floor.

[0058] This embodiment can pre-set detection areas for each floor to form a floor number-detection range lookup table. For example, for public floors such as the first floor, people are more likely to take the elevator when they are in the elevator lobby. To more accurately predict the movement trends of more people using images collected by sensors, a larger detection area can be set for public floors. Conversely, for non-public floors, people are less likely to take the elevator in the elevator lobby. For instance, pedestrians passing through the lobby do not necessarily take the elevator, and they are usually on the side furthest from the elevator doors. Figure 1 As shown, in detection area 5, person A is in the elevator lobby 2 near the elevator door 4 and facing the elevator door, while person B passes by the elevator lobby 2, away from the elevator door 4 and not facing the elevator door. Therefore, person A is more likely to take the elevator, while person B is less likely to take the elevator. Thus, the detection area 5 of the non-public floor can be adjusted and reduced to exclude person B from the detection area 5.

[0059] Specifically, in this embodiment, after obtaining the floor number of the target floor where the elevator is currently stopped, the detection area corresponding to the floor number can be found in the floor number-detection range lookup table to obtain the target detection area of ​​the target floor. This allows the sensor's target detection area to be adjusted according to the floor, which can reduce interference information in the images of the waiting hall collected on each floor and improve the accuracy of the movement trend of people.

[0060] In an optional embodiment, at least one time period can be set according to the peak time of elevator use on each floor. At least one target time period matching the floor number of the target floor can be obtained from a pre-set floor number-time period table. After obtaining the current time, it is determined whether the current time falls within at least one target time period. If so, a detection area matching the target time period to which the current time belongs is searched in a pre-set time period-detection range lookup table and used as the target detection area for the target floor. For example, if the 10th floor of an office building is a dining floor, its peak elevator usage times are typically during peak dining hours, such as 8:00-9:00 AM, 12:00-1:00 PM, and 5:00-6:30 PM. These time periods can be set as pre-set time periods, and a corresponding first detection area can be set for each time period. A second detection area can be set for the remaining time periods, where the first detection area is larger than the second detection area. If the current time is during dining hours, such as 12:30 PM, most people have finished eating and need to take the elevator back to their offices, then 12:00 PM is considered a peak time period. 30 falls within the time period of 12:00-13:00. The first detection area corresponding to this time period is obtained as the target detection area. If the current time is 10:00, and there are no people or only a few people eating on the dining floor, the demand for elevator use on this dining floor is small. Therefore, the detection area of ​​this dining floor can be set as the second detection area. This realizes the adjustment of the detection area according to the peak time of elevator use on each floor. It can expand the detection area during peak use to detect the movement trend of people in a wider range, and shrink the detection area during off-peak use to reduce interference information in the collected images.

[0061] In another optional embodiment, the target detection area can be determined based on the number of passengers on the target floor within a preset time period. That is, the number of passengers on the target floor is obtained, and a detection area matching the number of passengers is found in a preset passenger-detection range lookup table, which is then used as the target detection area for the target floor. For example, different detection ranges corresponding to different numbers of passengers can be preset. For instance, if fewer than 8 people ride the elevator within 5 minutes, the detection range is the first detection area; if more than 8 but less than 15 people ride the elevator, the detection range is the second detection area; and if more than 15 people ride the elevator, the detection range is the third detection area. The areas of the first, second, and third detection areas increase sequentially. This allows for the statistical analysis of the number of passengers on the target floor within the previous 5 minutes. Based on this, the corresponding detection area can be selected. For example, if more than 15 people ride the elevator within 5 minutes, it indicates a high demand for elevator access on the target floor, with many people waiting. To detect more people, the detection area for that target floor is adjusted to the third detection area. This achieves dynamic adjustment of the detection area based on the number of passengers on the target floor within a preset time period, allowing for flexible adjustment of the sensor's detection area on the target floor.

[0062] In another optional embodiment, the detection area can be adjusted according to the proportion of people taking the elevator on the target floor. Specifically, the total number of people in the waiting hall and the number of people taking the elevator on the target floor within a preset time period can be obtained, and the ratio of the number of people taking the elevator to the total number of people can be calculated. The detection area that matches the ratio can be found in a preset ratio-detection range lookup table and used as the target detection area for the target floor. In essence, among the people in the elevator lobby, including those passing through and those needing to take the elevator, the total number of people in the lobby within a preset time period, as well as the number of people entering the elevator, can be counted. The ratio of the number of passengers to the total number of people is the elevator usage ratio. Different detection areas are set up for different usage ratios. Generally, people needing to take the elevator are usually closer to the elevator doors, while those passing through the lobby are usually farther away from the doors. If the usage ratio is high, it means that there are many people taking the elevator in the lobby and few passing through. The detection area can be expanded to predict the movement trend of more people in the lobby. Conversely, if the usage ratio is low, it means that there are few people taking the elevator in the lobby and many passing through. The detection area can be reduced to avoid predicting the movement trend of those passing through the lobby, thus reducing the influence of those passing through the lobby on the prediction results and improving the accuracy of the prediction.

[0063] Of course, in practical applications, technicians can also determine the target detection area based on the floor number, preset time period, number of passengers, and passenger ratio of the target floor. In one example, weights can be set for the floor number, preset time period, number of passengers, and passenger ratio to calculate the weighted sum of the floor number, preset time period, number of passengers, and passenger ratio. The detection area matching this weighted sum is then used as the target detection area for the target floor. This allows for a comprehensive determination of the target floor's detection area based on factors such as the nature of the target floor (public or non-public), whether the current time period is peak usage, the number of passengers, and the passenger ratio. The images collected by the sensor can better reflect the situation in the waiting hall of the target floor and more accurately predict the movement trend of people in the waiting hall, thereby controlling the opening or closing of the elevator doors based on this movement trend.

[0064] S304. Obtain the sensor's installation data and the sensor's field of view.

[0065] Sensor installation data can include the sensor's installation location. In one example, the installation data includes the sensor's coordinates relative to the car. The sensor's field of view can be the angle between the boundary of the area the sensor can detect after its current calibration and the line connecting the sensor's center. Figure 1 As shown, taking the middle position of the lintel of the car door as the installation position (origin of the coordinate system), the installation data of sensor 3 includes the height of sensor 3 from the bottom of car 1 or waiting hall 2, and the field of view is as follows: Figure 1 Angle a is shown.

[0066] S305. Determine the sensor adjustment parameters based on the installation data, field of view, and target detection area.

[0067] Specifically, the angle of the sensor corresponding to the target detection area can be calculated using imaging geometry principles; this angle is the adjustment parameter, such as... Figure 3B The diagram shows the angles of the sensor corresponding to different target detection areas. The angle b between the light emission axis of sensor 3 and the vertical direction can be calculated by the installation height of sensor 3, the field of view angle a, and the range of the target detection area, thus obtaining the angle b corresponding to different detection areas.

[0068] S306. Adjust the sensor according to the adjustment parameters to adjust the sensor's detection area in the elevator lobby of the target floor to the target detection area.

[0069] Specifically, adjusting the parameters can be the angle between the sensor's light emission axis and the vertical direction, which can control the drive mechanism to rotate the sensor and adjust the angle so that the sensor's detection area in the elevator lobby of the target floor is adjusted to the target detection area.

[0070] Of course, when the field of view, focal length, etc. of the sensor are adjustable, the sensor can also be adjusted by at least one of the following: field of view, focal length, and the angle between the light emission axis of sensor 3 and the vertical direction, so as to adjust the detection area of ​​the sensor in the waiting hall of the target floor to the target detection area.

[0071] This embodiment adjusts the sensor's parameters to move the sensor's detection area in the elevator lobby of the target floor to the target detection area. This requires less data computation, has a simple adjustment scheme, and is highly efficient.

[0072] In another alternative embodiment, after acquiring the sensor's installation data and field of view in S304, the target detection area of ​​the sensor in the waiting hall of the target floor can be determined by the following steps:

[0073] S307. Determine the target detection area of ​​the waiting hall on the target floor from the image acquired by the sensor.

[0074] Specifically, the boundary of the target detection area in the image acquired by the sensor can be determined based on the installation data, field of view, and target detection area. The image is then cropped according to the boundary to obtain the target image, which serves as the image of the target detection area of ​​the sensor in the waiting hall of the target floor.

[0075] When the sensor's position and field of view remain constant, the number of pixels in the image acquired by the sensor remains constant. That is, each pixel in the image corresponds to each position in the elevator lobby, meaning that each pixel in the image is mapped to each position in the elevator lobby. After determining the target detection area, the boundary pairs of the target detection area can be determined in the image acquired by the sensor. By cropping the acquired image according to the boundary, an image containing only the target detection area can be obtained, thereby adjusting the detection area. The target detection area is cropped by image cropping, eliminating the need to adjust the sensor for each floor. Furthermore, the accuracy of the target detection area is high, and the amount of image data transmitted to the controller is small, so the controller does not need to crop further.

[0076] After adjusting the detection area to obtain the image in this embodiment, the image can be input into the motion trend analysis model to identify the movement direction, speed, and position changes of each object (person, wheelchair, robot) in the image, in order to determine whether the objects in the waiting hall have a tendency to take the elevator. For example, when a person is identified to approach the elevator door at a relatively fast speed, it is determined that the person has a tendency to take the elevator, and the door opening time can be extended. Or, if an object including a robot is identified, the door opening time can be extended. Or, if a child is identified to approach the elevator door, the door opening time can be extended. Of course, if the elevator door is opened and the people in the waiting hall are identified to be stationary, it means that the direction of the people in the waiting hall to take the elevator is opposite to the current direction of the elevator car, and there is no tendency to take the elevator. The elevator door can be closed in advance to improve the operating efficiency of the elevator.

[0077] In this embodiment, when the elevator door is detected to be open, the target floor where the elevator car is currently stopped is determined. At least one of the following is obtained: the floor number of the target floor, a preset time period set for the target floor, the number of passengers within the preset time period, the total number of people in the waiting hall within the preset time period, and the number of passengers to determine the target detection area for the target floor. The sensor is adjusted to align its detection area in the waiting hall of the target floor with the target detection area. This comprehensive approach, considering factors such as the nature of the target floor (public or non-public), whether the current time period is peak usage, the number of passengers, and the passenger ratio, determines the detection area for the target floor. This reduces invalid information in the image, improving the accuracy of passenger movement trend recognition and reducing the amount of data processed, thus increasing recognition efficiency.

[0078] Example 3

[0079] Figure 4 This is a schematic diagram of a detection area adjustment device provided in Embodiment 3 of the present invention. Figure 4 As shown, the detection area adjustment device includes:

[0080] The floor determination module 401 is used to determine the target floor where the elevator car is currently stopped when the elevator door is detected to be open.

[0081] The floor data acquisition module 402 is used to acquire the floor data of the target floor;

[0082] The target detection area determination module 403 is used to determine the target detection area of ​​the target floor based on the floor data.

[0083] The detection area adjustment module 404 is used to adjust the detection area of ​​the elevator sensor in the waiting hall of the target floor to the target detection area.

[0084] Optionally, the floor data acquisition module 402 includes:

[0085] A floor number acquisition unit is used to acquire the floor number of the target floor;

[0086] The target detection region determination module 403 includes:

[0087] The first target detection area matching unit is used to find the detection area that matches the floor number in a pre-set floor number-detection range lookup table, so as to use it as the target detection area of ​​the target floor.

[0088] Optionally, the floor data acquisition module 402 includes:

[0089] The target time period acquisition unit is used to acquire at least one target time period that matches the floor number of the target floor from a pre-set floor number-time period.

[0090] The target detection region determination module 403 includes:

[0091] The time period determination unit is used to determine whether the current time is within at least one of the target time periods;

[0092] The second target detection area matching unit is used to find a detection area that matches the target time period to which the current time belongs in a preset time period-detection range lookup table, so as to serve as the target detection area of ​​the target floor.

[0093] Optionally, the floor data acquisition module 402 includes:

[0094] The elevator passenger number acquisition unit is used to acquire the number of passengers on the target floor, wherein the number of passengers is the number of passengers within a preset time period before the current time, which is pre-statistically counted.

[0095] The target detection region determination module 403 includes:

[0096] The third target detection area matching unit is used to find a detection area that matches the number of passengers in a preset elevator passenger-detection range lookup table, so as to serve as the target detection area for the target floor.

[0097] Optionally, the floor data acquisition module 402 includes:

[0098] The elevator waiting hall total number of people and elevator passenger number acquisition unit is used to acquire the total number of people in the elevator waiting hall of the target floor and the number of people entering the elevator. The total number of people in the elevator waiting hall includes the number of people in the elevator waiting hall who are passengers and the number of people who pass by the elevator who are not passengers.

[0099] The target detection region determination module 403 includes:

[0100] An elevator ratio calculation unit is used to calculate the ratio of the number of elevator passengers to the total number of passengers;

[0101] The fourth target detection area matching unit is used to find a detection area that matches the ratio in a preset ratio-detection range lookup table, so as to serve as the target detection area of ​​the target floor.

[0102] Optionally, the detection area adjustment module 404 includes:

[0103] A sensor data acquisition unit is used to acquire the installation data of the sensor and the field of view of the sensor;

[0104] The parameter adjustment determination unit is used to determine the adjustment parameters of the sensor based on the installation data, the field of view, and the target detection area.

[0105] The detection area adjustment unit is used to adjust the sensor according to the adjustment parameters so as to adjust the detection area of ​​the sensor in the waiting hall of the target floor to the target detection area;

[0106] The adjustment parameters include at least one of the sensor's angle, focal length, and viewing angle.

[0107] Optionally, the detection area adjustment module 404 includes:

[0108] A sensor data acquisition unit is used to acquire the installation data of the sensor and the field of view of the sensor;

[0109] An image boundary determination unit is used to determine the boundary of the target detection area in the image acquired by the sensor based on the installation data, the field of view, and the target detection area;

[0110] An image cropping unit is used to crop the image according to the boundary to obtain a target image, which is used as the image of the target detection area of ​​the sensor in the waiting hall of the target floor.

[0111] The detection area adjustment device provided in this embodiment of the invention can execute the detection area adjustment method provided in Embodiment 1 and Embodiment 2 of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0112] Example 4

[0113] Figure 5 A schematic diagram of an electronic device 50 that can be used to implement embodiments of the present invention is shown. The electronic device 50 is intended to represent various forms of digital computers, such as desktop computers, workbenches, servers, blade servers, mainframe computers, etc. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0114] like Figure 5 As shown, the electronic device 50 includes at least one processor 51 and a memory, such as a read-only memory (ROM) 52 and a random access memory (RAM) 53, communicatively connected to the at least one processor 51. The memory stores computer programs executable by the at least one processor. The processor 51 can perform various appropriate actions and processes based on the computer program stored in the ROM 52 or loaded into the RAM 53 from storage unit 58. The RAM 53 can also store various programs and data required for the operation of the electronic device 50. The processor 51, ROM 52, and RAM 53 are interconnected via a bus 54. An input / output (I / O) interface 55 is also connected to the bus 54.

[0115] Multiple components in electronic device 50 are connected to I / O interface 55, including: input unit 56, such as keyboard, mouse, sensor, etc.; output unit 57, such as various types of display, speaker, etc.; storage unit 58, such as disk, optical disk, etc.; and communication unit 59, such as network card, modem, wireless transceiver, etc. Communication unit 59 allows electronic device 50 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0116] Processor 51 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 51 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 51 performs the various methods and processes described above, such as the detection region adjustment method.

[0117] In some embodiments, the detection area adjustment method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 58. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 50 via ROM 52 and / or communication unit 59. When the computer program is loaded into RAM 53 and executed by processor 51, one or more steps of the detection area adjustment method described above may be performed. Alternatively, in other embodiments, processor 51 may be configured to perform the detection area adjustment method by any other suitable means (e.g., by means of firmware).

[0118] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0119] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs 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 processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0120] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0121] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0122] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0123] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0124] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0125] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method of detecting an area adjustment, characterized by, The method comprises: detecting that a door of an elevator is in an open state; determining a target floor where a car of the elevator is currently stopped; obtaining floor data of the target floor; determining a target detection area of the target floor based on the floor data; adjusting a detection area of a sensor of the elevator in a hall of the target floor to the target detection area; the obtaining of the floor data of the target floor comprises: obtaining a total number of people in the hall of the target floor and a number of boarding people entering the elevator, the total number of people in the hall of the target floor including the number of boarding people and a number of non-boarding people passing by the elevator; the determining of the target detection area of the target floor based on the floor data comprises: calculating a ratio of the number of boarding people to the total number of people; 2. The detection region adjustment method of claim 1, wherein, finding a detection area matching the ratio in a preset ratio-detection range correspondence table as the target detection area of the target floor. the obtaining of the floor data of the target floor comprises: obtaining a floor number of the target floor; the determining of the target detection area of the target floor based on the floor data comprises:

3. The detection region adjustment method of claim 1, wherein, finding a detection area matching the floor number in a preset floor number-detection range correspondence table as the target detection area of the target floor. the obtaining of the floor data of the target floor comprises: obtaining at least one target time period matching the floor number of the target floor in a preset floor number-time period; the determining of the target detection area of the target floor based on the floor data comprises: judging whether a current time is within the at least one target time period; 4. The detection region adjustment method of claim 1, wherein, if yes, finding a detection area matching a target time period to which the current time belongs in a preset time period-detection range correspondence table as the target detection area of the target floor. the obtaining of the floor data of the target floor comprises: obtaining a number of boarding people of the target floor, the number of boarding people being a number of boarding people in a preset time period before the current time; the determining of the target detection area of the target floor based on the floor data comprises:

5. The detection region adjustment method according to any one of claims 1 to 4, characterized by, finding a detection area matching the number of boarding people in a preset number of boarding people-detection range correspondence table as the target detection area of the target floor. the adjusting of the detection area of the sensor of the elevator in the hall of the target floor to the target detection area comprises: obtaining installation data of the sensor and a field of view angle of the sensor; determining an adjustment parameter of the sensor according to the installation data, the field of view angle and the target detection area; adjusting the sensor according to the adjustment parameter to adjust the detection area of the sensor in the hall of the target floor to the target detection area; 6. The detection region adjustment method according to any one of claims 1 to 4, characterized by, wherein the adjustment parameter comprises at least one of an angle, a focal length and a viewing angle of the sensor. the adjusting of the detection area of the sensor of the elevator in the hall of the target floor to the target detection area comprises: obtaining installation data of the sensor and a field of view angle of the sensor; determining a boundary of the target detection area in an image captured by the sensor according to the installation data, the field of view angle and the target detection area; cropping the image according to the boundary to obtain a target image as an image of the target detection area of the waiting hall of the target floor by the sensor.

7. An area detection adjusting apparatus characterized by comprising: comprise: a stop floor determination module configured to determine a target floor where a car of an elevator is currently stopped when it is detected that a door of the elevator is in an open state; a floor data acquisition module configured to acquire floor data of the target floor; a target detection area determination module configured to determine a target detection area of the target floor based on the floor data; a detection area adjustment module configured to adjust a detection area of a sensor of the elevator in a waiting hall of the target floor to the target detection area; the floor data acquisition module comprises: a waiting hall total number of people and boarding number of people acquisition unit configured to acquire a waiting hall total number of people of the target floor and a boarding number of people entering the elevator, the waiting hall total number of people comprising a boarding number of people in the waiting hall and a non-boarding number of people passing by the elevator; the target detection area determination module comprises: a boarding ratio calculation unit configured to calculate a ratio of the boarding number of people to the total number of people; a fourth target detection area matching unit configured to find a detection area matching the ratio in a preset ratio-detection range correspondence table as the target detection area of the target floor.

8. An electronic device, comprising: The electronic device comprises: at least one processor; and a memory connected in communication with the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the detection area adjustment method of any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for causing the processor to execute when executed to implement the detection area adjustment method of any one of claims 1-6. The computer readable storage medium stores computer instructions for causing the processor to execute when executed to implement the detection area adjustment method of any one of claims 1-6.

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