Intelligent three-dimensional parking equipment based on cloud service

Abstract

The intelligent three-dimensional parking equipment based on the cloud service comprises a garage, a photographing unit is fixedly installed on the left side of the interior of the garage, a rotating table is connected to the right side of the interior of the garage through a bearing, a boss is fixedly installed on the outer side of the rotating table, and the rotating table is flush with the boss; the intelligent three-dimensional parking equipment uses an intelligent parking system, the intelligent parking system comprises an information uploading module, the information uploading module comprises a number input module, and the number input module comprises a vehicle condition evaluation module and an expected wear calculation module. The vehicle condition evaluation module and the expected wear calculation module are in communication connection with the number input module, the number input module is used for inputting the number of the kart, and the vehicle condition evaluation module is used for evaluating the vehicle body wear condition of the kart.

Description

Technical Field

[0001] This invention relates to the field of parking equipment technology, specifically to an intelligent multi-level parking system based on cloud services. Background Technology

[0002] Go-karts in amusement facilities will wear out over time. However, existing go-karts are only repaired after problems occur, and the timing of damage is random, which may affect normal operation and ruin the visitor experience.

[0003] Existing parking systems suffer from poor practicality; they also lack the ability to determine specific repair dates based on vehicle wear and tear, hindering early maintenance scheduling and preventing damage during peak usage periods that could disrupt normal operations. Therefore, designing a cloud-based intelligent automated parking system that is highly practical and features automatic repair date reminders is essential. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent multi-level parking system based on cloud services to solve the problems mentioned in the background art.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a cloud-based intelligent three-dimensional parking equipment, including a garage, wherein a camera unit is fixedly installed on the left side of the garage, a rotating platform is connected to the right side of the garage by a bearing, and a boss is fixedly installed on the outside of the rotating platform, and the rotating platform and the boss are kept flush.

[0006] According to the above technical solution, the intelligent three-dimensional parking equipment uses an intelligent parking system, which includes an information uploading module, a number input module, a vehicle condition assessment module, and an expected wear calculation module. The vehicle condition assessment module and the expected wear calculation module are communicatively connected to the number input module.

[0007] The number input module is used to input the number of the go-kart, the vehicle condition assessment module is used to assess the wear and tear of the go-kart's body, and the expected wear calculation module is used to calculate the wear and tear of the go-kart's body over a future period of time.

[0008] According to the above technical solution, the vehicle condition assessment module includes an image comparison module, which is electrically connected to an image grayscale module, and the image grayscale module is electrically connected to a photography unit and a rotation unit.

[0009] The image comparison module is used to compare and analyze images, the image grayscale module is used to process images into grayscale to provide a data environment for image comparison, the photo-taking unit is used to record and upload vehicle conditions, and the rotation unit is used to rotate the go-kart to make the recorded data more comprehensive.

[0010] According to the above technical solution, the expected wear calculation module includes a running frequency prediction module, which includes an off-season running information prediction module and a peak season running information prediction module. Both the off-season running information prediction module and the peak season running information prediction module are communicatively connected to a data statistics module.

[0011] The number of runs prediction module is used to predict the number of runs of the go-karts afterward. The off-season run information prediction module is used to predict the number of runs of the go-karts during the off-season. The peak season run information prediction module is used to predict the number of runs of the go-karts during the peak season. The data statistics module is used to provide data support for predicting the number of runs in the off-season and peak season based on the previous number of runs.

[0012] According to the above technical solution, the operation steps of the intelligent parking system are as follows:

[0013] S1. First, enter the number of the go-kart that needs to be parked using the code on the go-kart and upload it to the cloud;

[0014] S2. After the go-kart is parked, the camera and rotating units are used to fully record the condition of the go-kart and upload the information.

[0015] S3. Then, the image is converted to grayscale using the image grayscale module, and then the image is compared and analyzed.

[0016] S4. Based on the comparison results, use the vehicle condition assessment module to assess the wear and tear of the vehicle.

[0017] S5. Based on past operational data, predict the number of operations during peak and off-peak seasons in the future;

[0018] S6. Using the expected wear calculation module, calculate the expected wear based on the predicted number of runs during peak and off-peak seasons and the wear situation on the day.

[0019] S7. Calculate the maintenance dates required for the vehicle based on expected wear and tear and the current condition of the vehicle.

[0020] S8. When the date is close to the maintenance date, the date will be uploaded and the maintenance personnel will be notified to perform vehicle maintenance in a timely manner.

[0021] According to the above technical solution, step S3 further includes:

[0022] Step S31: First, upload the image and convert the captured image to the same resolution as the standard image;

[0023] Step S32: Convert all images to grayscale, then compare pixels at the same location in the images, and obtain the difference in grayscale values ​​of the pixels by comparison;

[0024] Step S33: The gray value is a value between 0 and 255. When the gray value difference of a small range of image pixels is greater than 50, then paint needs to be touched up in that range of images. When the gray value difference of a large range of image pixels is greater than 100, then parts are missing in that range of images. At the same time, the number of differences in the image range is counted to obtain the number of paint to be touched up and the number of missing parts.

[0025] According to the above technical solution, in step S4, the wear level of the vehicle is estimated using the image, and the wear level ω is:

[0026]

[0027] In the formula, k is the wear correction coefficient, and a n b is the grayscale value of the standard image. n The image grayscale value of the vehicle under repair is given by n, which is the number of pixels. The wear at a single location can be seen by the grayscale value ratio of a single pixel. The overall wear of the vehicle can be obtained by the sum of the grayscale value ratios of the pixels and the correction coefficient.

[0028] According to the above technical solution, in step S5, the fluctuation coefficient of the number of operations is calculated by using the past number of operations during peak and off-peak seasons, and the future number of operations during peak and off-peak seasons is obtained by using the average number of operations and fluctuation coefficients during peak and off-peak seasons.

[0029] According to the above technical solution, in step S6, the expected wear... for:

[0030]

[0031] In the formula, ω represents the previous losses, t represents the number of times the vehicle has been operated, and t 淡 For the number of runs during the off-season, t 旺 Let n be the number of trips during peak season, n be the number of trips during off-season, and m be the number of trips during peak season. The average wear per run is used to derive the expected wear from the wear per run and the number of future runs.

[0032] According to the above technical solution, in step S7, since the off-season and peak season alternate throughout the year, n ≥ m, and the difference between n and m is at most 1. Based on the service life, the replacement time can be calculated, and the replacement time m and n can be obtained using the following formula:

[0033]

[0034]

[0035]

[0036] In the formula, δ represents the service life, ω represents the previous wear and tear, and t represents the current number of operations. 淡 The number of runs during the off-season is a fixed value, t 旺 The number of runs during peak season is also a fixed value. By subtracting the current lifespan from the current lifespan, the remaining lifespan can be obtained, and the values ​​of n and m can be derived, thus determining the specific date when the go-kart needs to be replaced.

[0037] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: The present invention utilizes the rotation of the rotating platform to enable the photography unit to record the condition of the go-kart from all angles. Then, through the comparison module, the photos of the go-kart's condition are compared with those of a standard go-kart to analyze the parts and quantities that need repair. At the same time, the wear and tear of the vehicle is assessed by the vehicle condition assessment module, and the number of past runs is statistically analyzed by the data statistics module to predict the number of runs during peak and off-peak seasons. Subsequently, the expected wear and tear calculation module can calculate the expected wear and tear, thereby estimating the specific repair date based on its service life. Attached Figure Description

[0038] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0039] Figure 1 This is a schematic diagram of the overall front structure of the present invention;

[0040] Figure 2 This is a schematic diagram of the system modules of the present invention;

[0041] In the diagram: 1. Garage; 2. Camera unit; 3. Rotating platform; 4. Boss. Detailed Implementation

[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0043] Please see Figure 1-2 The present invention provides a technical solution: a cloud-based intelligent three-dimensional parking equipment, including a garage 1, characterized in that: a camera unit 2 is fixedly installed on the left side inside the garage 1, a rotating platform 3 is connected to the right side inside the garage 1 by a bearing, a boss 4 is fixedly installed on the outside of the rotating platform 3, and the rotating platform 3 and the boss 4 are kept flush; when a go-kart is parked in the garage, the rotating platform 3 rotates, and at the same time the camera unit 2 takes a picture, records the condition of the go-kart and uploads it to the cloud.

[0044] The intelligent multi-level parking equipment uses an intelligent parking system, which includes an information uploading module, a number input module, a vehicle condition assessment module, and an expected wear calculation module. The vehicle condition assessment module and the expected wear calculation module are connected to the number input module.

[0045] The number input module is used to input the number of the go-kart, the vehicle condition assessment module is used to assess the wear and tear of the go-kart's body, and the expected wear calculation module is used to calculate the wear and tear of the go-kart's body over a future period of time.

[0046] The vehicle condition assessment module includes an image comparison module, which is electrically connected to an image grayscale conversion module. The image grayscale conversion module is electrically connected to a photography unit and a rotation unit.

[0047] The image comparison module is used to compare and analyze images, the image grayscale module is used to process images into grayscale to provide a data environment for image comparison, the photo-taking unit is used to record and upload the vehicle's condition, and the rotation unit is used to rotate the go-kart to make the recorded data more comprehensive.

[0048] The expected wear calculation module includes a running frequency prediction module, which includes a low-season running information prediction module and a high-season running information prediction module. Both the low-season running information prediction module and the high-season running information prediction module are communicatively connected to a data statistics module.

[0049] The number of runs prediction module is used to predict the number of runs of go-karts in the future. The off-season run information prediction module is used to predict the number of runs of go-karts in the off-season. The peak season run information prediction module is used to predict the number of runs of go-karts in the peak season. The data statistics module is used to provide data support for predicting the number of runs in the off-season and peak season based on the previous number of runs.

[0050] The operation steps of this intelligent parking system are as follows:

[0051] S1. First, enter the number of the go-kart that needs to be parked using the code on the go-kart and upload it to the cloud;

[0052] S2. After the go-kart is parked, the camera and rotating units are used to fully record the condition of the go-kart and upload the information.

[0053] S3. Then, the image is converted to grayscale using the image grayscale module, and then the image is compared and analyzed.

[0054] S4. Based on the comparison results, use the vehicle condition assessment module to assess the wear and tear of the vehicle.

[0055] S5. Based on past operational data, predict the number of operations during peak and off-peak seasons in the future;

[0056] S6. Using the expected wear calculation module, calculate the expected wear based on the predicted number of runs during peak and off-peak seasons and the wear situation on the day.

[0057] S7. Calculate the maintenance dates required for the vehicle based on expected wear and tear and the current condition of the vehicle.

[0058] S8. When the date is close to the maintenance date, the date will be uploaded and the maintenance personnel will be notified to perform vehicle maintenance in a timely manner.

[0059] Step S3 further includes:

[0060] Step S31: First, upload the image and convert the captured image to the same resolution as the standard image;

[0061] Step S32: Convert all images to grayscale, then compare pixels at the same location in the images, and obtain the difference in grayscale values ​​of the pixels by comparison;

[0062] Step S33: The gray value is a value between 0 and 255. When the gray value difference of a small range of image pixels is greater than 50, then paint needs to be touched up in that range of images. When the gray value difference of a large range of image pixels is greater than 100, then parts are missing in that range of images. At the same time, the number of differences in the image range is counted to obtain the number of paint to be touched up and the number of missing parts.

[0063] In step S4, the wear level of the vehicle was estimated using the image, and the wear level ω was:

[0064]

[0065] In the formula, k is the wear correction coefficient, and a n b is the grayscale value of the standard image. n The image grayscale value of the vehicle under repair is given by n, which is the number of pixels. The wear at a single location can be seen by the grayscale value ratio of a single pixel. The overall wear of the vehicle can be obtained by the sum of the grayscale value ratios of the pixels and the correction coefficient.

[0066] In step S5, the fluctuation coefficient of the number of operations is calculated by using the past number of operations during peak and off-peak seasons. The future number of operations during peak and off-peak seasons is obtained by using the average number of operations and fluctuation coefficients during peak and off-peak seasons.

[0067] In step S6, the expected wear for:

[0068]

[0069] In the formula, ω represents the previous losses, t represents the number of times the vehicle has been operated, and t 淡 For the number of runs during the off-season, t 旺 Let n be the number of trips during peak season, n be the number of trips during off-season, and m be the number of trips during peak season. The average wear per run is used to derive the expected wear from the wear per run and the number of future runs.

[0070] In step S7, since the off-season and peak season alternate throughout the year, n ≥ m, and the difference between n and m is at most 1. Based on the service life, the replacement time can be calculated. The replacement time m and n can be obtained using the following formula:

[0071]

[0072]

[0073]

[0074] In the formula, δ represents the service life, ω represents the previous wear and tear, and t represents the current number of operations.淡 The number of runs during the off-season is a fixed value, t 旺 The number of runs during peak season is also a fixed value. By subtracting the current lifespan from the current lifespan, the remaining lifespan can be obtained, and the values ​​of n and m can be derived, thus determining the specific date when the go-kart needs to be replaced.

[0075] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0076] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A cloud-based intelligent multi-level parking system, comprising a parking garage (1), characterized in that: A camera unit (2) is fixedly installed on the left side of the interior of the garage (1), and a rotating platform (3) is connected to the right side of the interior of the garage (1) by a bearing. A boss (4) is fixedly installed on the outside of the rotating platform (3), and the rotating platform (3) and the boss (4) are flush. The intelligent three-dimensional parking equipment uses an intelligent parking system, which includes an information uploading module, a number input module, a vehicle condition assessment module, and an expected wear calculation module. The vehicle condition assessment module and the expected wear calculation module are communicatively connected to the number input module. The vehicle condition assessment module includes an image comparison module, which is electrically connected to an image grayscale module, and the image grayscale module is electrically connected to a photography unit and a rotation unit. The expected wear calculation module includes a running frequency prediction module, which includes an off-season running information prediction module and a peak season running information prediction module. Both the off-season running information prediction module and the peak season running information prediction module are communicatively connected to a data statistics module. The operation steps of the intelligent parking system are as follows: S1. First, enter the number of the go-kart that needs to be parked using the code on the go-kart and upload it to the cloud; S2. After the go-kart is parked, the camera and rotating units are used to fully record the condition of the go-kart and upload the information. S3. Subsequently, the image grayscale module is used to process the image into grayscale, and then the image comparison analysis is performed. First, the image is uploaded, and the image obtained by taking the picture is converted to the same resolution as the standard comparison image. The images are all grayscaled, and then the pixels at the same position in the image are compared. By comparison, the difference in grayscale value of the pixels is obtained. The grayscale value is a value between 0 and 255. When the grayscale difference of a small range of image pixels is greater than 50, it means that paint needs to be touched up in that area of ​​the image. When the grayscale difference of a large range of image pixels is greater than 100, it means that a part is missing in that area of ​​the image. At the same time, the number of differences in the image is counted to obtain the number of paint to be touched up and the number of missing parts. S4. Based on the comparison results, the vehicle condition assessment module is used to evaluate the wear and tear of the vehicle. The degree of wear is estimated using images, and the wear degree ω is: In the formula, k is the wear correction coefficient, and a n b is the grayscale value of the standard image. n The image grayscale value of the vehicle being repaired is given by n, which is the number of pixels. The wear at a single location can be seen by the grayscale value ratio of a single pixel. The overall wear of the vehicle can be obtained by the sum of the grayscale value ratios of the pixels and the correction coefficient. S5. Based on past operational data, predict the number of operations during the peak and off-peak seasons in the future. Calculate the fluctuation coefficient of the number of operations using the past number of operations during the peak and off-peak seasons. Calculate the future number of operations during the peak and off-peak seasons using the average number of operations and the fluctuation coefficient during the peak and off-peak seasons. S6. Using the expected wear calculation module, calculate the expected wear based on the predicted number of runs during peak and off-peak seasons and the wear situation on the day. for: In the formula, ω represents the previous losses, t represents the number of times the vehicle has been operated, and t 淡 For the number of runs during the off-season, t 旺 Let n be the number of trips during peak season, n be the number of trips during off-season, and m be the number of trips during peak season. The average wear per run is used to derive the expected wear by combining the wear from a single run with the number of future runs. S7. Calculate the maintenance dates required for the vehicle based on expected wear and tear and the current condition of the vehicle. S8. When the date is close to the maintenance date, the date will be uploaded and the maintenance personnel will be notified to perform vehicle maintenance in a timely manner; The number input module is used to input the number of the go-kart, the vehicle condition assessment module is used to assess the wear and tear of the go-kart's body, and the expected wear calculation module is used to calculate the wear and tear of the go-kart's body over a future period of time. The image comparison module is used to compare and analyze images, the image grayscale module is used to process images into grayscale to provide a data environment for image comparison, the photo-taking unit is used to record and upload vehicle conditions, and the rotation unit is used to rotate the go-kart to make the recorded data more comprehensive. The number of runs prediction module is used to predict the number of runs of the go-karts afterward. The off-season run information prediction module is used to predict the number of runs of the go-karts during the off-season. The peak season run information prediction module is used to predict the number of runs of the go-karts during the peak season. The data statistics module is used to provide data support for predicting the number of runs in the off-season and peak season based on the previous number of runs.

2. The intelligent automated parking system based on cloud services according to claim 1, characterized in that: In step S7, since the off-season and peak season alternate throughout the year, n ≥ m, and the difference between n and m is at most 1. Based on the service life, the replacement time can be calculated. The replacement time m and n can be obtained using the following formula: In the formula, δ represents the service life, ω represents the previous wear and tear, and t represents the current number of operations. 淡 The number of trips during the off-season is a fixed value, t 旺 The number of runs during peak season is also a fixed value. By subtracting the used lifespan from the current lifespan, the remaining lifespan can be obtained, and the values ​​of n and m can be derived, thus determining the specific date when the go-kart needs to be replaced.

Images