Inspection robot based on AI cloud service

Abstract

The invention provides an inspection robot based on AI cloud service, which comprises an NFC module, a camera module, a Raspberry Pi, a voice module and a cloud service platform with a plurality of AI models, each AI model corresponds to an inspection task, all inspection tasks are different, the NFC module is connected with the Raspberry Pi through an SPI interface, the camera module is connected with the Raspberry Pi through a USB interface, and the voice module is connected with the cloud service platform. The voice module is connected with the Raspberry Pi, and the Raspberry Pi is connected with the cloud service platform through an API interface. Therefore, by calling the AI models corresponding to the different inspection tasks, flexible switching among the different inspection tasks can be achieved, a local deployment algorithm is not needed, time and labor cost is reduced, and maintenance is convenient.

Description

Technical Field

[0001] The present invention relates to the technical field of inspection robots, and in particular to an inspection robot based on AI cloud services. Background Art

[0002] In modern industrial production, inspection robots have become a crucial tool for improving efficiency and reducing human error. Currently, most inspection robots on the market rely on local computing resources to complete tasks, such as environmental monitoring, 5S scoring, and equipment inspections, using embedded hardware and pre-set algorithms. However, these robots have the following shortcomings:

[0003] Inflexible task switching: Local processing robots are usually optimized for a single task and cannot quickly adapt to different types of visual inspection tasks.

[0004] Difficulty in maintenance: Local algorithm updates and model training require high costs and time, resulting in poor adaptability of the robot in completing tasks. Summary of the Invention

[0005] In order to solve one of the above technical problems, the present invention proposes the following technical solution.

[0006] An embodiment of the first aspect of the present invention proposes an inspection robot based on AI cloud service, comprising an NFC module, a camera module, a Raspberry Pi, a voice module and a cloud service platform with multiple AI models, wherein each AI model corresponds to an inspection task, and all inspection tasks are different. The NFC module is connected to the Raspberry Pi through an SPI interface, the camera module is connected to the Raspberry Pi through a USB interface, the voice module is connected to the Raspberry Pi, and the Raspberry Pi is connected to the cloud service platform through an API interface.

[0007] In addition, the inspection robot based on AI cloud service according to the above embodiment of the present invention may also have the following additional technical features.

[0008] According to some embodiments of the present invention, the inspection robot based on AI cloud service also includes a wireless communication module connected to the Raspberry Pi.

[0009] According to some embodiments of the present invention, the inspection robot based on AI cloud service also includes a database, which is connected to the cloud service platform and is used to store the image analysis data output by the AI model.

[0010] According to some embodiments of the present invention, the inspection robot based on AI cloud services also includes a Web inspection system, which is connected to the database and is used for users to view the image analysis data.

[0011] According to some embodiments of the present invention, the camera module is installed directly in front of the inspection robot, the NFC module is installed directly below the inspection robot, the Raspberry Pi is installed directly above the inspection robot, and there is at least one voice module, which is installed on both sides of the inspection robot.

[0012] The technical solution of the embodiment of the present invention can achieve flexible switching between different inspection tasks by calling the AI models corresponding to different inspection tasks, without the need for local deployment of algorithms, reducing time and labor costs, and facilitating maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 This is a structural block diagram of an AI cloud service-based inspection robot according to an embodiment of the present invention.

[0014] Figure 2 This is a schematic diagram of the working principle of an AI cloud service-based inspection robot as an example of the present invention. DETAILED DESCRIPTION

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0016] Figure 1 This is a structural block diagram of an AI cloud service-based inspection robot according to an embodiment of the present invention.

[0017] like Figure 1 As shown, the inspection robot based on AI cloud service includes an NFC module 1, a camera module 2, a Raspberry Pi 3, a voice module 4 and a cloud service platform 5 with multiple AI models, wherein each AI model corresponds to an inspection task, and all inspection tasks are different. The NFC module 1 is connected to the Raspberry Pi 3 through the SPI interface, the camera module 2 is connected to the Raspberry Pi 3 through the USB interface, the voice module 4 is connected to the Raspberry Pi 3, and the Raspberry Pi 3 is connected to the cloud service platform 5 through the API interface.

[0018] NFC module 1: The inspection robot starts taking pictures through NFC sensing.

[0019] Camera module 2: used to capture factory content and upload it to the Raspberry Pi 3.

[0020] Raspberry Pi 3: Serves as the central processing unit of all functional modules of the robot, coordinating data transmission and task execution between modules.

[0021] Voice module 4: emits a prompt sound at the start and end of shooting.

[0022] The Raspberry Pi may be a Raspberry Pi 4B, and the NFC module may be an RC522 module.

[0023] Specifically, the Raspberry Pi 3 is the master control device, which first starts the NFC module 1, camera module 2, and voice module 4. When the NFC module 1 senses the NFC sticker marked with the inspection task and recognizes that the NFC sticker content includes shooting, it activates the shooting function of the camera module 2 and simultaneously starts the voice broadcast of the voice module 4. The captured photos are uploaded to the AI model corresponding to the corresponding inspection task in the cloud service platform 5 through the Raspberry Pi 3 by calling the API. The AI model performs image analysis, and the user can view the analysis results in any way, thus completing the inspection of the corresponding task. Afterwards, the inspection robot continues to track and drive. When it recognizes other inspection tasks, it takes pictures and calls the corresponding AI model for image analysis.

[0024] By invoking AI models corresponding to different inspection tasks (such as environmental inspection, equipment inspection, safety hazard identification, 5S scoring, and other inspection tasks), multifunctional inspection is achieved. Flexible switching between tasks is possible, providing multifunctional inspection capabilities.

[0025] The present invention combines NFC with inspection tasks, and through NFC sticker content instructions (such as "shoot"), it realizes flexible modular task execution, improves task switching efficiency, and reduces the hardware dependence of complex logic. Cloud AI services cooperate with local control, using corresponding AI models to analyze the uploaded environmental images for required functions, generate accurate scoring results and improvement suggestions, and through cloud-based intelligent scheduling, the robot can flexibly switch working modes according to the needs of different inspection tasks. By calling the AI model through the API, local deployment of AI is avoided, greatly reducing hardware costs. It avoids a lot of complex training of local models, reducing time and labor costs.

[0026] Therefore, by calling the AI models corresponding to different inspection tasks, flexible switching between different inspection tasks can be achieved without the need for local deployment of algorithms, reducing time and labor costs and facilitating maintenance.

[0027] In one example, an AI cloud-based inspection robot also includes a wireless communication module connected to a Raspberry Pi via a USB port. This module enables data upload to the cloud service platform and real-time analysis of results.

[0028] In one example, if Figure 2As shown, the inspection robot based on AI cloud service also includes a database, which is connected to the cloud service platform and is used to store the image analysis data output by the AI model.

[0029] Further, refer to Figure 2 The inspection robot based on AI cloud service also includes a Web inspection system, which is connected to the database and is used for users to view image analysis data.

[0030] Web inspection system: A visual user interface where users can view the data returned by AI analysis.

[0031] Specifically, after the AI model analysis is completed, the cloud service platform 5 uploads the image analysis data to the MySQL database. Users can log in to the Web inspection system to view the image analysis data, or use the Web operation terminal to open and close the inspection process, forming a closed operation.

[0032] Specifically, in order to solve the problems of insufficient task switching, perception ability and flexibility of inspection robots, the present invention provides an inspection robot based on AI cloud service, which can achieve efficient switching between different tasks. Figure 2 , call the corresponding AI model of the AI cloud service platform through the API, and then set the corresponding indicator words for the current task, so as to achieve efficient switching between different tasks. For example, to check whether the clothing of the inspection staff is reasonable, first select the AI model for image analysis on the cloud service platform, and then write the AI model instruction words: Check the clothes of the employees on this production line to see if they are worn correctly. The inspection robot starts to follow the track. When the NFC module 1 senses the NFC sticker and recognizes that the content of the NFC sticker is for shooting, it activates the shooting function of the camera module 2 and simultaneously activates the voice module 4 to broadcast: Start shooting, please do not block the line of sight. The captured pictures are uploaded to the specified AI model through the Raspberry Pi 4B by calling the API. The AI model performs image analysis and uploads the analysis data to the MySQL database. Users can log in to the Web inspection system to view the analysis data.

[0033] The inspection robot primarily uses infrared sensors to sense the reflective properties of black stickers, adjusting its wheel steering based on this information to achieve path tracking. When the inspection robot detects an NFC sticker, the Raspberry Pi main control board uses the NFC parsing code to extract the sticker's content. If the content reads "shoot," the inspection robot stops and the main control board uses the shooting code to control the camera module to capture the factory environment. After capturing, the photo is uploaded to the AI cloud service platform via an API. The AI cloud service platform identifies and analyzes the image and performs corresponding functional analysis on the captured content. After scoring, the AI platform returns the data to the main control board, which stores the returned analysis content in a database. After storing the data, the inspection robot continues tracking and executes the same steps as above when it recognizes an NFC sticker.

[0034] In one example, the inspection robot is a four-wheeled inspection vehicle.

[0035] The camera module 2 is installed in front of the inspection robot, the NFC module 1 is installed below the inspection robot, the Raspberry Pi 3 is installed above the inspection robot, and there is at least one voice module 4, which is installed on both sides of the inspection robot.

[0036] In summary, the efficiency and accuracy of the inspection robot based on AI cloud service in the embodiment of the present invention, the multifunctional inspection robot, has been significantly improved. The inspection robot can independently complete multiple tasks including environmental inspection, equipment inspection, safety hazard identification, etc., and upload the scoring data and test results to the cloud without manual intervention, which greatly reduces the dependence on manpower. The cloud service platform is based on a standardized scoring model, which ensures the objectivity and accuracy of the scoring data and effectively eliminates the subjective bias in manual scoring. At the same time, the scoring and inspection data realize real-time feedback, allowing the factory to quickly identify problems and take corrective measures, forming an efficient closed-loop management system, and further improving the overall operational efficiency and factory environmental quality.

[0037] This invention has broad application prospects in the field of multifunctional inspection management. Its implementation injects intelligent and standardized management elements into traditional industrial fields, significantly improving management efficiency and accuracy. By reducing labor costs and improving inspection efficiency, it not only optimizes resource allocation but also indirectly promotes the overall improvement of factory production efficiency. The multifunctional inspection robot can flexibly perform a variety of tasks, such as environmental safety inspections, equipment status monitoring, and 5S scoring, further strengthening the intelligent management of the production process and improving the factory's operational efficiency and safety.

[0038] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. "Multiple" means two or more, unless otherwise specifically defined.

[0039] In the description of this specification, the reference terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" and the like are intended to mean that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are exemplary and are not to be construed as limiting the present invention. Those skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. An inspection robot based on AI cloud service, characterized in that: It includes an NFC module, a camera module, a Raspberry Pi, a voice module and a cloud service platform with multiple AI models, wherein each AI model corresponds to an inspection task, and all inspection tasks are different. The NFC module is connected to the Raspberry Pi through an SPI interface, the camera module is connected to the Raspberry Pi through a USB interface, the voice module is connected to the Raspberry Pi, and the Raspberry Pi is connected to the cloud service platform through an API interface.

2. The inspection robot based on AI cloud service according to claim 1, characterized in that: It also includes a wireless communication module that connects to the Raspberry Pi.

3. The inspection robot based on AI cloud service according to claim 1, characterized in that: It also includes a database, which is connected to the cloud service platform and is used to store the image analysis data output by the AI model.

4. The inspection robot based on AI cloud service according to claim 3, characterized in that: It also includes a Web inspection system, which is connected to the database and is used for users to view the image analysis data.

5. The inspection robot based on AI cloud service according to any one of claims 1 to 4, characterized in that: The camera module is installed directly in front of the inspection robot, the NFC module is installed directly below the inspection robot, the Raspberry Pi is installed directly above the inspection robot, and there is at least one voice module, which is installed on both sides of the inspection robot.

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