Mobile phone multi-terminal parallel detection system and method and computer storage medium

Abstract

The invention discloses a mobile phone multi-terminal parallel detection system and method and a computer storage medium, and belongs to the field of mobile terminal detection. The system comprises a multi-protocol access unit, a silent installation and authorization module, a task scheduling and control center, a synchronous control and exception handling module, a data aggregation and report generation engine and a dynamic migration and breakpoint positioning module. According to the invention, high throughput, low delay and strong fault-tolerant capability of multi-device parallel detection are realized, and the accuracy and efficiency of multi-terminal parallel detection are ensured.

Description

Technical Field

[0001] The present invention relates to the field of mobile terminal detection technology, and more particularly to a mobile phone multi-terminal parallel detection system, method and computer storage medium. Background Art

[0002] In the traditional mobile terminal (such as mobile phone) hardware detection process, a single device serial detection mode is usually adopted. Its typical operation process is as follows:

[0003] 1. Manual connection and authorization:

[0004] The operator connects the mobile phone and the testing computer one by one through a data cable, manually clicks "Trust this computer" on the mobile phone to authorize, and installs an independent testing tool or APP;

[0005] 2. Manually trigger the test item by item:

[0006] The tester needs to select test items one by one (such as screen, camera, microphone, etc.) on the computer or mobile phone APP;

[0007] After each test is completed, you need to manually record the results (such as whether there are bad pixels on the screen, whether the camera focus is normal), and then manually switch to the next test item;

[0008] 3. Data decentralized management:

[0009] Test results are usually saved in local files (such as Excel spreadsheets) or paper reports, lacking a unified database to support multi-device data comparison and analysis;

[0010] 4. Obvious efficiency bottleneck:

[0011] Single-unit testing takes about 10-30 minutes, and batch testing requires queuing, which is difficult to meet the needs of large-scale production;

[0012] Multiple devices need to be tested in parallel on multiple computers, which takes up a lot of space and human resources.

[0013] In summary, traditional mobile phone testing relies on a single-device tandem model, which presents challenges such as low efficiency, high reliance on manual labor, and fragmented data management. For example, testing requires manual connection to each device and triggering test items, and results are stored in a decentralized manner, making batch processing difficult. Furthermore, existing technologies lack collaborative control mechanisms, making it impossible to achieve simultaneous testing and anomaly isolation across multiple devices. This results in high testing costs and a high error rate.

[0014] Therefore, how to provide a mobile phone multi-terminal parallel detection system, method and computer storage medium is a problem that those skilled in the art urgently need to solve. Summary of the Invention

[0015] In view of this, the present invention provides a mobile phone multi-terminal parallel detection system, method and computer storage medium, which are used to solve the defects existing in the above-mentioned prior art.

[0016] In order to achieve the above object, the present invention provides the following technical solutions:

[0017] A mobile phone multi-terminal parallel detection system, comprising:

[0018] Multi-protocol access unit, used to connect multiple iOS and Android devices simultaneously and achieve independent power supply and communication;

[0019] Silent installation and authorization module, used to automatically install the detection package through the libimobiledevice library or ADB command, and perform breakpoint resumption;

[0020] The task scheduling and control center models the dependency relationships of detection items based on DAG, dynamically adjusts detection priorities through the Drools rule engine, and generates a list of detection tasks in JSON format.

[0021] Synchronization control and exception handling module, used for instruction synchronization, management of shared resources, and port reset;

[0022] Data aggregation and report generation engine, which automatically generates detection result labels based on preset thresholds and outputs reports through responsive templates;

[0023] The dynamic migration and breakpoint positioning module is used to migrate devices that exceed the threshold in the detection result labels, and at the same time use a dual-modal positioning algorithm to locate and breakpoint tasks.

[0024] Furthermore, the multi-protocol access unit includes:

[0025] Universal Serial Bus hub for connecting multiple iOS and Android devices simultaneously;

[0026] MFi certified chip for fast charging and stable power supply;

[0027] The usbmuxd protocol and ADB protocol modules are used for device communication.

[0028] Furthermore, the silent installation and authorization module includes:

[0029] The initial unit includes calling the libimobiledevice library to send installation instructions for iOS devices, triggering a system-level trust pop-up window; for Android devices, executing ADB commands to wake up the pop-up window and completing the detection package download by scanning the QR code;

[0030] The breakpoint resuming unit is used to resume unfinished installation tasks using the ideviceinstaller command.

[0031] Furthermore, the task scheduling and control center includes:

[0032] Detection item dependency management module, which models detection item dependencies based on DAG;

[0033] Dynamic priority adjustment module, which uses the Drools rule engine to dynamically adjust detection priorities;

[0034] The CPU resource allocation module adopts a three-level thread priority queue and allocates CPU resources through a time slice round-robin algorithm.

[0035] Furthermore, the synchronization control and exception handling module includes:

[0036] The synchronization unit sends synchronization instructions to all devices through the MQTT protocol and forces synchronization of manual intervention items;

[0037] Resource management unit, using CAS atomic operations and read-write locks to manage shared resources;

[0038] The reset unit uses a heartbeat detection mechanism to automatically reset the USB port when it times out.

[0039] Furthermore, the data aggregation and report generation engine includes:

[0040] Report generation unit, which automatically generates detection result labels based on preset thresholds and automatically fills them into responsive HTML / PDF templates to generate reports;

[0041] The output unit uses a two-column layout with CSS Grid to achieve responsiveness, and outputs reports using the PDF / A-1B standard to ensure archiving compatibility.

[0042] A method for parallel detection of multiple mobile terminals includes the following steps:

[0043] Connect multiple iOS and Android devices at the same time and achieve independent power supply and communication;

[0044] Automatically install the detection package and resume downloading through the libimobiledevice library or ADB command;

[0045] Based on DAG modeling, detection item dependencies are built, and detection priorities are dynamically adjusted through the Drools rule engine to generate a JSON-formatted detection task list.

[0046] Perform command synchronization, manage shared resources, and reset ports;

[0047] Automatically generate detection result labels based on preset thresholds and output reports through responsive templates;

[0048] The devices exceeding the threshold value in the detection result labels are migrated, and the dual-modal positioning algorithm is used to locate and breakpoint tasks.

[0049] A computer storage medium stores a computer program, which, when executed by a processor, implements the steps of a method for parallel detection of multiple mobile phone terminals.

[0050] It can be seen from the above technical solution that compared with the existing technology, the present invention discloses a mobile phone multi-terminal parallel detection system, method and computer storage medium, which solves the efficiency, collaboration, flexibility and data management problems of the existing technology through multi-device parallel control, automated process scheduling, human-computer collaborative interruption management and a unified data platform, and builds a high-throughput, low-error intelligent detection system to ensure the accuracy and efficiency of multi-terminal parallel detection, which is more suitable for mobile phone production quality inspection, after-sales maintenance and second-hand equipment recycling. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0052] Figure 1 Schematic diagram of the system structure of the present invention;

[0053] Figure 2 A flowchart for implementing the system of the present invention;

[0054] Figure 3 This is a schematic diagram of the specific data processing process of the system of the present invention. DETAILED DESCRIPTION

[0055] 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.

[0056] Example 1

[0057] See also Figure 1 The embodiment of the present invention discloses a mobile phone multi-terminal parallel detection system, comprising:

[0058] Multi-protocol access unit, used to connect multiple iOS and Android devices simultaneously and achieve independent power supply and communication;

[0059] Silent installation and authorization module, used to automatically install the detection package through the libimobiledevice library or ADB command, and perform breakpoint resumption;

[0060] The task scheduling and control center models the dependency relationships of detection items based on DAG, dynamically adjusts detection priorities through the Drools rule engine, and generates a list of detection tasks in JSON format.

[0061] Synchronization control and exception handling module, used for instruction synchronization, management of shared resources, and port reset;

[0062] Data aggregation and report generation engine, which automatically generates detection result labels based on preset thresholds and outputs reports through responsive templates;

[0063] The dynamic migration and breakpoint positioning module is used to migrate devices that exceed the threshold in the detection result labels, and at the same time use a dual-modal positioning algorithm to locate and breakpoint tasks.

[0064] Specifically, the multi-protocol access unit is the system's entry point, interacting directly with the silent installation module and the synchronization control module. The task scheduling and control center is the core coordination module, connecting the synchronization control, data aggregation, and dynamic migration modules. The synchronization control and exception handling module is responsible for command distribution and status monitoring, directly controlling all detection equipment. The data aggregation and report generation engine receives data bidirectionally from devices and the task scheduling module to generate the final output. The dynamic migration and breakpoint location module relies on the task scheduling module to trigger migrations and collaborates with the silent installation module to recover broken tasks.

[0065] In a specific embodiment, the multi-protocol access unit includes:

[0066] Universal Serial Bus hub for connecting multiple iOS and Android devices simultaneously;

[0067] MFi certified chip for fast charging and stable power supply;

[0068] The usbmuxd protocol and ADB protocol modules are used for device communication.

[0069] In a specific embodiment, the silent installation and authorization module includes:

[0070] The initial unit includes calling the libimobiledevice library to send installation instructions for iOS devices, triggering a system-level trust pop-up window; for Android devices, executing ADB commands to wake up the pop-up window and completing the detection package download by scanning the QR code;

[0071] The breakpoint resuming unit is used to resume unfinished installation tasks using the ideviceinstaller command.

[0072] In a specific embodiment, the task scheduling and control center includes:

[0073] Detection item dependency management module, which models detection item dependencies based on DAG;

[0074] Dynamic priority adjustment module, which uses the Drools rule engine to dynamically adjust detection priorities;

[0075] The CPU resource allocation module adopts a three-level thread priority queue and allocates CPU resources through a time slice round-robin algorithm.

[0076] In a specific embodiment, the synchronization control and exception handling module includes:

[0077] The synchronization unit sends synchronization instructions to all devices through the MQTT protocol and forces synchronization of manual intervention items;

[0078] Resource management unit, using CAS atomic operations and read-write locks to manage shared resources;

[0079] The reset unit uses a heartbeat detection mechanism to automatically reset the USB port when it times out.

[0080] In one embodiment, the data aggregation and report generation engine includes:

[0081] Report generation unit, which automatically generates detection result labels based on preset thresholds and automatically fills them into responsive HTML / PDF templates to generate reports;

[0082] The output unit uses a two-column layout with CSS Grid to achieve responsiveness, and outputs reports using the PDF / A-1B standard to ensure archiving compatibility.

[0083] See also Figure 2 The system of the present invention roughly implements the following process: plug in the mobile phone, detect the mobile phone hardware information and automatically install the quality inspection app → batch quality inspection of multiple mobile phones → quality inspection report is actively generated and synchronized, and can be viewed on multiple terminals (app, aio, ERP background).

[0084] See also Figure 3, the background data summary represents the data processing center of the system, which is responsible for receiving and integrating all detection data. The all-in-one device, as the hardware core, is displayed as a physical device icon directly connected to the background data summary module (such as a server cabinet icon), and the all-in-one device is marked as receiving background instructions and sending detection data back to the background. The network app refers to the presentation of mobile or web interface icons. Users submit detection requests through the app and receive reports. From a holistic perspective, the process includes: data upload, instruction issuance and collaborative control, as well as result display and feedback. Among them, users upload mobile phone hardware information (such as model, serial number) through the app and trigger the detection process. The detection results (such as screen touch data, sensor values) are uploaded to the background in real time. The background issues detection task configuration (such as detection item priority, threshold rules), controls the parallel detection process of multiple devices, and the summary report after the detection is completed (such as HTML / PDF file) is pushed to the user through the app.

[0085] On the other hand, an embodiment of the present invention further provides a method for parallel detection of multiple mobile terminals, including the following steps:

[0086] Connect multiple iOS and Android devices at the same time and achieve independent power supply and communication;

[0087] Automatically install the detection package and resume downloading through the libimobiledevice library or ADB command;

[0088] Based on DAG modeling, the dependency relationships between detection items are modeled, and the detection priority is dynamically adjusted through the Drools rule engine to generate a JSON-formatted detection task list.

[0089] Perform command synchronization, manage shared resources, and reset ports;

[0090] Automatically generate detection result labels based on preset thresholds and output reports through responsive templates;

[0091] The devices exceeding the threshold value in the detection result labels are migrated, and the dual-modal positioning algorithm is used to locate and breakpoint tasks.

[0092] On the other hand, an embodiment of the present invention further provides a computer storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of a method for parallel detection of multiple mobile terminals are implemented.

[0093] Example 2:

[0094] The specific implementation process of the present invention may include the following steps:

[0095] (1) Device connection and authorization:

[0096] Connect multiple mobile phones to be tested to the device through the multi-protocol data cable of the all-in-one machine;

[0097] The all-in-one machine uses the USB HUB (Universal Serial Bus HUB) expansion interface to ensure that each data line has independent power supply and communication;

[0098] For iPhones: Using the usbmuxd protocol (the core protocol for Apple devices to communicate with computers), call the libimobiledevice library or private APIs (such as the lockdownd protocol) to send a connection command to the iOS device, triggering a system-level trust pop-up window. After manually clicking "trust," use the ideviceinstaller tool in the libimobiledevice library to send installation instructions directly over USB to silently install the detection package. For Android phones: Manually enable USB debugging mode, plug in the cable, and execute the adb devices command on the device to wake up the system pop-up window. Scan the QR code in the backend to download the detection package.

[0099] Adopt MFi certified chips (such as C94) to ensure stable power supply of data line (voltage fluctuation threshold ±3%) and support 2.4A fast charging protocol. Real-time monitoring of charging handshake protocols (such as Apple 2.4A, USB-PD), dynamically adjusting the power supply mode to prevent the device from entering the protection state. Heartbeat detection: Send lockdownd protocol heartbeat packets every 300ms, and automatically reset the USB port (call ideviceconnection_reset) after 3 times of timeout. Resume after disconnection: When the installation process is interrupted, use the ideviceinstaller-u[UDID]-l command to resume the unfinished task.

[0100] (2) Detection task configuration and initialization:

[0101] In the management backend, select or customize detection items (such as screen, camera, battery, front and rear microphones) to generate a task list in JSON (JavaScript Object Notation) format. When generating the JSON task list:

[0102] 1. Priority matrix for built-in test items: Prioritize basic hardware tests (e.g., battery voltage test → screen test → sensor test); adhere to resource isolation (avoid running CPU-intensive camera tests and I / O-intensive storage tests simultaneously); and use DAGs (directed acyclic graphs) to model test item dependencies. For example, microphone tests must be performed after speaker tests to prevent acoustic interference.

[0103] 2. Implemented using the Drools rule engine: When it is detected that the basic battery power test is not completed, the screen test is automatically placed at the top to avoid screen brightness test errors caused by abnormal power.

[0104] (3) Network communication exception handling mechanism:

[0105] Multi-level retry strategy, exponential backoff retry: initial timeout 5 seconds, each time increasing by 2 seconds; network environment sniffing:

[0106] Automatically switch between TCP / UDP protocols (detect MTU value through getsockopt).

[0107] The device's unique device identifier (UDI) is read via the USB (Universal Serial Bus) protocol, and the cloud is queried for the model's detection parameter library. The parameters are loaded into local memory (such as screen brightness threshold and touch verification rules) to initialize the detection logic.

[0108] Multi-device synchronous detection execution (core synchronization control process):

[0109] 1. Start the detection task: The synchronization control module creates an independent thread for each device, uses time-sharing multiplexing and priority scheduling, and adopts a dynamic allocation algorithm based on time slice rotation to allocate CPU resources with a fixed time slot for each detection thread (for example, a 5ms time slice for each thread). Establish a three-level priority queue:

[0110] 1.1 Real-time level (camera focus test): preemptive scheduling, response delay <10ms;

[0111] 1.2 Ordinary level (screen touch test): time slice round-robin scheduling.

[0112] 1.3 Background level (log upload): scheduling during idle time.

[0113] Use the Linux memory control group (cgroup) to limit the maximum memory usage of each thread to prevent OOM exceptions.

[0114] CAS atomic operations are used for shared resources (such as the detection result cache). ReentrantReadWriteLock is used for USB communication channels, allowing concurrent reads but exclusive writes. Dynamic migration is triggered when any metric exceeds the threshold: the device thread is migrated to a backup compute node. Instructions are sent to all devices via the MQTT (Message Queuing Telemetry Transport) protocol. After receiving the instructions, the device starts the corresponding detection module (such as camera detection).

[0115] 2. Synchronous detection and waiting mechanism:

[0116] 2.1 Single device completes the test item: After the device completes the current test item (such as T1 camera test), it sends a command to the synchronization control module; enters the waiting state: the device-side APP suspends subsequent operations and displays "Waiting for other devices to complete".

[0117] 2.2 Master synchronization control: The synchronization control module counts the number of completed tests of all devices in real time. If all online devices return a confirmation signal, a command is sent;

[0118] 3. Synchronization of manual intervention items:

[0119] 3.1 If the test item requires manual operation (such as screen touch test): all devices will pop up the operation prompt (such as "Please click the screen 5 times") at the same time; the worker will operate each mobile phone in turn, and the device will send the instruction after completing the operation; forced synchronization: the synchronization control module will wait for all devices to complete the operation before allowing the next test item to proceed.

[0120] (4) Data aggregation and report generation:

[0121] Receive raw data uploaded by each device (such as touch coordinates and sensor values ​​in JSON format);

[0122] Perform threshold comparison based on preset rules (e.g., screen brightness of 300±0.5nit is acceptable) and generate normal / abnormal labels;

[0123] Fill the data into the preset HTML / PDF template, which uses a responsive layout solution:

[0124] 1. A two-column layout (70% main content area + 30% sidebar), implemented using CSS Grid.

[0125] 2. Breakpoint design: @media (max-width: 768px) switches to a single-column fluid layout.

[0126] Cross-platform compatibility guarantee:

[0127] PDF generation strategy:

[0128] PDFDocument doc=new PDFDocument();

[0129] doc.setComplianceLevel(PDF_A_1B); / / Force compliance with archiving standards

[0130] doc.embedFonts(StandardFonts.HELVETICA_BOLD);

[0131] doc.setColorProfile(ColorProfile.SRGB);

[0132] HTML5 feature detection:

[0133] if(!('grid'in document.documentElement.style)){

[0134] loadFallbackCSS('legacy-layout.css'); / / compatible with IE11

[0135] }

[0136] Automatically generate a report containing:

[0137] Basic device information (model, memory, serial number);

[0138] Test item results (in tabular form, including normal / abnormal status);

[0139] Abnormal items are highlighted (such as "rear camera abnormality").

[0140] (5) Report management and retesting mechanism:

[0141] Data is uploaded to the cloud backend, allowing retrieval by device ID, test date, and result status (normal / abnormal). Select the abnormal device on the report interface and click the "Retest" button. An SQL MERGE statement is used to implement UPSERT operations, employing the CRDT conflict-free replicated data type to handle concurrent writes and enable correlation and integration of test data.

[0142] (6) The system automatically locates breakpoint tasks:

[0143] A dual-modal positioning algorithm is used. The algorithm selection is based on the following: hardware detection items (such as screen touch) use the M / T method two-wire capacitive positioning with an accuracy of ±0.3mm; software detection items (such as system stress testing) use hash table tracing and verify the historical progress block through SHA-256; retesting is only initiated for failed items to avoid repeated execution of passed tests.

[0144] Specifically, the present invention is mainly used in the field of large-scale quality inspection and performance evaluation of mobile terminal equipment, and is particularly suitable for scenarios such as mobile phone manufacturing, after-sales maintenance, and second-hand equipment recycling. On a mobile phone production line, it can be deployed in the quality inspection link before leaving the factory. By connecting the devices to be inspected in batches, it can simultaneously complete automated testing of core hardware such as screen touch sensitivity, camera imaging, and sensor functions to ensure product qualification rate; in after-sales maintenance centers, it can quickly diagnose hardware anomalies of multiple faulty mobile phones (such as speaker damage, battery loss), accurately locate problems, and generate repair reports; in second-hand mobile phone recycling scenarios, it supports simultaneous detection of the quality, performance, and hardware integrity of dozens of devices, improving detection efficiency and reducing labor costs. In addition, the present invention can also be expanded to a laboratory environment for multi-model hardware compatibility testing or long-term stability stress testing to meet the needs of batch data collection in the research and development stage.

[0145] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0146] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A mobile phone multi-terminal parallel detection system, characterized in that: include: Multi-protocol access unit, used to connect multiple iOS and Android devices simultaneously and achieve independent power supply and communication; Silent installation and authorization module, used to automatically install the detection package through the libimobiledevice library or ADB command, and perform breakpoint resumption; The task scheduling and control center models the dependency relationships of detection items based on DAG, dynamically adjusts detection priorities through the Drools rule engine, and generates a list of detection tasks in JSON format. Synchronization control and exception handling module, used for instruction synchronization, management of shared resources, and port reset; Data aggregation and report generation engine, which automatically generates detection result labels based on preset thresholds and outputs reports through responsive templates; The dynamic migration and breakpoint positioning module is used to migrate devices that exceed the threshold in the detection result labels, and at the same time use a dual-modal positioning algorithm to locate and breakpoint tasks.

2. A mobile phone multi-terminal parallel detection system according to claim 1, characterized in that: The multi-protocol access unit includes: Universal Serial Bus hub for connecting multiple iOS and Android devices simultaneously; MFi certified chip for fast charging and stable power supply; The usbmuxd protocol and ADB protocol modules are used for device communication.

3. A mobile phone multi-terminal parallel detection system according to claim 1, characterized in that: The silent installation and authorization module includes: The initial unit includes calling the libimobiledevice library to send installation instructions for iOS devices, triggering a system-level trust pop-up window; for Android devices, executing ADB commands to wake up the pop-up window and completing the detection package download by scanning the QR code; The breakpoint resuming unit is used to resume unfinished installation tasks using the ideviceinstaller command.

4. A mobile phone multi-terminal parallel detection system according to claim 1, characterized in that: The task scheduling and control center includes: Detection item dependency management module, which models detection item dependencies based on DAG; Dynamic priority adjustment module, which uses the Drools rule engine to dynamically adjust detection priorities; The CPU resource allocation module adopts a three-level thread priority queue and allocates CPU resources through a time slice round-robin algorithm.

5. A mobile phone multi-terminal parallel detection system according to claim 1, characterized in that: The synchronization control and exception handling module includes: The synchronization unit sends synchronization instructions to all devices through the MQTT protocol and forces synchronization of manual intervention items; Resource management unit, using CAS atomic operations and read-write locks to manage shared resources; The reset unit uses a heartbeat detection mechanism to automatically reset the USB port when it times out.

6. A mobile phone multi-terminal parallel detection system according to claim 1, characterized in that: The data aggregation and report generation engine includes: Report generation unit, which automatically generates detection result labels based on preset thresholds and automatically fills them into responsive HTML / PDF templates to generate reports; The output unit uses a two-column layout with CSS Grid to achieve responsiveness, and outputs reports using the PDF / A-1B standard to ensure archiving compatibility.

7. A method for parallel detection of multiple mobile terminals, characterized in that: The following steps are involved: Connect multiple iOS and Android devices at the same time and achieve independent power supply and communication; Automatically install the detection package and resume downloading through the libimobiledevice library or ADB command; Based on DAG modeling, detection item dependencies are built, and detection priorities are dynamically adjusted through the Drools rule engine to generate a JSON-formatted detection task list. Perform command synchronization, manage shared resources, and reset ports; Automatically generate detection result labels based on preset thresholds and output reports through responsive templates; The devices exceeding the threshold value in the detection result labels are migrated, and the dual-modal positioning algorithm is used to locate and breakpoint tasks.

8. A computer storage medium, characterized in that The computer storage medium stores a computer program, and when the computer program is executed by the processor, the steps of the method for parallel detection of multiple mobile terminals according to any one of claims 1 to 7 are implemented.

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