Special notebook triggering working method and system based on handle tension detection

Abstract

The invention discloses a special notebook triggering working method and system based on handle pulling force detection, and relates to the technical field of intelligent equipment starting control, and the method comprises the steps: deploying bidirectional pulling force detection units in left and right carrying handles of a notebook; when the continuous sampling value of the left or right tension detection unit meets a static threshold value in a preset sampling period, a motion monitoring command is started; and configuring a monitoring window according to the command to record tension change fluctuation, establishing a tension fluctuation data set, sending the tension fluctuation data set to the EC control chip, and controlling the notebook computer to be pre-started if the chip judges that a startup standard is met. The technical problems of operation delay and low efficiency caused by the fact that an existing special notebook computer is too long in starting time and cannot accurately recognize the instant starting requirement of a user under the emergency condition are solved, intelligent pre-starting of equipment is achieved through tension detection, starting delay is reduced, and the starting efficiency is improved. And the response speed of the equipment in a special environment is improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent device start-up control technology, specifically to a special notebook triggering method and system based on handle pull force detection. Background Technology

[0002] With the increasing complexity of special operating environments and the growing urgency of tasks, the demand for rapid equipment response is growing. Specialty laptops, as crucial tools in mission-critical execution, rely heavily on rapid startup capabilities to improve work efficiency. However, the startup process of existing specialty laptops still relies on traditional manual operation, resulting in startup delays and untimely responses. Furthermore, current technologies struggle to accurately identify users' immediate startup needs, leading to incorrect or missed startups and impacting task execution efficiency. Summary of the Invention

[0003] This application provides a special notebook computer triggering method and system based on handle pull force detection, which is used to solve the technical problems of existing special notebook computers having excessively long startup time in emergency situations and failing to accurately identify the user's immediate startup needs, resulting in operation delays and low efficiency.

[0004] In a first aspect, this application provides a special notebook computer triggering method based on handle pull force detection. The method includes: deploying bidirectional pull force detection units inside the left and right handles of the notebook computer, the bidirectional pull force detection units including a left pull force detection unit and a right pull force detection unit; if the continuous sampling value of the left or right pull force detection unit meets a static threshold within a preset sampling period, then initiating a motion monitoring command; configuring N monitoring windows according to the motion monitoring command to record the periodic pull force fluctuations of the bidirectional pull force detection units, and establishing a pull force fluctuation dataset; sending the pull force fluctuation dataset to an EC control chip, and if the EC control chip determines that the boot-up standard is met, then controlling the notebook computer to pre-boot.

[0005] Secondly, this application provides a special notebook triggering system based on handle pull force detection. The system includes: a pull force detection unit deployment module for deploying bidirectional pull force detection units inside the left and right handles of the notebook, the bidirectional pull force detection units including a left pull force detection unit and a right pull force detection unit; a motion monitoring module for initiating a motion monitoring command if the continuous sampling value of the left or right pull force detection unit meets a static threshold within a preset sampling period; a pull force change fluctuation recording module for configuring N monitoring windows according to the motion monitoring command to record the periodic pull force change fluctuations of the bidirectional pull force detection units and establish a pull force fluctuation dataset; and a pre-start determination control module for sending the pull force fluctuation dataset to an EC control chip, and controlling the notebook to pre-start if the EC control chip determines that the power-on start standard is met.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0007] This application provides a method and system for triggering operation of a special laptop based on handle pull force detection, relating to the field of intelligent device start-up technology. By deploying a bidirectional pull force detection unit inside the laptop handle, it monitors pull force changes in real time, determines whether the device is in a moving state, and triggers motion monitoring based on pull force fluctuation data. The EC control chip determines whether the power-on start-up standard is met, thereby realizing intelligent pre-start of the device. This solves the technical problems of existing special laptops having excessively long start-up times in emergency situations and being unable to accurately identify the user's immediate start-up needs, leading to operation delays and low efficiency. It achieves the technical effect of realizing intelligent pre-start of the device through pull force detection, reducing start-up delay, and improving the response speed of the device in special environments. Attached Figure Description

[0008] Figure 1 A schematic diagram of a special notebook triggering method based on handle pull force detection provided in this application;

[0009] Figure 2 This application provides a schematic diagram of the structure of an electronic device based on a special notebook triggering method using handle pull force detection;

[0010] Figure 3 This application provides a schematic diagram of a special notebook triggering system based on handle pull force detection.

[0011] Figure labeling: 11 Tensile detection unit deployment module, 12 Motion monitoring module, 13 Tensile fluctuation recording module, 14 Pre-start judgment control module. Detailed Implementation

[0012] This application provides a special notebook computer triggering method and system based on handle pull force detection, which solves the technical problem that existing special notebook computers have excessively long startup times in emergency situations and cannot accurately identify the user's immediate startup needs, resulting in operation delays and low efficiency.

[0013] Example 1, as Figure 1 As shown, this application provides a special notebook computer triggering operation method based on handle pull force detection, the method including:

[0014] P10: As Figure 2 As shown, a bidirectional tension detection unit is deployed inside the left and right handles of the laptop. The bidirectional tension detection unit includes a left tension detection unit and a right tension detection unit.

[0015] Specifically, a left-hand pull detection unit and a right-hand pull detection unit are installed inside the left and right handles of the special laptop, respectively, to create a bidirectional pull detection unit capable of monitoring changes in pull force generated when the user lifts the laptop in real time. The bidirectional pull detection unit consists of two pull sensors, installed inside the left and right handles of the laptop, respectively. Each pull sensor is responsible for detecting changes in pull force from the corresponding side; when the user lifts the laptop or applies external force, the sensor senses and records the change in real time.

[0016] To achieve this functionality, a suitable tension sensor must first be selected. These sensors must be high-precision, small in size, and low-power to accurately detect minute changes in tension when the user lifts the laptop, without affecting the laptop's overall appearance or normal use. During installation, the tension sensor is embedded in the handle's internal structure, ensuring a tight fit that effectively protects the sensor from external environmental influences while guaranteeing its proper functioning.

[0017] These tension sensors accurately measure the tension applied to the laptop handle and transmit the data to an embedded control chip (EC). The chip analyzes this tension data in real time to determine if the device is in a normal moving state. When the device is lifted, the tension data from the sensors on both sides changes. By analyzing this data, it can confirm whether the device has started moving and determine whether the pre-start conditions are met based on the intensity and direction of the movement. Unlike traditional single-detection methods, the application of bidirectional tension sensors ensures accurate detection of the device under various conditions, whether it's the magnitude of the force applied by the left or right hand, or changes in tension due to differences in the wearer's pace or strength; the system can efficiently identify these variations.

[0018] In practical applications, the system uses data from the left and right pull detection units to determine whether the laptop has started to move and triggers the corresponding control commands. This bidirectional detection method can more comprehensively capture the user's lifting action characteristics, thereby providing a more accurate trigger signal for the pre-boot process, thus shortening the device startup waiting time in special scenarios and improving the device's response speed.

[0019] P20: If the continuous sampling values ​​of the left tension detection unit or the right tension detection unit meet the static threshold within the preset sampling period, then the motion monitoring command is started.

[0020] Optionally, a preset sampling period can be set, during which either the left or right pull force detection unit will continuously sample the pull force applied to the laptop handle. These samples capture fluctuations in pull force in real time. When the system detects that the continuous sampling value of either sensor exceeds the set static threshold, it can determine that the device is being carried or moved.

[0021] The static threshold is a pre-set tension value that represents the normal range recorded by the left and right tension sensors when the laptop is not being moved. This value distinguishes the laptop from a stationary state to a state about to be moved. When the tension detection unit detects a tension value exceeding this static threshold, it indicates that the laptop may be being lifted or moved, rather than being stationary. The static threshold can be calibrated based on factors such as the weight of the device, the material of the handle, and the user's carrying method to ensure that the sensor's sampling value does not falsely trigger the system when no external force is applied.

[0022] If the sampled values ​​of either the left or right tension detection unit continuously exceed the static threshold within the preset sampling period, it indicates that the equipment has begun to be affected by external forces and has entered a moving state. At this point, a motion monitoring command can be immediately initiated. The purpose of the motion monitoring command is to initiate subsequent detection and control processes, such as configuring the monitoring window and recording tension fluctuation data, to further analyze the equipment's status and trigger corresponding operations. This process ensures that the equipment's startup accurately matches the actual moving state, thereby achieving precise pre-start control.

[0023] P30: Configure N monitoring windows according to the motion monitoring command to record the periodic tensile force fluctuation of the bidirectional tensile force detection unit and establish a tensile force fluctuation dataset.

[0024] It should be understood that when a motion monitoring command is triggered, the system will configure multiple monitoring windows according to the command. These monitoring windows will periodically record the changes in the tension sensor at preset time intervals, thereby capturing the tension fluctuation characteristics of the device during carrying or movement.

[0025] Specifically, N monitoring windows are configured, where N is a positive integer set according to actual needs. Each monitoring window has a fixed time length, such as 1 second or a shorter time interval. Within each monitoring window, the bidirectional tension detection unit periodically samples the tension data. Since the user's movement while carrying the device may be accompanied by different force changes, such as acceleration or deceleration of steps, changes in carrying force, etc., recording data in multiple monitoring windows can capture a variety of different tension fluctuations.

[0026] Therefore, within each monitoring window, the left and right pull force detection units record the pull force values ​​they detect. These pull force values ​​reflect the magnitude and variation of the force applied by the user when lifting or moving the laptop. By sampling and recording pull force data across multiple monitoring windows, the system can establish a complete pull force fluctuation dataset. This dataset contains the pull force changes of the device at different time points and reflects various fluctuation patterns during device movement. For example, when the user moves the laptop at a stable speed, the pull force fluctuation may be relatively small; while when the user moves quickly or changes direction, the pull force fluctuation may increase significantly. This fluctuation data will form the basis for subsequent judgments on whether the device meets the pre-boot conditions. This process provides sufficient basic data for subsequent pre-boot decisions, helping to improve the accuracy and response speed of the device boot process.

[0027] P40: Send the tensile fluctuation dataset to the EC control chip. If the EC control chip determines that the power-on startup criteria are met, it controls the laptop to pre-start.

[0028] Furthermore, the tensile fluctuation dataset is sent to the EC control chip. In this embodiment, step P40 further includes:

[0029] P41: Determine whether the tensile fluctuation dataset meets the stop pulling mode; P42: If the tensile fluctuation dataset meets the stop pulling mode, the EC control chip determines that the boot-up standard is not met and stops executing the laptop's boot command.

[0030] Optionally, the tension fluctuation dataset recorded through the monitoring window can be sent to the EC control chip for processing. Upon receiving the tension fluctuation dataset, the EC control chip will first analyze the dataset to determine if it meets the preset power-on start-up criteria. These criteria are based on the tension change pattern of the equipment during movement; for example, within a certain tension fluctuation range, it indicates that the equipment has been fully lifted and is in a moving state, meeting the start-up conditions.

[0031] When the EC control chip determines that the tensile fluctuation dataset meets the boot criteria, it issues a command to control the laptop to enter a pre-boot state. At this time, the laptop's boot process will proceed automatically without the user needing to manually press the power button, thus saving time and improving emergency response capabilities.

[0032] Specifically, the EC control chip first determines whether the tension fluctuation dataset meets the stop-pull pattern. The stop-pull pattern refers to the user's behavior pattern of stopping movement or putting down the laptop after lifting it. This pattern is determined by analyzing specific features in the tension fluctuation dataset. For example, when the EC control chip receives the tension fluctuation dataset, it first checks whether the dataset contains features of the stop-pull pattern. These features may include a sudden decrease in tension, a decrease in the frequency of tension fluctuations, and a shortening of the tension duration. If the EC control chip detects these features, it determines that the tension fluctuation dataset meets the stop-pull pattern.

[0033] If the tensile fluctuation dataset meets the stop-pull mode, the EC control chip will determine that the device has not met the power-on standard. In this case, the EC control chip will stop executing the laptop's boot command to avoid unnecessary pre-boot operations due to misjudgment, thereby ensuring the rational use of battery and system resources and avoiding unnecessary power consumption. In this way, the device's boot process can be controlled more precisely, improving the efficiency and accuracy of device startup.

[0034] Furthermore, step P41 in this embodiment of the application also includes:

[0035] P41-1: If the tension fluctuation dataset does not meet the stop pulling mode, then perform tension analysis on the tension fluctuation data. The tension analysis includes a comparison of the tension change rate of the left and right tensions and a directional fluctuation analysis of the independent tensions. P41-2: Establish a laptop motion status label based on the tension analysis results. P41-3: Perform boot-up standard judgment and management based on the laptop motion status label.

[0036] Specifically, the detailed analysis process of the tensile fluctuation dataset can be further refined to enhance the equipment's intelligent judgment capabilities and improve the accuracy of startup.

[0037] First, if the tension fluctuation dataset does not meet the stop-pull mode (i.e., the device has not completely stopped or is being pulled to some extent), the system will perform a more detailed analysis of the tension fluctuation data. This analysis includes comparing the rate of change of tension between the left and right sides. By analyzing the rate of change of tension recorded by the left and right tension detection units, the system determines whether the user's force is balanced when moving the laptop. For example, if the rate of change of tension with the left hand is significantly higher than that with the right hand, or vice versa, this may indicate that the user is tilting or unbalanced during movement.

[0038] Simultaneously, the system analyzes the directional fluctuations of independent pulling forces. This analysis primarily focuses on the changes in the direction of the pulling force recorded by a single pulling force detection unit. For example, if the direction of the pulling force on one side fluctuates frequently within a short period, it may indicate that the user is making unstable movements while moving the laptop, such as rapid turns or shaking. By analyzing the directional fluctuations of independent pulling forces, the system can further refine its understanding of user movement behavior, thereby more accurately determining the laptop's motion status.

[0039] Based on these tension analysis results, a motion status label is established for the laptop. This label identifies the current motion mode of the device and whether it is in a suitable state for powering on. This label is a quantitative description of the laptop's current motion status, combining the results of comparing the left and right tension change rates and analyzing the independent tension direction fluctuations. For example, if the tension change rate comparison shows that the left and right tensions are balanced and the independent tension direction fluctuations are small, the system may define the laptop's motion status label as "smooth movement"; conversely, if the tension change rate is unbalanced and the direction fluctuations are large, the motion status label may be defined as "unstable movement".

[0040] Finally, the system manages and determines the boot criteria based on the established notebook motion status tags. These boot criteria are set according to the notebook's motion status tags, with different tags corresponding to different boot conditions. For example, if the motion status tag is "smooth movement" and the duration reaches a preset threshold, the system may determine that the boot criteria are met, thus triggering the notebook's pre-boot process. Conversely, if the motion status tag is "unstable movement," the system may delay booting or require further confirmation to avoid unnecessary boot operations due to misjudgment.

[0041] Furthermore, step P41-3 in the embodiments of this application also includes:

[0042] P41-31: If the tension fluctuation dataset does not meet the stop pulling mode, the position sensor is activated synchronously to obtain the current position information and read the preset target working position; P41-32: The movement path is updated based on the current position information and the preset target working position; P41-33: Periodic fluctuation analysis is performed on the tension fluctuation dataset, and step frequency data is configured; P41-34: The power-on start-up standard is judged and managed according to the laptop movement status label, the step frequency data, and the movement path.

[0043] Optionally, the boot-up criteria management process based on the tension fluctuation dataset can be further refined by introducing the analysis of position sensor and step frequency data to more comprehensively evaluate the laptop's motion status.

[0044] First, if the tension fluctuation dataset does not meet the stop-pull mode, the system will synchronously activate the position sensor to acquire the current location information and read the preset target working position. The position sensor can be a GPS module, a Wi-Fi positioning module, or other suitable positioning technology to obtain the laptop's geographical location information in real time. By acquiring the current location information, the system determines whether the device is close to the preset target working position. This information is crucial for subsequent startup decisions, as the device can only start working when it reaches the appropriate location.

[0045] Next, based on the current location information and the preset target working position, the device's motion path is updated. The purpose of motion path updating is to optimize the device's startup timing and process, especially when the device has multiple preset working positions. By adjusting the path, it ensures that the device can start up at the correct time and place. This process dynamically adjusts the laptop's motion path by analyzing the distance and direction between the current position and the target position. For example, if the current position deviates from the preset motion path, the system can adjust the path planning in real time to ensure that the laptop can efficiently reach the target position.

[0046] Next, periodic fluctuation analysis is performed on the tension fluctuation dataset, and cadence data is configured. Cadence data refers to the frequency of a user's walking while moving the laptop. By analyzing the periodic fluctuations in the tension fluctuation dataset, the user's walking cadence can be estimated. A faster cadence may indicate that the device is in a state of rapid movement, while a slower cadence may indicate that the device is in a more stable carrying state. The collection of cadence data helps improve the system's accurate understanding of the device's movement state, thereby making more reasonable start-up decisions.

[0047] Finally, the system manages and determines the boot criteria based on the laptop's motion status label, cadence data, and the updated motion path. The motion status label reflects the device's movement pattern, the cadence data provides the frequency changes during movement, and the updated motion path ensures the device reaches the target working position along the predetermined path. This information is combined to ensure the system's boot criteria are more intelligent and accurate. For example, if the laptop's motion status label shows "smooth movement," the cadence data indicates the user is moving at a stable speed, and the motion path matches the preset path, then the boot criteria are met, triggering the laptop's pre-boot process. Conversely, if the motion status is unstable, the cadence is abnormal, or the path deviates from the preset path, the system may delay booting or require further confirmation to avoid misjudgment. This step comprehensively and accurately considers the device's current state and expected path, further optimizing the device's boot timing and path selection, thereby improving the system's response speed and reliability.

[0048] Furthermore, steps P41-33 in the embodiments of this application also include:

[0049] P41-331: Record data on the personnel carrying the equipment and establish a user profile; P41-332: Perform interactive authentication of the personnel carrying the equipment during the lifting process and establish the interactive authentication result; P41-333: Configure step frequency data based on the user profile, interactive authentication result, and periodic fluctuation analysis result.

[0050] Specifically, the analysis of the tension fluctuation dataset can be further expanded by introducing user profiling and identity interaction authentication mechanisms to configure step frequency data more accurately.

[0051] First, the system continuously records the behavioral data of those carrying the device. This data covers various behavioral characteristics of users while using the laptop, such as movement habits, tension patterns, cadence, and movement paths. Through long-term collection and analysis of this data, the system can build a detailed user profile. A user profile is a quantitative description of a user's behavioral characteristics and habits, helping the system better understand the user's usage patterns and needs. For example, the system can record the tension fluctuation patterns, corresponding cadence, and movement paths of users during normal walking, fast running, or slow movement. This data will be stored in the system to provide a basis for subsequent analysis and decision-making.

[0052] Next, during the device lifting process, the system will perform identity verification for the person carrying the device. The purpose of this process is to ensure that the person carrying the device is an authorized user through identity verification methods. Identity verification can take various forms, such as comparing the user's biometric information (e.g., fingerprint, facial recognition) or confirming the person's identity using preset user credentials (e.g., password, mobile phone verification). The authentication result will be recorded and formed as an interaction authentication result, which will influence the device's activation decision along with other sensor data.

[0053] Finally, the cadence data is configured by combining user profiles, interaction authentication results, and periodic fluctuation analysis results. Specifically, the system will analyze periodic fluctuation data after confirming the user's identity based on the user's behavioral characteristics and habits recorded in the user profile and the interaction authentication results. For example, if the user profile shows that the user's cadence is 120 steps per minute when walking normally and 150 steps per minute when moving quickly, the system will determine the user's current walking speed and rhythm based on the current periodic fluctuation analysis results and configure the cadence data accordingly. In this way, cadence data can be configured more accurately, and by combining identity interaction authentication results, it ensures that only the behavior of authorized users is used for cadence data configuration and subsequent activation decisions.

[0054] These steps enable not only physical monitoring of equipment movement but also multi-dimensional analysis of personnel identity and behavioral patterns, thereby achieving more intelligent and precise pre-start control of equipment.

[0055] Furthermore, steps P41-34 in the embodiments of this application also include:

[0056] P41-341: Configure a tolerance time window using the notebook motion status label; P41-342: Obtain the notebook's preset startup time, and establish a baseline startup time node based on the preset startup time and the tolerance time window; P41-343: Perform motion simulation based on motion path and step frequency data, establish a simulation time axis, and reconstruct the startup time node after time conversion of the simulation time axis and the baseline startup time node; P41-344: If the reconstructed startup time node is met, it is determined that the boot-up standard is met.

[0057] It should be understood that the user's status can be determined based on the laptop's motion status label, thereby adjusting the device's pre-boot time and startup node.

[0058] First, a grace period window is configured based on the laptop's motion status label. The length of this grace period window depends on the user's pulling action, i.e., whether the user is in an urgent situation. If the user's actions are stable, the system determines that the user is not in a hurry to use the laptop, and a shorter grace period window is configured, in which case the laptop will enter a normal pre-boot mode. Conversely, if the user's actions indicate urgency, such as a single-sided pulling motion or an abrupt stop, a longer grace period window is configured to start the laptop earlier to accommodate the user's urgent needs.

[0059] Next, obtain the laptop's preset boot time and, in conjunction with the configured tolerance time window, establish a baseline boot time node. The baseline boot time node refers to the time the device should boot under normal conditions. The preset boot time refers to the time required for the laptop to fully boot from the start of pre-boot under normal usage conditions. By incorporating the tolerance time window, the baseline boot time node can be adjusted to suit different users' habits and urgency levels. For example, if the device is in a more urgent boot mode, the baseline boot time node will be shifted forward to boot the device as early as possible.

[0060] Next, motion simulation is performed based on the device's movement path and step frequency data. By simulating the user's path and steps while carrying the device, the system can predict the time required for the device to reach the target location from its current position, constructing a simulated timeline. By constructing this simulated timeline, the system can estimate all time factors during the movement and convert them to a baseline start time, thus obtaining a reconstructed start time. The reconstructed start time more accurately reflects the actual start-up requirements of the device, ensuring that the device can start immediately when the user reaches the target location.

[0061] Finally, when the refactoring startup time calculated by the system meets the conditions, the boot standard is considered satisfied. At this point, the system will trigger the laptop's pre-boot process to ensure the laptop is ready to use when the user needs it most. This method of dynamically adjusting the startup time based on user behavior and environmental conditions not only improves the user experience but also optimizes the laptop's power consumption management.

[0062] Furthermore, when the reconfiguration start time node is met, steps P41-344 in this embodiment of the application further include:

[0063] P41-3441: Activate the position sensor and establish verification position data; P41-3442: Use the verification position data to perform a startup verification judgment. If the startup verification judgment passes, it is determined that the power-on startup standard is met.

[0064] Optionally, when the reconstructed startup time node is met, a verification mechanism can be added to ensure that the laptop's boot-up standards are correctly met, while also taking into account the user's actual location information.

[0065] First, the position sensor is activated to obtain the device's current location and establish verification location data. The position sensor's role is to monitor the device's position changes in real time during movement, ensuring that the device has reached the predetermined target location. Location data not only verifies the device's movement process but also confirms whether the device has reached the location required for activation. For example, in an emergency, the device may need to be carried to a specific location to activate; the position sensor will provide accurate real-time feedback based on the device's current geographical location.

[0066] Next, the acquired verification location data is used to perform a startup verification check. The current location is compared with the preset target working location to determine whether the laptop has arrived at or is close to the area where the user needs to start working. If the current location matches the target location, or is within an acceptable error range, the system considers the startup verification check to be successful. If the startup verification check is successful, meaning the laptop's location matches the preset target working location, the system will ultimately determine that the boot-up criteria are met. This means the laptop will enter the pre-boot process, ready to be used immediately when the user arrives at the working area.

[0067] This process further enhances the device's intelligent startup function, ensuring that the device only starts after actually arriving at the designated location through location verification. This avoids accidental or premature startups in inappropriate locations, thus preventing energy waste. By combining time node and location data for dual verification, the device can be ensured to start at the appropriate time and location, improving task execution efficiency and success rate.

[0068] Furthermore, regarding the control of the laptop pre-boot, step P40 in this embodiment further includes:

[0069] P43: After the laptop pre-boots, execute the laptop's operation log and generate a false boot feedback database based on the operation log; P44: Optimize the control of the EC control chip based on the false boot feedback database.

[0070] Specifically, in addition to controlling the pre-boot of the laptop, it can also record the operation of the laptop after pre-boot, generate a false boot feedback database based on these records, and use the database to optimize the control of the EC control chip.

[0071] First, after the laptop pre-boots, the system begins logging the laptop's operations. This includes recording various user actions performed after booting, such as launching applications, accessing files, and changing system settings. These logs are used to analyze whether the pre-boot truly meets the user's needs and whether there have been any accidental boots. In this way, the system can collect actual data on the effectiveness of the pre-boot, providing a basis for subsequent optimizations.

[0072] Based on these operation records, the database is specifically used to store events identified as false starts—that is, instances where the laptop is started unnecessarily. By analyzing these false start events, the system can identify common causes and patterns leading to false starts, such as specific tension fluctuation patterns, inaccurate cadence configurations, or incorrect geolocation judgments.

[0073] Next, the control logic of the EC control chip is optimized using the false start feedback database. This includes adjusting the power-on startup criteria, improving the tensile force fluctuation analysis algorithm, and optimizing the position verification logic. For example, the accuracy and response speed of the startup process can be improved by adjusting the startup time window, optimizing the response parameters of the tensile force sensor, and adjusting the position verification mechanism. In this way, the system can gradually improve the device startup experience, ensuring that the device can start quickly and stably in different usage scenarios and reducing the probability of false starts.

[0074] Through these optimization steps, control strategies can be optimized by continuously recording operation data and using a feedback database, thereby improving the overall level of intelligence and enabling the equipment to maintain efficient and stable operation over long periods of use.

[0075] Furthermore, step P40 in this embodiment of the application also includes:

[0076] P43a: Initiate voice interaction and use the voice interaction to obtain software startup requirements; P44a: After the laptop pre-boots, control the software to run according to the software startup requirements.

[0077] In one possible embodiment of this application, in addition to conventional pre-start control and false start feedback optimization, voice interaction functionality can be introduced to further improve the intelligence of device startup and user experience. Specifically, the system includes the following two sub-steps:

[0078] First, the voice interaction function is activated immediately after the laptop device pre-boots. It receives the user's voice input through the built-in microphone and then uses speech recognition technology to convert the voice signal into text commands. This function allows users to directly control the device's startup process via voice commands. Especially in scenarios where direct device operation is not possible, voice interaction provides a more convenient and flexible control method. For example, a user might need to launch a specific application or open certain files; the system receives these requests through voice commands and responds accordingly.

[0079] Next, based on the software launch requests obtained from the voice interaction, the system controls the laptop's software operation. This process includes launching or scheduling the user-requested application, executing specific tasks, or performing corresponding software configurations. For example, if a user requests to launch a working application or run a specific script via voice command, the system will parse these commands and automatically execute the corresponding software launch operation. Voice interaction makes device operation more user-friendly, especially when users cannot manually operate the device; voice control provides an efficient and convenient alternative.

[0080] Through the steps described above, not only can the device be physically pre-started, but software and applications can also be intelligently launched based on the user's voice commands. This not only improves the device's response speed but also enhances the user's interactive experience, making it particularly suitable for special scenarios requiring rapid startup, such as tactical environments or emergency missions. Users can quickly control the device via voice commands, achieving an efficient workflow.

[0081] In summary, the embodiments of this application have at least the following technical effects:

[0082] This application uses a bidirectional tensile testing unit to intelligently sense the carrying status of the device and automatically determine whether the device needs to be started, thereby reducing manual intervention; it accurately senses the movement status of the device to avoid accidental start-up; it improves the accuracy and response speed of device start-up by periodically recording and analyzing tensile fluctuation datasets; and it optimizes the device start-up timing by judging the start-up criteria through the EC control chip, thereby improving the efficiency of device use.

[0083] This technology achieves the goal of enabling intelligent pre-start of equipment through tensile testing, reducing start-up delay, and improving the response speed of equipment in special environments.

[0084] Example 2 is based on the same inventive concept as the special notebook triggering method based on handle pull force detection in the previous example, such as... Figure 3 As shown, this application provides a special notebook computer triggering system based on handle pull force detection. The system and method embodiments in this application are based on the same inventive concept. The system includes:

[0085] The tensile testing unit deployment module 11 is used to deploy bidirectional tensile testing units inside the left and right handles of the laptop. The bidirectional tensile testing units include a left tensile testing unit and a right tensile testing unit.

[0086] The motion monitoring module 12 is used to start a motion monitoring command if the continuous sampling values ​​of the left tension detection unit or the right tension detection unit meet the static threshold within a preset sampling period.

[0087] The tension change fluctuation recording module 13 is used to configure N monitoring windows according to the motion monitoring command to record the periodic tension change fluctuation of the bidirectional tension detection unit and establish a tension fluctuation dataset.

[0088] The pre-start determination control module 14 is used to send the tensile fluctuation data set to the EC control chip. If the EC control chip determines that the power-on start-up standard is met, it controls the laptop to pre-start.

[0089] Furthermore, the pre-start determination and control module 14 is also used to perform the following steps:

[0090] Determine whether the tensile fluctuation dataset meets the stop pulling mode; if the tensile fluctuation dataset meets the stop pulling mode, the EC control chip determines that the power-on standard is not met and stops executing the laptop's startup command.

[0091] Furthermore, the pre-start determination and control module 14 is also used to perform the following steps:

[0092] If the tension fluctuation dataset does not meet the stop-pull mode, tension analysis is performed on the tension fluctuation data. The tension analysis includes comparing the tension change rate of the left and right tensions and analyzing the directional fluctuation of the independent tensions. A notebook motion status label is established based on the tension analysis results. The boot-up standard is judged and managed based on the notebook motion status label.

[0093] Furthermore, the pre-start determination and control module 14 is also used to perform the following steps:

[0094] If the tension fluctuation dataset does not meet the stop-pull mode, the position sensor is activated synchronously to obtain the current position information and read the preset target working position; the movement path is updated based on the current position information and the preset target working position; periodic fluctuation analysis is performed on the tension fluctuation dataset, and step frequency data is configured; the boot-up standard is judged and managed according to the laptop movement status label, the step frequency data, and the movement path.

[0095] Furthermore, the pre-start determination and control module 14 is also used to perform the following steps:

[0096] Configure a tolerance time window using the notebook motion status label; obtain the notebook's preset startup time, and establish a baseline startup time node based on the preset startup time and tolerance time window; perform motion simulation based on motion path and step frequency data, establish a simulation time axis, and reconstruct the startup time node after time conversion of the simulation time axis and the baseline startup time node; if the reconstructed startup time node is met, it is determined that the boot-up standard is met.

[0097] Furthermore, the pre-start determination and control module 14 is also used to perform the following steps:

[0098] Activate the position sensor and establish verification position data; use the verification position data to perform a startup verification judgment. If the startup verification judgment passes, it is determined that the power-on startup standard is met.

[0099] Furthermore, the pre-start determination and control module 14 is also used to perform the following steps:

[0100] Record data on the personnel carrying the equipment and establish user profiles; perform interactive authentication of the personnel carrying the equipment during the lifting process and establish the authentication results; configure step frequency data based on user profiles, authentication results, and periodic fluctuation analysis results.

[0101] Furthermore, the pre-start determination and control module 14 is also used to perform the following steps:

[0102] After the laptop pre-boots, the laptop's operation log is executed, and a false boot feedback database is generated based on the operation log; the control optimization of the EC control chip is performed based on the false boot feedback database.

[0103] Furthermore, the pre-start determination and control module 14 is also used to perform the following steps:

[0104] Initiate voice interaction to obtain software startup requirements; after the laptop pre-boots, control the software operation according to the software startup requirements.

[0105] Furthermore, the pre-start determination and control module 14 is also used to perform the following steps:

[0106] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0107] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0108] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. A special notebook computer triggering operation method based on handle pull force detection, characterized in that, The method includes: A bidirectional tension detection unit is deployed inside the left and right handles of the laptop, the bidirectional tension detection unit including a left tension detection unit and a right tension detection unit; If the continuous sampling values ​​of the left or right tension detection unit meet the static threshold within the preset sampling period, then the motion monitoring command is activated. According to the motion monitoring command, N monitoring windows are configured to record the periodic tension change fluctuations of the bidirectional tension detection unit, and a tension fluctuation dataset is established. The tensile fluctuation dataset is sent to the EC control chip. If the EC control chip determines that the boot-up criteria are met, it controls the laptop to pre-boot.

2. The special notebook triggering method based on handle pull force detection as described in claim 1, characterized in that, Sending the tensile fluctuation dataset to the EC control chip includes: Determine whether the tensile force fluctuation dataset meets the stop pulling mode; If the tensile fluctuation dataset meets the stop pulling mode, the EC control chip determines that the power-on standard is not met and stops executing the laptop's startup command.

3. A special notebook computer triggering method based on handle pull force detection as described in claim 2, characterized in that, The step of determining whether the tensile fluctuation dataset meets the stop-pull mode includes: If the tension fluctuation dataset does not meet the stop pulling mode, then tension analysis is performed on the tension fluctuation data. The tension analysis includes a comparison of the tension change rate of the left and right tensions and an analysis of the directional fluctuation of the independent tensions. Establish notebook motion status labels based on the tensile analysis results; The system determines and manages the boot-up criteria based on the laptop's motion status tags.

4. A special notebook computer triggering method based on handle pull force detection as described in claim 3, characterized in that, The judgment and management of the boot-up criteria based on the laptop's motion status tags includes: If the tension fluctuation dataset does not meet the stop pulling mode, the position sensor is activated synchronously to obtain the current position information and read the preset target working position; The movement path is updated based on the current location information and the preset target working position; Perform periodic fluctuation analysis on the tensile fluctuation dataset and configure step frequency data; The system determines and manages the boot-up criteria based on the laptop's motion status label, cadence data, and motion path.

5. A special notebook computer triggering method based on handle pull force detection as described in claim 4, characterized in that, The method for determining and managing the boot-up criteria based on the laptop's motion status label, cadence data, and motion path includes: Configure a tolerance time window using the aforementioned notebook motion status tags; Obtain the preset startup time of the laptop, and establish a baseline startup time node based on the preset startup time and the tolerance time window; Motion simulation is performed based on motion path and step frequency data. A simulation timeline is established. After time conversion of the simulation timeline and the baseline start time node, the start time node is reconstructed. If the reconstructed startup time node is met, then the boot-up standard is deemed to be met.

6. A special notebook computer triggering method based on handle pull force detection as described in claim 5, characterized in that, The startup time node that meets the reconstruction requirement includes: Activate the position sensor and establish verification position data; The startup verification is performed using the verification location data. If the startup verification passes, the system is deemed to meet the startup criteria.

7. A special notebook computer triggering method based on handle pull force detection as described in claim 4, characterized in that, The step frequency data configuration for performing periodic fluctuation analysis on the tensile fluctuation dataset includes: Record data on personnel carrying the equipment and create user profiles; During the lifting process, perform interactive authentication of the personnel carrying the equipment and establish the authentication result. Configure step frequency data based on user profiles, interaction authentication results, and periodic fluctuation analysis results.

8. A special notebook computer triggering method based on handle pull force detection as described in claim 1, characterized in that, The control of the laptop pre-boot includes: After the laptop pre-boots, the laptop's operation log is executed, and a false boot feedback database is generated based on the operation log. The control optimization of the EC control chip is performed based on the aforementioned false start feedback database.

9. A special notebook computer triggering method based on handle pull force detection as described in claim 1, characterized in that, The control of the laptop pre-boot also includes: Initiate voice interaction and use the voice interaction to obtain software startup requirements; After the laptop pre-boots, the software operation is controlled according to the software startup requirements.

10. A special notebook computer triggering system based on handle pull force detection, characterized in that, The system includes: A tensile testing unit deployment module is used to deploy bidirectional tensile testing units inside the left and right handles of a laptop. The bidirectional tensile testing unit includes a left tensile testing unit and a right tensile testing unit. The motion monitoring module is used to start a motion monitoring command if the continuous sampling values ​​of the left tension detection unit or the right tension detection unit meet the static threshold within a preset sampling period. The tension change fluctuation recording module is used to configure N monitoring windows according to the motion monitoring command to record the periodic tension change fluctuation of the bidirectional tension detection unit and establish a tension fluctuation dataset. The pre-start determination control module is used to send the tensile fluctuation data set to the EC control chip. If the EC control chip determines that the power-on start-up standard is met, it controls the laptop to pre-start.

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