AI intelligent computer self-help and optimization management chip

Abstract

The application discloses an AI intelligent computer self-rescue and optimization management chip, and relates to the technical field of computer system management and optimization chip, and comprises the following steps: a built-in host software and hardware independent running space of the chip guarantees the stable work of the computer; real-time acquisition of computer hardware parameters, prediction of faults and early warning by means of light-weight AI algorithm; positioning of the root cause of the fault according to the early warning, autonomous completion of system repair; support for offline triggering, repair of only system partition and reservation of user data; automatic adaptation of hardware and system, completion of driver installation, update and conflict repair; intelligent allocation of computer performance and power consumption by learning user habits; interception of system tampering and virus invasion from the bottom layer; automatic identification of peripherals and optimization and adaptation, and simplification of wiring layout. The application improves the reliability and operation and maintenance efficiency of the computer, guarantees the stable operation of the computer, reduces the maintenance cost and replacement frequency, and increases the experience of users.

Description

Technical Field

[0001] This invention relates to the field of computer system management and optimization chip technology, specifically to an AI-powered intelligent computer self-rescue and optimization management chip. Background Technology

[0002] Computers frequently experience system crashes, blue screens, freezes, virus intrusions, and inability to boot during daily use. Traditional repair methods heavily rely on manual operation and professional technicians, resulting in complex and costly repair processes that can easily lead to data loss. Traditional operating system or hard drive-based repair methods are no longer suitable for the new generation of computer architectures, and the market lacks hardware-level, AI-driven proactive self-rescue and intelligent optimization solutions.

[0003] Existing technologies suffer from the following problems: System restore and fault repair functions in current computers rely on the operating system or hard drive storage. Once the system is damaged, the hard drive fails, or the computer cannot boot, these functions become completely ineffective, lacking self-rescue capabilities in extreme scenarios. Traditional computer hardware monitoring and performance scheduling are reactive, lacking AI prediction and proactive protection capabilities, only able to remedy problems after they occur. Furthermore, ordinary users lack professional repair skills, making fault handling difficult and compromising data security. Existing solutions also cannot meet the future needs of integrated, closed-loop computers requiring repair without disassembly or external devices, resulting in low overall levels of intelligence, autonomy, and security, making them ill-suited for the use and maintenance needs of AI-era computers. Therefore, an AI-powered intelligent computer self-rescue and optimization management chip is urgently needed to address the problems of existing technologies. Summary of the Invention

[0004] To address the aforementioned technical issues, this invention provides an AI-powered intelligent computer self-rescue and optimization management chip, comprising a hardware structure consisting of independent firmware, an independent power supply unit, independent storage, and an independent computing unit. Independent operating module: Used during the computer's power-on self-test phase, it completes the underlying hardware initialization through the chip's built-in independent firmware, independent power supply unit, independent storage, and independent computing unit, building an independent operating space that does not depend on the host CPU, memory, and operating system; the independent power supply unit supports redundant power supply when the host power supply fails. Fault prediction and early warning module: In an independent operating space, the hardware status parameters of the computer system are collected in real time, and the probability of computer operation failure is analyzed through a lightweight AI algorithm. Based on the failure probability, a risk warning signal is generated. The lightweight AI algorithm is a fault prediction model based on time series analysis. Self-healing module: Used to autonomously identify the root cause of a fault based on risk warning signals during computer system operation, and then autonomously complete the repair based on the root cause of the fault. One-click restore module: Used to remotely trigger one-click restore via shortcut key or mobile APP when the computer is not in the operating system interface. It only repairs the system partition and does not modify the user data partition. Intelligent driver matching module: It is used to automatically identify the current computer's hardware model and system operating environment, intelligently match the optimal driver version from the chip's built-in driver library, and automatically complete driver installation, updates, and conflict repair; the chip supports offline driver library updates via local USB interface; Scheduling module: Used to learn user behavior characteristics through lightweight AI algorithms, automatically identify the current scenario type, and dynamically allocate performance and power consumption; Security protection module: Used to intercept and protect against system file tampering and virus intrusion. This interception and protection does not depend on the operating system. Peripheral Management Module: Used for automatic identification of peripheral hardware type and communication protocol, supporting unified configuration, intelligent adaptation and parameter optimization of wired and wireless peripherals, and simplifying interface and cable structure.

[0005] In a preferred embodiment, the specific process of generating a risk warning signal includes: The hardware status parameters of the computer system are collected in real time. These hardware status parameters include at least: CPU utilization, memory usage, hard disk read / write status, graphics card load, power supply status, and heat dissipation status. The hardware status parameters are input into a lightweight AI algorithm for analysis to obtain the hardware failure probability. The hardware failure probability is compared and analyzed with the preset hardware failure probability. If the hardware failure probability is greater than or equal to the preset hardware failure probability, a risk warning signal is generated.

[0006] In a preferred embodiment, after generating the risk warning signal, the method further includes triggering a corresponding protection operation, the specific process of which is as follows: The CPU is downclocked to a safe frequency threshold. Iterate through all running processes in the current system, identify processes whose CPU or memory usage exceeds a preset process usage threshold, mark them as abnormal processes, and forcibly terminate them. After the abnormal process terminates, the memory space is released. It automatically saves documents, code, design files, and unsaved data currently being edited on the computer, and performs temporary encrypted backups of the computer's core working data.

[0007] In a preferred embodiment, the process of autonomously completing the repair based on the root cause of the fault includes: Receive risk warning signals and extract abnormal hardware identification information from the risk warning signals; Based on the abnormal hardware identification information, collect the corresponding detailed operation logs and error codes, and construct the current fault feature description vector; The fault feature description vector is input into the chip's built-in fault root cause identification model to classify and identify the types of fault root causes. The root causes of the failures include corrupted system files, driver conflicts, abnormal boot partitions, memory leaks, process deadlocks, and hardware overheating. Based on the identified root cause type of the fault, a corresponding repair solution is matched from the chip's built-in repair strategy library; Based on the matching repair scheme, it performs autonomous repair.

[0008] In a preferred embodiment, after remotely triggering a one-click restore via a shortcut key or mobile app, the method further includes: Based on the received shortcut key trigger signal or the received restore command issued by the mobile APP, the chip's built-in simplified system image and USB flash drive-like boot repair logic are retrieved. The system fault is repaired by partitioning based on the simplified system image and USB-like boot repair logic.

[0009] In a preferred embodiment, the specific process of automatically completing driver installation, updates, and conflict resolution includes: Automatically read the model identification codes of each hardware device in the current computer. The model identification codes include at least: motherboard model, CPU model, graphics card model, sound card model, network card model, and peripheral device identification codes. Collect current system operating environment parameters, which include at least: operating system version, system bitness, and version number of currently installed drivers; Input the hardware model identification code and system operating environment parameters into the chip's built-in driver matching algorithm, and select the driver version with the highest compatibility score with the current hardware model and system environment from the chip's built-in driver library as the optimal driver version; Compare the currently installed driver version number with the matched optimal driver version number; If the current version is lower than the optimal version, the driver update operation will be performed automatically; If the corresponding driver is not currently installed, the driver installation process will be performed automatically. Extract the loading order and resource usage records of each driver, identify driver combinations that have resource contention or loading anomalies, and mark them as conflicting drivers; Based on the identified conflict drivers, driver conflict repair operations are automatically performed.

[0010] In a preferred embodiment, the specific process of dynamically allocating performance and power consumption includes: Collect user behavior data, which includes at least: CPU utilization curve, memory utilization curve, graphics card load curve, active application type, keyboard input frequency, mouse movement trajectory, click intensity, and user operation frequency. User behavior data is input into the chip's built-in AI scene recognition model and matched with built-in standard scene feature templates for similarity matching; The standard scene feature templates include at least: office scene, game scene, standby scene, and rendering scene; The scene feature template with the highest similarity is selected as the current scene type to be identified. Based on the identified scene type, the corresponding preset performance and power consumption allocation scheme is retrieved from the resource scheduling strategy library built into the chip. The preset performance and power consumption allocation scheme includes at least automatic frequency reduction, power saving, and heat reduction in office or standby scenarios; The system automatically maximizes performance and enhances heat dissipation in game or rendering scenarios to ensure smooth computer operation in all scenarios, balancing performance and power consumption.

[0011] In a preferred embodiment, the specific process for intercepting and protecting against system file tampering and virus intrusion includes: The hash values ​​of key system files are calculated in real time and compared one by one with the pre-fixed baseline hash values ​​in the chip's independent storage unit; The critical system files include at least: system boot file, system kernel file, driver files, and system registry file; If the current hash value of any critical file is found to be inconsistent with the base hash value, it is determined that the file has been tampered with, and the corresponding operation process is immediately suspended. Monitor and extract malicious behavior characteristics of the program, including at least: privilege escalation, auto-start, silent background installation, network connection, file encryption, memory injection, and modification of system configuration; The malicious behavior signature is matched with the malicious behavior signature database built into the chip to identify suspicious programs, Trojans, viruses and malicious scripts, and then intercept them. At the hardware level, write access to the storage medium by the abnormal process is cut off, and the interception record is written to the chip's independent log area.

[0012] In a preferred embodiment, a two-way connection is established with a mobile APP through an encrypted wireless communication channel to push the computer hardware health status, fault warning information, remote AI diagnostic hardware and system diagnostic results to the user terminal in real time, so as to realize remote full-scenario management.

[0013] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention integrates functions such as intelligent driver matching, computer self-healing, and remote control via mobile APP, encapsulating the complex underlying diagnostic process into automated logic. Ordinary users do not need to understand the technical principles behind the fault; they can simply click or perform a one-click operation to let the chip autonomously complete various tasks from driver conflict repair to system lag cleanup, thereby autonomously resolving approximately 98% of common computer software and configuration faults.

[0014] 2. This invention monitors minute parameters such as voltage, temperature, and read / write trends of hardware in real time within an independent space. Utilizing algorithms, it predicts crash risks, allowing the system to anticipate and eliminate potential faults before a blue screen or hardware failure occurs. This chip safeguards computer data security from the hardware level, automatically saving critical data such as unsaved documents, code, and design files before a failure. All repair and restore operations do not touch user data partitions, completely resolving data loss issues caused by system failures and greatly ensuring system continuity and data security.

[0015] 3. In extreme cases where the system is completely damaged and cannot be booted, the chip of this invention can still force the repair logic to start during the boot self-test stage by relying on the built-in simplified image and independent firmware, so as to achieve one-click restoration at the underlying level and ensure that the computer can be restored to a usable state under any software failure.

[0016] 4. This invention saves users expensive repair labor and parts costs, and extends the lifespan of computer hardware. This efficient and low-cost maintenance model not only alleviates the economic burden on users, but also transforms complex artificial intelligence technology into a practical and convenient tool, allowing every ordinary user to enjoy the safe and smooth experience brought by AI technology.

[0017] 5. This invention is compatible with traditional computer architectures and is also adapted to future integrated, closed-system new computers. Attached Figure Description

[0018] Figure 1 This is a schematic diagram showing the connection of the built-in module of the AI ​​intelligent computer self-rescue and optimization management chip in an embodiment of this application.

[0019] Explanation of reference numerals in the attached diagram: 1: Independent operation module; 2: Fault prediction and early warning module; 3: Self-healing module; 4: One-click restore module; 5: Intelligent driver matching module; 6: Scheduling module; 7: Security protection module; 8: Peripheral management module. Detailed Implementation

[0020] The subject matter described herein will now be discussed with reference to exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and implement the subject matter described herein, and changes may be made to the function and arrangement of the elements discussed without departing from the scope of this specification. Various processes or components may be omitted, substituted, or added as needed in the examples. Furthermore, features described in some examples may be combined in other examples.

[0021] It should be noted that, unless otherwise defined, the technical or scientific terms used in one or more embodiments of the present invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in one or more embodiments of the present invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0022] Example 1 Please see Figure 1 As shown in the figure, this application provides an AI intelligent computer self-rescue and optimization management chip, which includes a hardware structure consisting of independent firmware, an independent power supply unit, independent storage and an independent computing unit; Independent operating module: Used during the computer's power-on self-test phase, it completes the underlying hardware initialization through the chip's built-in independent firmware, independent power supply unit, independent storage, and independent computing unit, building an independent operating space that does not depend on the host CPU, memory, and operating system; the independent power supply unit supports redundant power supply when the host power supply fails. It should be noted that the independent operating module is the basic core hardware unit of this chip, with independent power supply, independent firmware, independent storage, and independent computing capabilities; it can power on and start up the moment the computer is powered on and the motherboard performs POST self-test, without waiting for host hardware initialization, loading of the operating system, or access to hard drive data; the independent power supply unit supports redundant power supply in case of host power failure; Its operating environment is physically isolated from the host system. Even if the host experiences extreme situations such as system crash, blue screen, black screen, inability to boot, hard drive damage, or CPU / memory failure, the module can still maintain stable operation and continuously perform functions such as fault monitoring, early warning, repair, restoration, and remote control.

[0023] Fault prediction and early warning module: In an independent operating space, the hardware status parameters of the computer system are collected in real time, and the probability of computer operation failure is analyzed through a lightweight AI algorithm. Based on the failure probability, a risk warning signal is generated. The lightweight AI algorithm is a fault prediction model based on time series analysis. The specific process of generating risk warning signals includes: The hardware status parameters of the computer system are collected in real time. These hardware status parameters include at least: CPU utilization, memory usage, hard disk read / write status, graphics card load, power supply status, and heat dissipation status. The hardware status parameters are input into a lightweight AI algorithm for analysis to obtain the hardware failure probability. The hardware failure probability is compared and analyzed with the preset hardware failure probability. If the hardware failure probability is greater than or equal to the preset hardware failure probability, a risk warning signal is generated. It should be noted that in its independent operating space, the chip can continuously monitor the operating status of various computer hardware components, unaffected by the computer's CPU, memory, and operating system. Even in extreme moments when the operating system crashes or experiences a blue screen due to driver conflicts or a system kernel crash, the chip can still maintain high-frequency sampling. Real-time collection of computer hardware status parameters helps to understand the current operating status and trends of the computer. At the same time, the analysis of lightweight AI algorithms can diagnose the computer's operating status in advance and identify potential fault risks. This predictive maintenance mechanism changes the traditional passive response maintenance model and moves the problem detection window from after the fault occurs to the bud stage of the fault. After generating the risk warning signal, the process also includes triggering the corresponding protection operation, the specific process of which is as follows: The CPU is downclocked to a safe frequency threshold. Iterate through all running processes in the current system, identify processes whose CPU or memory usage exceeds a preset process usage threshold, mark them as abnormal processes, and forcibly terminate them. After the abnormal process terminates, the memory space is released. It automatically saves documents, code, design files, and unsaved data currently being edited on the computer, and performs temporary encrypted backups of the computer's core working data.

[0024] It should be noted that underclocking the CPU can reduce CPU power consumption, heat generation and load stress, and prevent temperature spikes, power overload or system crashes caused by continuous high-frequency operation. By accurately locating and eliminating the culprits causing abnormal system load, the high-occupancy processes can be freed from monopolizing hardware resources, quickly relieving system pressure and eliminating lag and unresponsiveness. Forcibly terminating these uncontrolled abnormal processes can instantly break system logic deadlocks and restore the CPU's ability to schedule core tasks. Performing a memory release operation can reclaim memory blocks that have been occupied, left over, or not properly released by abnormal programs, repair memory leaks and resource deadlocks, restore the system to a clean and usable memory state, and prevent secondary crashes or restarts caused by memory exhaustion. When an early warning signal is issued, the critical data automatic saving function is immediately triggered, and the currently edited documents, code, design files and unsaved data on the computer are saved automatically and instantly; temporary encrypted backups of the computer's core working data are performed to avoid data loss or damage caused by sudden failures.

[0025] Self-healing module: Used to autonomously identify the root cause of a fault based on risk warning signals during computer system operation, and then autonomously complete the repair based on the root cause of the fault. Based on the root cause of the fault, the process of autonomously completing the repair includes: Receive risk warning signals and extract abnormal hardware identification information from the risk warning signals; Based on the abnormal hardware identification information, collect the corresponding detailed operation logs and error codes, and construct the current fault feature description vector; The fault feature description vector is input into the chip's built-in fault root cause identification model to classify and identify the types of fault root causes. The root causes of the failures include corrupted system files, driver conflicts, abnormal boot partitions, memory leaks, process deadlocks, and hardware overheating. Based on the identified root cause type of the fault, a corresponding repair solution is matched from the chip's built-in repair strategy library; Based on the matching repair scheme, it performs autonomous repair.

[0026] It should be noted that this module can complete fully automatic system repair without human intervention, enabling the computer to quickly return to a stable operating state; By automatically analyzing the content of risk warning signals, the hardware identification information of the abnormality is extracted, and it is clear which type of hardware / system is abnormal, such as CPU, memory, hard drive, graphics card, power supply or heat dissipation. This hardware identification information can provide a target for subsequent accurate fault location. Based on the abnormal hardware identification information, the corresponding detailed operation logs and error codes are collected. These multi-dimensional information are integrated and normalized to construct a standardized fault feature description vector, which serves as the input basis for identifying the root cause of the fault, ensuring that the judgment basis is complete and accurate. The chip has a built-in lightweight fault root cause identification model. After the constructed fault feature description vector is input into the model, the model will automatically classify and determine the fault type, accurately distinguishing which one or more combinations of the current fault belongs to system file corruption, driver conflict, boot partition abnormality, memory leak, process deadlock, and hardware overheating, thus realizing intelligent and automated determination of the root cause of the fault. The chip's independent storage unit contains a complete repair strategy library, which stores corresponding standardized and executable repair solutions for each type of root cause, such as system file corruption, driver conflicts, boot anomalies, memory leaks, process deadlocks, and hardware overheating. Based on the identified root cause type, the most suitable repair solution is quickly and accurately matched. The entire repair process can be completed automatically in the background without any user intervention, access to system settings, or external tools, allowing the computer to quickly return to normal operation.

[0027] One-click restore module: Used to remotely trigger one-click restore via shortcut key or mobile APP when the computer is not in the operating system interface. It only repairs the system partition and does not modify the user data partition. After triggering a one-click restore remotely via keyboard shortcuts or a mobile app, it also includes: Based on the received shortcut key trigger signal or the received restore command issued by the mobile APP, the chip's built-in simplified system image and USB flash drive-like boot repair logic are retrieved. The system fault is repaired by partitioning based on the simplified system image and USB-like boot repair logic.

[0028] In a preferred embodiment, the chip further includes: By establishing a two-way connection with a mobile APP through an encrypted wireless communication channel, the system can push the computer hardware health status, fault warning information, remote AI diagnostic hardware and system diagnostic results to the user terminal in real time, so as to realize remote full-scenario management.

[0029] It's important to note that the chip's built-in streamlined system image is like having a clean, basic operating system backup pre-stored within the chip (similar to a factory-installed Windows system file). This backup resides in the chip's own storage unit, not on the hard drive, so hard drive failure or system crashes won't affect it. In other words, if the system malfunctions before the computer enters the operating system interface (such as the computer failing to boot, black screen, blue screen, repeated restarts, or inability to access the desktop), the user can choose a one-click restore operation to repair the system partitions. The USB-like boot repair logic is just like when we repair a computer, we insert a USB boot disk to repair the system. This USB-like boot repair logic is just like that USB disk, except that it is directly integrated into the chip, so you don't need to find the USB disk or insert it. One-click restore applies to the operating system itself, which means repairing or resetting damaged system files, boot records, and system partitions to a normal state; however, the user's own files (photos, documents, software data, etc.) will not be deleted.

[0030] For a common example: If your computer suddenly crashes with a blue screen and you can't access the system, previously you could only find someone to repair it or reinstall the system (and lose all your data). With this chip, you can press a shortcut key (such as pressing F8 repeatedly during startup) or use a mobile app to tap "One-Click Restore." The chip will use a streamlined system image and USB-like boot repair logic to automatically repair the system. After restarting, you can access the desktop normally, and all your files will be intact. The goal is to repair the system without affecting your data.

[0031] It should be noted that targeted system partition restore and repair means that only the system disk partition where the computer's operating system is installed is restored by image, system file repair, boot item reconstruction and fault correction. The entire process does not read, modify, delete or overwrite user-stored photos, documents, videos, desktop files, downloaded materials, software data and other contents. All contents will remain in their original state and will not be lost or changed due to the restore operation.

[0032] Intelligent driver matching module: It is used to automatically identify the current computer's hardware model and system operating environment, intelligently match the optimal driver version from the chip's built-in driver library, and automatically complete driver installation, updates, and conflict repair; the chip supports offline driver library updates via local USB interface; The specific process of automatically completing driver installation, updates, and conflict resolution includes: Automatically read the model identification codes of each hardware device in the current computer. The model identification codes include at least: motherboard model, CPU model, graphics card model, sound card model, network card model, and peripheral device identification codes. Collect current system operating environment parameters, which include at least: operating system version, system bitness, and version number of currently installed drivers; Input the hardware model identification code and system operating environment parameters into the chip's built-in driver matching algorithm, and select the driver version with the highest compatibility score with the current hardware model and system environment from the chip's built-in driver library as the optimal driver version; Compare the currently installed driver version number with the matched optimal driver version number; If the current version is lower than the optimal version, the driver update operation will be performed automatically; If the corresponding driver is not currently installed, the driver installation process will be performed automatically. Extract the loading order and resource usage records of each driver, identify driver combinations that have resource contention or loading anomalies, and mark them as conflicting drivers; Based on the identified conflict drivers, automatically perform driver conflict repair operations; It should be noted that drivers act as "translators" between hardware and the operating system. Missing drivers, incompatible versions, or driver conflicts are common causes of computer blue screens, crashes, and peripheral malfunctions. This module automatically identifies, matches, installs, and resolves conflicts of drivers at the chip level, fundamentally eliminating system failures caused by driver problems without requiring users to manually download, install, or troubleshoot drivers. The chip's built-in driver library has a complete set of drivers covering mainstream hardware models pre-installed. It does not rely on network downloads and can complete driver matching and installation even when offline, ensuring normal operation in any network environment. It is automatically triggered during each computer power-on self-test and when a hardware access event occurs, enabling continuous maintenance and dynamic updates of the driver status, thus ensuring stable and compatible operation between computer hardware and the system from the underlying level.

[0033] Scheduling module: Used to learn user behavior characteristics through lightweight AI algorithms, automatically identify the current scenario type, and dynamically allocate performance and power consumption; The specific process of dynamically allocating performance and power consumption includes: Collect user behavior data, which includes at least: CPU utilization curve, memory utilization curve, graphics card load curve, active application type, keyboard input frequency, mouse movement trajectory, click intensity, and user operation frequency. User behavior data is input into the chip's built-in AI scene recognition model and matched with built-in standard scene feature templates for similarity matching; The standard scene feature templates include at least: office scene, game scene, standby scene, and rendering scene; The scene feature template with the highest similarity is selected as the current scene type to be identified. Based on the identified scene type, the corresponding preset performance and power consumption allocation scheme is retrieved from the resource scheduling strategy library built into the chip. The preset performance and power consumption allocation scheme includes at least automatic frequency reduction, power saving, and heat reduction in office or standby scenarios; The system automatically maximizes performance and enhances heat dissipation in game or rendering scenarios to ensure smooth computer operation in all scenarios, balancing performance and power consumption.

[0034] It should be noted that different usage scenarios have significantly different requirements for computer performance and power consumption. In office scenarios, users mainly run light-load tasks such as document editing and web browsing, which do not require full power operation. In this case, the scheduling module automatically reduces the CPU and graphics card frequencies to reduce power consumption and heat generation, thus extending the computer's lifespan. In gaming or rendering scenarios, users need high-performance output, so the scheduling module automatically increases the CPU and graphics card operating frequencies and increases the speed of the cooling module to ensure stable operation of the hardware under high load. In standby scenarios, the scheduling module switches each hardware module to the lowest power consumption state to minimize energy consumption. Traditional computers rely on passive response mechanisms at the operating system level for performance and power consumption scheduling, which only make adjustments after the load has changed, resulting in a lag in response. This module, by learning user habits in advance, can predict and prepare scheduling strategies before scene switching occurs, achieving proactive and predictive performance and power consumption management, effectively eliminating stuttering, overheating, and power waste caused by scheduling lag.

[0035] Security protection module: Used to intercept and protect against system file tampering and virus intrusion. This interception and protection does not depend on the operating system. The specific process of intercepting and protecting against system file tampering and virus intrusion includes: The hash values ​​of key system files are calculated in real time and compared one by one with the pre-fixed baseline hash values ​​in the chip's independent storage unit; The critical system files include at least: system boot file, system kernel file, driver files, and system registry file; If the current hash value of any critical file is found to be inconsistent with the base hash value, it is determined that the file has been tampered with, and the corresponding operation process is immediately suspended. Monitor and extract malicious behavior characteristics of the program, including at least: privilege escalation, auto-start, silent background installation, network connection, file encryption, memory injection, and modification of system configuration; The malicious behavior signature is matched with the malicious behavior signature database built into the chip to identify suspicious programs, Trojans, viruses and malicious scripts, and then intercept them. At the hardware level, write access to the storage medium by the abnormal process is cut off, and the interception record is written to the chip's independent log area.

[0036] It should be noted that traditional antivirus software runs at the operating system level, and its protection capabilities are limited by the operating system's own operating status. Once the operating system is hijacked by a virus or the system kernel is damaged, traditional antivirus software will also become ineffective and unable to provide effective protection. This module runs in an independent operating space on the chip, physically isolated from the operating system. Viruses cannot bypass or disable the protection of this module by infecting the operating system, thus fundamentally achieving a security protection capability that is superior to traditional system-level antivirus software. This module detects system file tampering based on a hash value comparison mechanism. Any unauthorized modification to critical files will cause a change in the hash value, thus being detected and blocked immediately.

[0037] Peripheral Management Module: Used for automatic identification of peripheral hardware type and communication protocol, supporting unified configuration, intelligent adaptation and parameter optimization of wired and wireless peripherals, and simplifying interface and cable structure; It should be noted that when connecting new peripherals to a traditional computer, users usually need to manually install drivers, manually configure parameters, and even restart the computer to complete the peripheral recognition. For ordinary users, problems such as driver installation failure, peripheral device inability to be recognized, and interface incompatibility occur frequently, resulting in a poor user experience. This module automatically identifies, adapts, and optimizes parameters of peripherals at the chip level, without requiring manual intervention from the user, thus achieving a convenient plug-and-play peripheral management experience. This module supports unified management of wireless peripherals. By centralizing the connection and configuration of multiple wireless peripherals under the unified scheduling of the chip, the host's dependence on multiple wireless receivers is reduced, interface occupation and cable structure are simplified, and desktop cleanliness and ease of use are improved. This module runs in the chip's independent operating space and does not rely on the operating system's device management services. Even if the operating system malfunctions, the peripheral management module can continue to work, ensuring that peripherals can be recognized and used normally under any system state. After the peripheral identification, adaptation and parameter optimization operations are completed, the chip records the type of peripheral connected this time, the matching configuration scheme, the parameter initialization results and communication status to an independent log area, and pushes the peripheral management status to the mobile APP user terminal in real time through the remote control module, thus completing the complete processing loop of this peripheral intelligent management.

[0038] For example, detecting peripheral device access events and automatically reading the device identification code and communication protocol type of the peripheral hardware; the peripheral hardware includes at least: keyboard, mouse, monitor, printer, camera, audio device, mobile storage device and wireless peripheral; the communication protocol type includes at least: USB protocol, Bluetooth protocol, wireless radio frequency protocol and audio protocol; The read device identification code and communication protocol type are input into the chip's built-in peripheral adaptation algorithm, which then matches the optimal configuration scheme corresponding to the current peripheral hardware model and communication protocol from the chip's built-in adaptation rule base. According to the optimal configuration scheme, the peripheral parameter initialization operation is automatically completed. The parameter initialization content includes at least: communication baud rate configuration, data transmission bandwidth allocation, device response latency optimization, and power supply allocation. The system provides unified management of multiple connected peripherals and automatically detects whether there are communication protocol conflicts or resource contention between them. If a conflict is detected, the system automatically adjusts the resource allocation strategy according to the peripheral priority rules to eliminate the conflict. It supports unified management of both wired and wireless connection methods. For peripherals that support wireless connection, it automatically completes wireless pairing and channel allocation, simplifying manual pairing operations for users and reducing unnecessary interface occupation and cable connections. During the operation of peripherals, the communication status and response latency of each peripheral are continuously monitored. If a communication abnormality or response timeout is detected in a peripheral, the adaptation initialization process is automatically re-executed to restore the peripheral to normal working status. If the current peripheral model is detected to be outside the coverage of the chip's built-in adaptation rule library during the adaptation process, it will automatically downgrade to the general compatibility mode and complete the basic function adaptation according to the standard communication protocol to ensure that the basic functions of the peripheral are used normally.

[0039] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0040] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. AI intelligent computer self-rescue and optimization management chip, characterized in that, include: The hardware structure consists of independent firmware, independent power supply unit, independent storage and independent computing unit; Independent operating module: Used during the computer's power-on self-test phase, it completes the underlying hardware initialization through the chip's built-in independent firmware, independent power supply unit, independent storage, and independent computing unit, building an independent operating space that does not depend on the host CPU, memory, and operating system; the independent power supply unit supports redundant power supply when the host power supply fails. Fault prediction and early warning module: In an independent operating space, the hardware status parameters of the computer system are collected in real time, and the probability of computer operation failure is analyzed through a lightweight AI algorithm. Based on the failure probability, a risk warning signal is generated. The lightweight AI algorithm is a fault prediction model based on time series analysis. Self-healing module: Used to autonomously identify the root cause of a fault based on risk warning signals during computer system operation, and then autonomously complete the repair based on the root cause of the fault. One-click restore module: Used to remotely trigger one-click restore via shortcut key or mobile APP when the computer is not in the operating system interface. It only repairs the system partition and does not modify the user data partition. Intelligent driver matching module: It is used to automatically identify the current computer's hardware model and system operating environment, intelligently match the optimal driver version from the chip's built-in driver library, and automatically complete driver installation, updates, and conflict repair; the chip supports offline driver library updates via local USB interface; Scheduling module: Used to learn user behavior characteristics through lightweight AI algorithms, automatically identify the current scenario type, and dynamically allocate performance and power consumption; Security protection module: Used to intercept and protect against system file tampering and virus intrusion. This interception and protection does not depend on the operating system. Peripheral Management Module: Used for automatic identification of peripheral hardware type and communication protocol, supporting unified configuration, intelligent adaptation and parameter optimization of wired and wireless peripherals, and simplifying interface and cable structure.

2. The AI intelligent computer self-rescue and optimization management chip of claim 1, wherein, The specific process of generating risk warning signals includes: The hardware status parameters of the computer system are collected in real time. These hardware status parameters include at least: CPU utilization, memory usage, hard disk read / write status, graphics card load, power supply status, and heat dissipation status. The hardware status parameters are input into a lightweight AI algorithm for analysis to obtain the hardware failure probability. The hardware failure probability is compared and analyzed with the preset hardware failure probability. If the hardware failure probability is greater than or equal to the preset hardware failure probability, a risk warning signal is generated.

3. The AI intelligent computer self-rescue and optimization management chip of claim 1, wherein, After generating the risk warning signal, the process also includes triggering the corresponding protection operation, the specific process of which is as follows: The CPU is downclocked to a safe frequency threshold. Iterate through all running processes in the current system, identify processes whose CPU or memory usage exceeds a preset process usage threshold, mark them as abnormal processes, and forcibly terminate them. After the abnormal process terminates, the memory space is released. It automatically saves documents, code, design files, and unsaved data currently being edited on the computer, and performs temporary encrypted backups of the computer's core working data.

4. The AI intelligent computer self-rescue and optimization management chip of claim 1, wherein, Based on the root cause of the fault, the process of autonomously completing the repair includes: Receive risk warning signals and extract abnormal hardware identification information from the risk warning signals; Based on the abnormal hardware identification information, collect the corresponding detailed operation logs and error codes, and construct the current fault feature description vector; The fault feature description vector is input into the chip's built-in fault root cause identification model to classify and identify the types of fault root causes. The root causes of the failures include corrupted system files, driver conflicts, abnormal boot partitions, memory leaks, process deadlocks, and hardware overheating. Based on the identified root cause type of the fault, a corresponding repair solution is matched from the chip's built-in repair strategy library; Based on the matching repair scheme, it performs autonomous repair.

5. The AI intelligent computer self-rescue and optimization management chip of claim 1, wherein, After triggering a one-click restore remotely via keyboard shortcuts or a mobile app, it also includes: Based on the received shortcut key trigger signal or the received restore command issued by the mobile APP, the chip's built-in simplified system image and USB flash drive-like boot repair logic are retrieved. The system fault is repaired by partitioning based on the simplified system image and USB-like boot repair logic.

6. The AI intelligent computer self-rescue and optimization management chip of claim 1, wherein, The specific process of automatically completing driver installation, updates, and conflict resolution includes: Automatically read the model identification codes of each hardware device in the current computer. The model identification codes include at least: motherboard model, CPU model, graphics card model, sound card model, network card model, and peripheral device identification codes. Collect current system operating environment parameters, which include at least: operating system version, system bitness, and version number of currently installed drivers; Input the hardware model identification code and system operating environment parameters into the chip's built-in driver matching algorithm, and select the driver version with the highest compatibility score with the current hardware model and system environment from the chip's built-in driver library as the optimal driver version; Compare the currently installed driver version number with the matched optimal driver version number; If the current version is lower than the optimal version, the driver update operation will be performed automatically; If the corresponding driver is not currently installed, the driver installation process will be performed automatically. Extract the loading order and resource usage records of each driver, identify driver combinations that have resource contention or loading anomalies, and mark them as conflicting drivers; Based on the identified conflict drivers, driver conflict repair operations are automatically performed.

7. The AI intelligent computer self-rescue and optimization management chip of claim 1, wherein, The specific process of dynamically allocating performance and power consumption includes: Collect user behavior data, which includes at least: CPU utilization curve, memory utilization curve, graphics card load curve, active application type, keyboard input frequency, mouse movement trajectory, click intensity, and user operation frequency. User behavior data is input into the chip's built-in AI scene recognition model and matched with built-in standard scene feature templates for similarity matching; The standard scene feature templates include at least: office scene, game scene, standby scene, and rendering scene; The scene feature template with the highest similarity is selected as the current scene type to be identified. Based on the identified scene type, the corresponding preset performance and power consumption allocation scheme is retrieved from the resource scheduling strategy library built into the chip. The preset performance and power consumption allocation scheme includes at least automatic frequency reduction, power saving, and heat reduction in office or standby scenarios; The system automatically maximizes performance and enhances heat dissipation in game or rendering scenarios to ensure smooth computer operation in all scenarios, balancing performance and power consumption.

8. The AI ​​intelligent computer self-rescue and optimization management chip according to claim 1, characterized in that, The specific process of intercepting and protecting against system file tampering and virus intrusion includes: The hash values ​​of key system files are calculated in real time and compared one by one with the pre-fixed baseline hash values ​​in the chip's independent storage unit; The critical system files include at least: system boot file, system kernel file, driver files, and system registry file; If the current hash value of any critical file is found to be inconsistent with the base hash value, it is determined that the file has been tampered with, and the corresponding operation process is immediately suspended. Monitor and extract malicious behavior characteristics of the program, including at least: privilege escalation, auto-start, silent background installation, network connection, file encryption, memory injection, and modification of system configuration; The malicious behavior signature is matched with the malicious behavior signature database built into the chip to identify suspicious programs, Trojans, viruses and malicious scripts, and then intercept them. At the hardware level, write access to the storage medium by the abnormal process is cut off, and the interception record is written to the chip's independent log area.

9. The AI intelligent computer self-rescue and optimization management chip of claim 1, wherein, The chip also includes: By establishing a two-way connection with a mobile APP through an encrypted wireless communication channel, the system can push the computer hardware health status, fault warning information, remote AI diagnostic hardware and system diagnostic results to the user terminal in real time, so as to realize remote full-scenario management.

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