A software installation method based on hardware configuration and installation device thereof

Abstract

The application provides a software installation method based on hardware configuration and an installation device thereof, which comprises the following steps: collecting hardware information and software running information of a terminal device; uploading the hardware information and the software running information to a server; analyzing and generating resource consumption comprehensive data of software on different types of terminal devices based on the hardware information and the software running information uploaded by multiple terminal devices through the server; and generating an installation suggestion and prompting the user based on the resource consumption comprehensive data and the running information of the current terminal device when installing target software on the terminal device. The application obtains relatively accurate running consumption of various types of software of a specified device type through terminal comprehensive running data analysis, accurately recommends device configuration information required by the user, and guides whether to upgrade the terminal device.

Description

Technical Field

[0001] This invention relates to the field of computer software installation and hardware resource management technology, and in particular to a software installation method, apparatus, device and storage medium based on big data analysis and hardware configuration. Background Technology

[0002] In the current software distribution and installation ecosystem, software providers typically offer a "system requirements" list when releasing software. This list usually includes minimum and recommended system requirements. For example, a software might require Windows 10 or later, a CPU with a clock speed of at least 2.0 GHz, at least 4 GB of RAM, and at least 2 GB of available hard disk space.

[0003] However, this static and universal system requirement has significant limitations and cannot meet the complex and ever-changing real-world usage environments, mainly in the following aspects:

[0004] First, the information is coarse-grained and lacks specificity: "Minimum configuration" or "recommended configuration" is usually based on idealized or standardized test environments and does not consider the impact of performance differences between different hardware models (such as different generations of CPUs, different types of hard drives (HDD vs. SSD)) on the actual resource consumption of the software. For example, the loading speed and disk I / O consumption of the same software on a device equipped with a solid-state drive (SSD) may be vastly different from those on a device equipped with a hard disk drive (HDD), but traditional system requirements do not differentiate between them.

[0005] Second: Ignoring the device's current operating status: Traditional methods only consider whether the device's static hardware specifications meet the minimum requirements of the software, completely ignoring the device's current dynamic load. This is the most fatal flaw of existing technology. For example, a computer with 8GB of RAM, from a static hardware perspective, fully meets the requirements of software that requires "4GB of RAM." However, if the computer is already running multiple memory-intensive applications (such as browsers, IDEs, virtual machines, etc.), its available memory may only be 500MB. Forcing the installation and running of the new software under these circumstances could very likely lead to system lag, software crashes, or even a blue screen. Existing technology cannot predict or warn of this risk.

[0006] Third: Inability to provide personalized suggestions: Existing technology can only provide a binary "yes" or "no" judgment—that is, whether the device hardware meets the minimum requirements. Existing technology cannot tell users, "After installing this software, your memory usage is expected to reach 95%, and the system may run very slowly," nor can it provide constructive suggestions, such as "It is recommended that you close other unnecessary applications before installation" or "For a smooth experience, it is recommended that you upgrade your memory to 16GB."

[0007] In other words, current technologies generally determine whether software can be installed on a terminal device based on the system and hardware configuration requirements at the time of its release. However, this method is not ideal and lacks comprehensive information on the operational status, mainly in the following two aspects: First, it generally only provides the minimum system requirements; second, it cannot provide the most reasonable suggestions based on the user's habits and the working status of commonly used software on the terminal. For example, an employee's computer needs to run multiple software programs daily, consuming a lot of resources. Therefore, whether certain new software can meet the installation or usage requirements cannot be determined simply from the minimum system requirements. Furthermore, if a certain software requires 1GB of memory, but the user's computer already has insufficient memory after running commonly used software, even though the minimum system configuration is 4GB and the hardware configuration meets the requirements, the solution may be to use the software.

[0008] In summary, the present invention addresses the problem that existing technologies cannot provide users with installation suggestions based on detailed terminal operating data or actual working status. Summary of the Invention

[0009] The technical problem that the invention aims to solve

[0010] The primary objective of this invention is to overcome the aforementioned deficiencies of the prior art and provide a software installation method and apparatus based on hardware configuration, which can accurately analyze comprehensive data from equipment, software, and users' daily office work, making it easier for users to obtain more comprehensive operating data, software installation suggestions, and equipment configuration suggestions.

[0011] Another objective of this invention is to establish a resource consumption profile for software under different hardware configurations by aggregating and analyzing operational data from a large number of terminal devices, thereby enabling accurate prediction of software resource consumption on specific models of devices.

[0012] Another objective of this invention is to generate and present intelligent installation suggestions, including estimated resource consumption and device upgrade recommendations, based on the aforementioned accurate predictions and the real-time operating status of the user's device, before the user performs the software installation operation, thereby helping the user make informed decisions and avoiding performance problems after installation.

[0013] Technical means for solving problems

[0014] To achieve the above objectives, the present invention provides a software installation method based on hardware configuration, comprising:

[0015] Collect hardware and software operation information of terminal devices;

[0016] Upload the hardware information and the software operation information to the server;

[0017] The server analyzes and generates comprehensive data on the resource consumption of the software on different types of terminal devices based on the hardware information and software operation information uploaded by multiple terminal devices.

[0018] When the target software is installed on the terminal device, an installation suggestion is generated and prompted to the user based on the comprehensive data of resource consumption and the current operating information of the terminal device.

[0019] Therefore, based on the hardware and software operation data of massive amounts of terminal devices in the real world, it can accurately predict the resource consumption of software on specific device models, overcoming the limitations of static system requirements. This helps users make informed installation decisions, improves user experience and system stability, and is especially suitable for enterprise IT management and individual users.

[0020] In the above-described hardware-based software installation method, preferably, anonymization processing is included before uploading the hardware information and the software operation information to the server. This anonymization processing involves anonymizing the data received by the server to protect user privacy.

[0021] Therefore, by anonymizing data, such as removing sensitive information like usernames and personal files, the privacy and security of user data during the uploading and analysis process are ensured, complying with relevant laws and regulations. While protecting individual privacy, data can still be effectively aggregated for global analysis, enhancing user trust and system compliance.

[0022] In the above-mentioned software installation method based on hardware configuration, preferably, the step of analyzing and generating comprehensive resource consumption data of the software on different types of terminal devices includes: classifying the data uploaded to the server; performing statistical analysis on the classified data; and generating comprehensive resource consumption data through a generation model.

[0023] Therefore, through a systematic data analysis process—classification, aggregation, and modeling—the accuracy and reliability of comprehensive resource consumption data are ensured, creating resource consumption profiles for the software across different devices. It supports big data processing and machine learning optimization, enabling the model to improve itself as the amount of data increases, thereby enhancing prediction accuracy and adaptability.

[0024] In the above-described hardware-configuration-based software installation method, preferably, when installing the target software on the terminal device, generating installation suggestions and prompting the user based on the comprehensive resource consumption data and the current operating information of the terminal device includes:

[0025] The client is triggered when a user installs target software on their terminal device;

[0026] The client collects and calculates the current operating information of the terminal device in real time.

[0027] The client sends a request to the server to obtain comprehensive data on the resource consumption of the target software;

[0028] The acquired local running status is compared and calculated with the acquired comprehensive data on software resource consumption to check whether the remaining disk space is greater than the space occupied by the software; and

[0029] Based on the comparison results, installation suggestions are generated.

[0030] Therefore, providing specific resource consumption metrics makes installation recommendations more detailed and quantifiable, helping users intuitively understand the software's impact on device performance. This facilitates optimization by IT departments or users targeting specific resource bottlenecks, such as upgrading memory or replacing hard drives, improving decision-making efficiency.

[0031] In the above-described hardware-configuration-based software installation method, preferably, when installing the target software on the terminal device, generating installation suggestions and prompting the user based on the comprehensive resource consumption data and the current operating information of the terminal device further includes:

[0032] The generated installation suggestions are clearly presented to the user through the user interface.

[0033] Therefore, users can not only understand whether the installation is possible, but also learn about the specific resource usage after installation and suggestions for improvement. In addition, actionable guidance is provided to help users prevent performance issues, optimize device configuration, and reduce total cost of ownership.

[0034] In the above-described hardware-configuration-based software installation method, preferably, the generated installation suggestions include estimated resource consumption, equipment upgrade suggestions, and immediate operation suggestions.

[0035] This enables automated data collection, analysis, and suggestion generation, reducing manual intervention, improving efficiency, and making it suitable for large-scale terminal environments.

[0036] In the above-described hardware-based software installation method, preferably, the acquisition module is specifically used to acquire at least one of the following as hardware information: device model, CPU model, memory size, and disk type; the acquisition module is specifically used to acquire at least one of the following as software operation information: application software list, CPU consumption, memory consumption, and disk I / O consumption.

[0037] This ensures the collection of key hardware identifiers and performance benchmark data, providing an accurate foundation for resource consumption analysis and enhancing the correlation between the model and equipment type. Furthermore, it supports distinguishing performance differences between different hardware combinations, improving the relevance and accuracy of recommendations.

[0038] The present invention also provides a software installation device based on hardware configuration, comprising:

[0039] The acquisition module is used to acquire hardware information and software operation information of the terminal device;

[0040] An upload module is used to upload the hardware information and software operation information to the server.

[0041] The analysis module is used to analyze and generate comprehensive data on the resource consumption of the software on different types of terminal devices based on the hardware information and software operation information uploaded by multiple terminal devices.

[0042] The prompting module is used to generate installation suggestions and prompt the user based on the comprehensive resource consumption data and the current operating information of the terminal device when installing target software on the terminal device.

[0043] Therefore, the above method is implemented in the form of a device, and the modular design facilitates integration and deployment, improving system maintainability and scalability.

[0044] The present invention also provides a computer-readable medium having a computer program stored thereon, characterized in that the program, when executed by a processor, implements any of the methods described above.

[0045] This enables the method to be widely deployed and disseminated in software form, compatible with different terminal devices and operating systems, reducing implementation costs. It provides flexible implementation options, supports updates and optimizations, and ensures the method can be continuously improved and adapted to new technologies.

[0046] The present invention also provides an electronic device based on a software installation method for hardware configuration, comprising:

[0047] One or more processors; and

[0048] Storage device for storing one or more programs.

[0049] The one or more programs are executed by the one or more processors, causing the one or more processors to implement any of the methods described above.

[0050] Therefore, a hardware platform is provided to automate the execution of methods, enabling efficient data processing and user interaction, suitable for scenarios such as personal computers and servers. This enhances the system's usability and accessibility, allowing users to benefit from intelligent installation suggestions without additional configuration.

[0051] Invention Effects

[0052] In summary, one or more embodiments of the above invention have the following advantages or beneficial effects:

[0053] The present invention discloses a software installation method and device based on hardware configuration. By analyzing the comprehensive operation data of the terminal, it obtains relatively accurate software operation consumption of a specified device type, accurately recommends the device configuration information required by the user, and guides the user to upgrade the terminal device.

[0054] The further effects of the aforementioned unconventional alternative methods will be explained below in conjunction with specific implementation methods. Attached Figure Description

[0055] The accompanying drawings are provided to better understand the invention and are not intended to unduly limit the scope of the invention. Wherein:

[0056] Figure 1 This is a flowchart of the hardware configuration-based software installation method of the present invention;

[0057] Figure 2 This is a flowchart illustrating the hardware configuration-based software installation method of the present invention.

[0058] Figure 3 This is a block diagram of a software installation device based on hardware configuration according to the present invention;

[0059] Figure 4 This is an exemplary system architecture diagram of a software installation method or installation device based on hardware configuration that applies embodiments of the present invention;

[0060] Figure 5 This is a schematic diagram of the structure of a computer system suitable for implementing the terminal device of the present invention. Detailed Implementation

[0061] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention, including various details to aid understanding. These details should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0062] First, refer to Figures 1-2 The software installation method based on hardware configuration in this embodiment will be described. Figure 1 This is a flowchart of the software installation method based on hardware configuration of the present invention; Figure 2 This is a flowchart illustrating the hardware configuration-based software installation method of the present invention.

[0063] This invention provides a software installation method based on hardware configuration. This method can provide installation suggestions to the user based on detailed operating data or the actual working status of the terminal. See also... Figure 1The flowchart of the method of the present invention shown below illustrates the following technical solution: the method includes the following steps:

[0064] Step S101: Collect information about the terminal device, including the device model, hardware information, and all software operating information of the current terminal device. This is the foundational stage of data collection and is typically performed by a lightweight client program (or "agent") deployed on the terminal device (such as a personal computer or corporate office computer). The collection process can be periodic, event-triggered (e.g., before software installation), or run continuously in the background.

[0065] Taking enterprise-level terminal devices as an example, but not limited to enterprise-level terminal devices, personal terminal devices are also supported. First, install a local performance monitoring software client. At this time, the client will collect the software working status of the terminal device, such as the resources consumed by the software. Second, the client will also collect the hardware information of the terminal device, such as the system model, operating system, and configuration information.

[0066] The aforementioned hardware information aims to obtain the device's static identity and performance benchmarks, and includes at least one or more of the following:

[0067] Device Model: For example, "Lenovo ThinkPad L14 Gen 2" or "Dell Latitude 5420". The device model is a key identifier associated with a specific hardware combination and performance characteristics. Memory Model: For example, "DDR4 3200MHz". Memory temporarily stores data processed by the CPU and directly affects system speed. Hard Drive Model: HDD (Hard Disk Drive): Such as Seagate Barracuda 2TB, inexpensive but slower (approximately 100MB / s), suitable for large-capacity storage. SSD (Solid State Drive): Such as Samsung 980Pro 1TB, for long-term storage of the operating system and files; SSDs are faster and more reliable than HDDs. Motherboard Model: For example, ASUS TUF Gaming X570-Plus, compact design, suitable for small to medium-sized cases, with 3-4 expansion slots. The motherboard connects all hardware, is responsible for data transmission and signal control, and determines system compatibility. CPU Model: For example, "Intel Core i5-1135G7 @2.40GHz". The CPU model determines the processor's architecture, number of cores, clock speed, and instruction set performance. Memory size: For example, "16GB DDR4 3200MHz". Total memory capacity is key to determining whether memory-intensive applications can run. Disk type: For example, "NVMe SSD", "SATA SSD", or "HDD". Disk type greatly affects system I / O throughput and software loading speed.

[0068] The software operation information mentioned above aims to obtain the current dynamic resource load of the device. The resources consumed by the software include at least one or more of the following: A list of application software, representing the executable file names or process identifiers of all currently running applications. CPU consumption: This can refer to the CPU utilization of a single process or the overall CPU utilization of the entire system. It is usually expressed as a percentage. Memory consumption: This refers to the amount of physical memory (RAM) occupied by the software process, usually measured in MB or GB. Virtual memory usage may also be included. Disk I / O consumption: This refers to the rate at which the software process performs disk read / write operations, such as read / write operations per second (IOPS) or data transfer rate (MB / s).

[0069] Step S102: Upload hardware and software operation information to the server. Specifically, the client uploads the collected information to the server via a secure network connection (such as HTTPS) to a centralized server. This step may also include an anonymization process, whereby the data is anonymized during upload to protect user privacy, such as removing sensitive information like usernames and personal files, retaining only hardware and software operation data relevant to performance analysis.

[0070] Step S103: Perform comprehensive analysis on the information uploaded by each terminal device and generate comprehensive analysis data. Specifically, perform statistical calculations on the information uploaded by each terminal device, calculate the average value, generate statistical data, and examine the software's operating status on these types of devices based on the statistical data. For example, memory consumption, CPU utilization, and disk I / O consumption are important reference data. In this way, by using the hardware information and software operating information uploaded by multiple terminal devices, the server can analyze and generate comprehensive resource consumption data for the software on different types of terminal devices. For example, on an L14 type device, the QQ software consumes approximately 500MB of memory. On a T14 type device, the JingME software consumes approximately 1GB of memory.

[0071] It should be noted that this step is the brain and core of this invention, essentially a big data analysis and modeling process. The server aggregates massive amounts of data from tens of thousands of terminal devices. Through data cleaning, classification, aggregation, and machine learning algorithms, a resource consumption model is built for each software on different types of devices. This software is identified by its executable file or digital signature. The specific data analysis process includes the following steps:

[0072] Data classification steps: The server first classifies the uploaded data according to the "device model" and "software identifier". For example, all running data related to the "QQ" software from the "Lenovo L14" device is grouped together.

[0073] Aggregation calculation step: Perform statistical analysis on the categorized data. This statistical analysis can be an average analysis of the above-mentioned multiple indicators. For example, calculate the average memory consumption of the "QQ" software on the "Lenovo L14" device, the 95th percentile of CPU utilization, and peak disk I / O, etc.

[0074] Model generation steps: The final result is comprehensive resource consumption data. This data can be a lookup table or a database; for example, core content includes, but is not limited to:

[0075] The typical memory consumption of "Software A" on "Device Model X" is Y1 MB.

[0076] The typical CPU consumption (average / peak) of "Software A" on "Device Model X" is Y2.

[0077] The typical disk I / O consumption (average read / write speed) of "Software A" on "Device Model X" is Y3 MB / s.

[0078] The model generation steps described above may also include an optimization and update step: since the model is dynamically updated, this optimization and update step continuously improves its accuracy as more data is incorporated.

[0079] Step S104: When the target software is installed on the terminal device, an installation suggestion is generated and prompted to the user based on the comprehensive resource consumption data and the current operating information of the terminal device. In other words, when the user downloads the software through an enterprise software library or other channels, the client of the invention device will prompt the user with the basic configuration information required for the software to work on the target terminal. This basic configuration information is an average indicator, generally a comprehensive view, including the CPU usage, memory consumption, and disk I / O consumption of the main applications used.

[0080] Specifically, this step is the value realization phase, applying the server's global knowledge to a single user's specific scenario. This step includes the following sub-steps:

[0081] Triggering Installation Suggestion Steps: When the client detects that a user has launched an installer for the "target software" on their terminal device, whether through an enterprise software repository, a web download, or other channels, it captures this installation intent and activates the suggestion generation module. In other words, the client is triggered when a user attempts to install "target software" on their terminal device (e.g., by clicking install from an enterprise software repository).

[0082] Steps to obtain local running status: The client collects and calculates the current running information of the terminal device in real time. This running information typically includes: current CPU utilization, current available memory space, current disk I / O activity and remaining storage space, network status, currently running heavily loaded processes, etc.

[0083] The step of retrieving and matching resource consumption data is as follows: The client sends a request to the server to obtain comprehensive resource consumption data for the target software, i.e., pre-analyzed average metrics. This data mainly includes: average CPU utilization during software operation, average memory consumption during software operation, average disk I / O consumption during software operation, and the possible average storage space usage. In this step, the client first identifies the device model of the current device and queries the server for pre-calculated comprehensive resource consumption data for "the target software" on "this device model," for example, estimating that it will consume 500MB of memory.

[0084] Comparison, analysis, and evaluation steps: Compare and calculate the local running status obtained in the above steps with the comprehensive data on software resource consumption to check whether the remaining disk space is significantly greater than the space occupied by the software. Example of evaluation logic:

[0085] If (current available memory - average software memory consumption) < safety threshold, then the assessment is "memory may be insufficient".

[0086] If (current CPU idle rate - software average CPU utilization) < safety threshold, then it is assessed as "may cause system lag".

[0087] Personalized installation suggestion generation steps: Based on the above comparison results, generate specific and easy-to-understand natural language suggestions, rather than listing raw data. For example, suggestion types: Green light suggestion (good conditions): "Your device currently has sufficient resources to run this software smoothly. Installation is recommended." Yellow light suggestion (risk exists): "Tip: This software typically requires a lot of memory to run. Your device's current memory usage is already high, and installation may affect the smoothness of multitasking. It is recommended that you close unnecessary programs before installation." Red light suggestion (higher risk): "Warning: Your device does not have enough available storage space to install this software. Please free up at least XX GB of disk space before trying again."

[0088] Presenting prompts to the user: Clearly display the generated installation suggestions to the user through a non-blocking, user-friendly interface, such as pop-ups or banner prompts. Provide the user with the choice: "Continue installation" or "Cancel installation," giving the final decision to the user.

[0089] The suggestion message could include, for example:

[0090] Estimated resource consumption: For example, after installing and running "XX software", your memory usage is expected to increase from the current 70% to 98%, and the system may become sluggish.

[0091] Device upgrade recommendations: For example, "To ensure smooth operation of this software, we recommend upgrading your RAM from 8GB to 16GB." Or, "Your mechanical hard drive may be causing slow loading of the software; we recommend replacing it with a solid-state drive (SSD)."

[0092] Immediate action suggestions: For example, "It has been detected that your currently running programs A, B, and C are consuming a lot of memory. Closing them will free up enough memory for new software to run."

[0093] In summary, this invention, based on operational data collected from numerous enterprise devices, provides comprehensive data on software performance consumption across different terminals. This data offers basic operational guarantees for running the software on different types of devices. For example, a certain software running on a Lenovo L14 device requires approximately 500MB of memory. Finally, when a user installs a particular software on a specific device, the system combines the user's computer's operational data with the software's required data for a comprehensive comparison, providing the user with relatively accurate suggestions regarding software consumption and whether the device can operate normally under daily office conditions. This allows users to choose software based on their needs or upgrade to larger, better hardware and computers.

[0094] Therefore, this invention can accurately analyze comprehensive data from equipment, software, and users' daily office work, making it easier for users to obtain more comprehensive operating data, software installation suggestions, and equipment configuration suggestions.

[0095] The present invention also provides a software installation device based on hardware configuration. For example... Figure 3 The diagram shown is a block diagram of a software installation device based on hardware configuration according to the present invention. This device can be implemented based on the software installation method described above, and its structure can be understood as mapping the above method steps to functional modules. See also Figure 3 The diagram shown is a block diagram of a hardware-based software installation device according to the present invention. This hardware-based software installation device 1 comprises four core modules: a data acquisition module 11, an upload module 12, an analysis module 13, and a notification module 14. These modules are interconnected via an internal bus or communication interface. The following provides a detailed description of the above-mentioned module.

[0096] The data acquisition module 11 collects hardware and software operation information from the terminal device. Specifically, it collects information such as device model, CPU model, memory size, disk type, application software list, CPU consumption, memory consumption, and disk I / O consumption. It is typically executed by a lightweight client program deployed on the terminal device, such as a personal computer or office computer. The data acquisition process can be periodic, event-triggered, or run continuously in the background.

[0097] Upload module 12 is used to upload the hardware information and software operation information to the server. The client uploads the collected information to the server, and there are no particular restrictions on the upload method. For example, it can upload to a centralized server through a secure network connection.

[0098] Analysis module 13 is used to analyze and generate comprehensive resource consumption data for the software on different types of terminal devices based on hardware information and software operation information uploaded by multiple terminal devices. In other words, analysis module 13 comprehensively analyzes the information uploaded by each terminal device and generates comprehensive analysis data. Specifically, it performs statistical calculations on the information uploaded by each terminal device, calculates the average value, generates statistical data, and uses the statistical data to view the software's operating status on these types of devices. The server analyzes and generates comprehensive resource consumption data for the software on different types of terminal devices based on hardware information and software operation information uploaded by multiple terminal devices.

[0099] The prompt module 14 is used to generate installation suggestions and prompt the user based on the comprehensive resource consumption data and the current operating information of the terminal device when installing the target software on the terminal device. When the user downloads the software through the enterprise software library or other channels, the client of the invention device will prompt the user for the basic configuration information required for the software to work on the target terminal. This basic configuration information is the average index.

[0100] Compared with the prior art, the software installation method and apparatus based on hardware configuration provided by the present invention have the following significant advantages:

[0101] This invention no longer relies solely on static, unrealistic minimum configuration requirements, but instead analyzes the operating data of massive amounts of real-world devices to accurately predict the resource consumption of software on specific device models, making the prediction results more realistic.

[0102] This invention not only considers hardware specifications, but more importantly, incorporates the device's current real-time operating status into the decision-making system. This enables the system to provide early warnings of potential risks caused by excessive current load, something that existing technologies simply cannot achieve.

[0103] The installation suggestions generated by this invention are specific and actionable. They not only tell users "whether it can be installed," but more importantly, "what will happen after installation" and "how to improve it," providing valuable decision-making support and avoiding performance degradation and work interruptions caused by blind installation.

[0104] For enterprise users, this invention can help IT departments better understand the actual performance of various software on their existing hardware assets, providing data-driven decision support for software procurement, hardware upgrades and IT resource planning, thereby optimizing total cost of ownership (TCO).

[0105] The data model upon which this invention relies is continuously enriched and optimized as the number of connected devices increases, and its prediction accuracy improves over time, forming a virtuous cycle of self-optimization.

[0106] The following two embodiments illustrate the hardware configuration-based software installation method of the present invention:

[0107] Example 1: Software Installation Early Warning in an Enterprise Environment

[0108] This embodiment uses an enterprise office scenario as an example to explain in detail the operation process of the present invention.

[0109] Deployment and data collection: A company deployed the client program of this invention on all employee computers.

[0110] Employee A uses a company-issued Lenovo ThinkPad T14 laptop, configured with an i5 CPU, 8GB of RAM, and a 256GB SSD.

[0111] The client continuously (or at specific intervals) collects the device's hardware information: Device model: ThinkPad T14, CPU: Intel i5-10210U, Memory: 8GB, Disk: NVMe SSD.

[0112] Simultaneously, software operation information is collected. At a certain moment, employee A is running "Chrome browser (10 tabs)," "Microsoft Word," "WeChat Work," and "JingME." The client records these processes and their resource usage: Total memory usage: 6.5GB, available memory: 1.5GB; CPU usage: 45%.

[0113] Data Upload and Modeling:

[0114] This anonymized data was uploaded to the company's IT management server (server-side).

[0115] The server aggregated data from thousands of devices of different models across the company. After analysis, it generated comprehensive data on the resource consumption of the design software Adobe Photoshop. One record showed that running Photoshop on a ThinkPad T14 device consumed an average of 3.5GB of memory.

[0116] Installation suggestions and prompts:

[0117] One day, employee A needed to install "Adobe Photoshop" from the company's software library to process images.

[0118] When employee A clicks the install button, the client is triggered. It performs the following actions:

[0119] a. Identify the device model as "ThinkPad T14".

[0120] b. Query the server for resource consumption data of "Photoshop" on this model, and get "estimated memory consumption 3.5GB".

[0121] c. Detect the current running status of the machine: "Available memory is approximately 1.5GB".

[0122] d. Comprehensive assessment: Estimated memory consumption (3.5GB) > Current available memory (1.5GB). Calculations show that memory will be severely insufficient after installation and operation.

[0123] The client generates a detailed installation suggestion and sends it to employee A via a pop-up window.

[0124] warn:

[0125] Your device currently has insufficient available memory (1.5GB) to ensure smooth operation of Photoshop. Extreme system lag is expected after running the program.

[0126] suggestion:

[0127] Immediately closing the Chrome browser and other non-essential applications can free up approximately 2GB of memory.

[0128] (Long-term) To successfully complete this type of design task, it is recommended to apply to the IT department to upgrade the memory to 16GB.

[0129] Following this prompt, employee A chose to close the Chrome browser first to free up memory before proceeding with the installation, thus avoiding the embarrassing situation of the system becoming unusable after installation.

[0130] Example 2: Upgrade Guide for Personal User Devices

[0131] This example uses the case of an individual user purchasing new software or a game.

[0132] Data Background: The server has established a data model through contributions from a large number of user clients. For example, it is known that when a certain large-scale 3D game is run on a certain model of gaming laptop (equipped with a GTX1660 graphics card), the average frame rate is only 40 FPS, and the CPU utilization rate is consistently higher than 90%.

[0133] Recommended installation process:

[0134] User B owns a gaming laptop of this model and is trying to install this 3D game.

[0135] After the client queries the server, the comprehensive resource consumption data obtained includes not only memory / CPU consumption, but also performance indicators such as "estimated frame rate: 40FPS (lower than the smooth standard of 60FPS)".

[0136] The client, based on its local hardware (confirmed to be a GTX 1660 graphics card), generates the following prompt:

[0137] "Your hardware configuration is capable of running this game, but based on data analysis of similar devices, the game's frame rate is expected to be low (around 40 FPS), and the experience may not be smooth."

[0138] "To achieve a smooth 60FPS experience at 1080p resolution, it is recommended to use an RTX 3060 or higher performance graphics card."

[0139] User B thus received clear upgrade guidance, enabling them to make more cost-effective consumption decisions.

[0140] Scope of information collected: In addition to the basic hardware and software operating information mentioned above, information such as network bandwidth, graphics card model and video memory, and battery level (for mobile devices) can also be collected to provide more comprehensive suggestions (such as cloud gaming and mobile application installation).

[0141] Analysis model complexity: In addition to simple averages and percentiles, the server can use more complex machine learning models (such as regression models and neural networks) to predict resource consumption, taking into account the interaction between multiple hardware parameters.

[0142] Recommended presentation format: Installation recommendations can be simple text prompts or graphical dashboards that visually display the risk level using colors (green / yellow / red).

[0143] Triggering timing: It can be triggered not only during installation, but also when browsing the software store, where the software's compatibility and performance estimates for the current device can be displayed in advance.

[0144] Enhanced privacy protection: All uploaded data can be strongly anonymized and uses technologies such as differential privacy to ensure the effectiveness of overall data analysis while protecting the privacy of individual users.

[0145] In summary, this invention provides an intelligent, precise, and forward-looking software installation solution that effectively fills a significant gap in existing technologies. It has high practical value and broad application prospects in both the personal user market and the enterprise IT management field.

[0146] Specifically, this invention collects and analyzes hardware information and real-time software operation information from a massive number of terminal devices to construct a software resource consumption model, thereby providing highly accurate installation and configuration suggestions based on the current operating status of a user's specific device when installing new software.

[0147] It should be noted that the acquisition, storage, and application of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate good morals.

[0148] Figure 4 An exemplary system architecture 800 is shown that can be applied to the hardware-based software installation method and installation apparatus of embodiments of the present invention.

[0149] like Figure 4 As shown, system architecture 800 may include terminal devices 801, 802, and 803, a network 804, and a server 805. Network 804 serves as the medium for providing communication links between terminal devices 801, 802, and 803 and server 805. Network 804 may include various connection types, such as wired or wireless communication links or fiber optic cables, etc.

[0150] Users can use terminal devices 801, 802, and 803 to interact with server 805 via network 804 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 801, 802, and 803, such as navigation applications, driving applications, autonomous vehicle control applications, and social platform software.

[0151] Terminal devices 801, 802, and 803 can be various electronic devices with displays and web browsing capabilities, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0152] Server 805 can be a server that provides various services, such as a backend management server that supports vehicle driving monitoring viewed by users through terminal devices 801, 802, and 803. The backend management server can analyze and process received data such as images and feed the processing results back to the terminal devices.

[0153] It should be noted that the hardware-configuration-based software installation method provided in this embodiment of the invention is generally executed by server 805, and correspondingly, the hardware-configuration-based software installation device is generally located in server 805.

[0154] It should be understood that Figure 4 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0155] The following is for reference. Figure 5 It shows a schematic diagram of the structure of a computer system 900 suitable for implementing a terminal device of the present invention. Figure 5 The terminal device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0156] like Figure 5 As shown, the computer system 900 includes a central processing unit (CPU) 901, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 902 or programs loaded from storage section 908 into random access memory (RAM) 903. The RAM 903 also stores various programs and data required for the operation of the system 900. The CPU 901, ROM 902, and RAM 903 are interconnected via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0157] The following components are connected to I / O interface 905: an input section 906 including a keyboard, mouse, etc.; an output section 907 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to I / O interface 905 as needed. A removable medium 911, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 910 as needed so that computer programs read from it can be installed into storage section 908 as needed.

[0158] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 909, and / or installed from removable medium 911. When the computer program is executed by central processing unit (CPU) 901, it performs the functions defined above in the system of this invention.

[0159] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0160] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0161] The modules described in the embodiments of the present invention can be implemented in software or hardware. The described modules can also be housed in a processor; for example, a processor can be described as including an image voxel mesh acquisition module, a lidar voxel mesh acquisition module, a fusion module, and a detection module. The names of these modules do not necessarily limit the functionality of the module itself.

[0162] In another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or it may exist independently and not assembled into the device. The computer-readable medium carries one or more programs that, when executed by the device, cause the device to perform the methods described above.

[0163] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A software installation method based on hardware configuration, characterized in that, include: Collect hardware and software operation information of terminal devices; Upload the hardware information and the software operation information to the server; The server analyzes and generates comprehensive data on the resource consumption of the software on different types of terminal devices based on the hardware information and software operation information uploaded by multiple terminal devices. When the target software is installed on the terminal device, an installation suggestion is generated and prompted to the user based on the comprehensive data of resource consumption and the current operating information of the terminal device.

2. The software installation method based on hardware configuration according to claim 1, characterized in that, Before uploading the hardware information and software operation information to the server, anonymization processing is performed on the data received by the server.

3. The software installation method based on hardware configuration according to claim 1, characterized in that, The analysis and generation of comprehensive resource consumption data for different types of terminal devices includes: classifying the data uploaded to the server; performing statistical analysis on the classified data; and generating comprehensive resource consumption data through a generation model.

4. The software installation method based on hardware configuration according to claim 1, characterized in that, When installing the target software on the terminal device, based on the comprehensive resource consumption data and the current operating information of the terminal device, an installation suggestion is generated and prompted to the user, including: The client is triggered when a user installs target software on their terminal device; The client collects and calculates the current operating information of the terminal device in real time; The client sends a request to the server to obtain comprehensive data on the resource consumption of the target software; The acquired local running status is compared and calculated with the acquired comprehensive data on software resource consumption to check whether the remaining disk space is greater than the space occupied by the software; and Based on the comparison results, installation suggestions are generated.

5. The software installation method based on hardware configuration according to claim 4, characterized in that, When installing the target software on the terminal device, based on the comprehensive resource consumption data and the current operating information of the terminal device, an installation suggestion is generated and prompted to the user, including: The generated installation suggestions are displayed to the user through the user interface.

6. The software installation method based on hardware configuration according to claim 5, characterized in that, The generated installation recommendations include estimated resource consumption, equipment upgrade recommendations, and immediate operation recommendations.

7. The software installation method based on hardware configuration according to claim 1, characterized in that, The acquisition module is specifically used to acquire at least one of the following as hardware information: device model, CPU model, memory size, and disk type; The acquisition module is specifically used to collect at least one of the following as software operation information: application software list, CPU consumption, memory consumption, and disk I / O consumption.

8. A software installation device based on hardware configuration, characterized in that, include: The acquisition module is used to acquire hardware information and software operation information of the terminal device; An upload module is used to upload the hardware information and software operation information to the server. The analysis module is used to analyze and generate comprehensive data on the resource consumption of the software on different types of terminal devices based on the hardware information and software operation information uploaded by multiple terminal devices. The prompting module is used to generate installation suggestions and prompt the user based on the comprehensive resource consumption data and the current operating information of the terminal device when installing target software on the terminal device.

9. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-7.

10. An electronic device with a software installation method based on hardware configuration, characterized in that, include: One or more processors; as well as Storage device for storing one or more programs. The one or more programs are executed by the one or more processors, such that the one or more processors implement the method as described in any one of claims 1-7.

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