CN114115822B - Cloud edge combination-based intelligent wearable operating system generation method and system - Google Patents
Cloud edge combination-based intelligent wearable operating system generation method and system Download PDFInfo
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Abstract
The invention provides a method and a system for generating an intelligent wearable operating system based on cloud edge combination. Chip manufacturers, chip models, drivers and a chip Lib library are managed reasonably; the background can quickly generate the basic operating system version according to different chips, an engineer does not need to perform local compiling, and a large amount of manpower and material resources are saved; the cloud can load the peripheral drivers according to different peripheral chips and requirements; and applying for a control and a service module required by the operating system on line by the background.
Description
Technical Field
The invention relates to an intelligent wearable operating system, in particular to a method and a system for generating the intelligent wearable operating system based on cloud edge combination, and belongs to the field of intelligent wearable operating systems.
Background
Currently, a wearable operating system or an embedded development in the market is developed based on two modes.
Firstly, in a monomer packaging mode, a main control chip Lib library or an external network chip is driven and preset in an intelligent wearable operating system, the version number of the operating system is built according to model selection chips of different manufacturers, and then the operating system is independently burned according to different projects;
secondly, in a single whole package mode, a main control chip Lib library and an external network chip which are mainstream in the industry are driven and preset in an intelligent wearable operating system, when the main control chip manufacturers and the external network chip manufacturers increase, codes are overlapped, and a main version is unified to burn the operating system in the burning process;
the first scheme is as follows: the single packing mode is not convenient for operating system code management as required, and each scheme has one set of codes, so that the management and maintenance cost is high;
scheme II: in a single integral packaging mode, codes of an operating system are too fat, so that the cost of intelligent wearable hardware is increased along with the increase of the codes and resources, and the running efficiency of the system is low;
the current operating system level adopts manual compilation, then after downloading, the burn is carried out through a burner, and a large amount of technicians are wasted.
The current intelligent wearable hardware configuration is low, the memory is generally between 64M-256M, the current operating system on the market adopts a single-body and whole-packet mode according to requirements, the single-body mode causes the maintenance cost of the operating system, the management of the operating system is inconvenient, and errors are easy to occur; the single whole-pack mode and the bloated codes enable the flash worn intelligently to not meet the hardware requirement, therefore, running hardware needs to be increased, and meanwhile, the problem of low running efficiency of an operating system is caused by a large number of redundant codes.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a method and a system for generating an intelligent wearable operating system based on cloud edge combination, which are used for achieving the purpose of generating the operating system of intelligent wearable equipment.
The invention provides a generation method of an intelligent wearable operating system based on cloud edge combination, which comprises the following steps of constructing a basic operating system cloud end:
s1: logging in an intelligent wearable basic operating system to construct a cloud platform, and entering an intelligent wearable WearfitOS basic construction page;
s2: selecting a communication protocol;
selecting a preset communication mode for information transmission between the cloud platform and the development terminal server;
s3: identifying the obtained chip;
the cloud platform receives information of the main control chip and the peripheral chips sent by the development terminal server and identifies the models of the main control chip and the peripheral chips;
s4: selecting a module;
the cloud platform controls the module and the service module according to the model of the identified main control chip and the model of the peripheral chip and the set module, the control module and the service module required by the model matching of the main control chip and the peripheral chip according to the preset matching rule in the module library, and feeds back the module matching result to the development terminal server;
s5: module confirmation;
the development terminal server receives the module matching result, confirms the module matching result and feeds the confirmed matching result back to the cloud platform;
s6: compiling and burning the system;
the cloud platform matches a preset corresponding system with the chip, online compiling is conducted to generate an intelligent wearable WearfitOS basic operating system, the cloud platform is connected with the burner, burner software is authorized to download the intelligent wearable WearfitOS basic operating system online, and burning of the main control chip and the peripheral chip is completed.
Preferably, the generation method further comprises system online upgrade, specifically comprising the following steps:
s11: monitoring a chip library and an SDK;
after the WearfitOS basic operating system is intelligently worn and started, monitoring whether a new chip base or SDK exists in the cloud;
s12: upgrading and selecting;
if a new chip library or SDK exists, loading the new chip library or SDK as required, and restarting the intelligent wearable WearfitOS basic operating system for updating;
and if the new chip library or the SDK does not exist, normally starting the WearfitOS basic operating system which is worn intelligently to run.
Preferably, the matching rule preset in the module library includes matching information between the chip and the module; marking the model of the chip as x, the chips of different models as x1, x2, x3., the setting module as d, the setting modules of different types as d1, d2, d3., the control module as e, the control modules of different types as e1, e2, e3., the traffic module as f, and the traffic modules of different types as f1, f2, f3.;
setting x, d, e and f as a group, arranging and combining x1, x2, x3., d1, d2, d3., e1, e2, e3., f1, f2 and f3. to obtain m combinations, wherein the matching degree of each combination is n, n is not less than p and is the matching qualification, p is the preset lowest matching degree qualification parameter, and screening u qualified combinations to form a module matching result.
Preferably, the module matching result further includes marking the highest matching qualification degree combination u1 and the lowest cost price combination u2 in the u qualified combinations, and marking the cost price for each matching qualified combination.
Preferably, after receiving the module matching result, the development terminal server selects a required combination from the u qualified combinations for system compilation and use according to a preset matching degree requirement and a preset cost price requirement.
Preferably, the monitoring time of the chip library and the SDK includes three modes:
the first method comprises the following steps: after the intelligent wearable equipment is started, the WearfitOS basic operating system is intelligently worn to start an automatic monitoring chip library and update the SDK;
and the second method comprises the following steps: after the intelligent wearable WearfitOS basic operating system is started, whether the chip library and the SDK are updated or not is automatically monitored within preset interval time;
and the third is that: based on the number of different functions used in the intelligent wearable WearfitOS basic operating system and the number of times of each function used by a wearable device user in a preset time period, automatically monitoring;
setting the number of the used functions as w, setting the number of the used functions as y, adding w different y values and dividing by w to obtain an average value z of the number of the used functions, comparing z with a, if z is larger than or equal to a, automatically updating a monitoring chip library and an SDK by the intelligent wearable WearfitOS basic operating system, and a is a preset average value of the number of the used functions.
A generation system of an intelligent wearable operating system based on cloud edge combination is used for a cloud platform; comprises a communication module, an identification module, a distribution module and an authorization module;
the communication module selects a preset communication mode and is used for information transmission between the cloud platform and the development terminal server;
the identification module is used for receiving the information of the main control chip and the peripheral chips sent by the development terminal server by the cloud platform and identifying the models of the main control chip and the peripheral chips;
the distribution module is used for the cloud platform to set a module, a control module and a service module required by the model matching of the main control chip and the peripheral chip according to the model of the main control chip and the model of the peripheral chip which are identified and according to a matching rule preset in a module library, and feeding back a module matching result to the development terminal server;
and the authorization module is used for matching a preset corresponding system with the chip by the cloud platform, performing online compiling to generate an intelligent wearable WearfitOS basic operating system, connecting the cloud platform with the burner, and authorizing the burner software to download the intelligent wearable WearfitOS basic operating system online to complete the burning of the main control chip and the peripheral chip.
The invention has the beneficial effects that:
1. chip manufacturers, chip models, drivers and a chip Lib library are managed reasonably; the background can quickly generate the basic operating system version according to different chips, an engineer does not need to perform local compiling, and a large amount of manpower and material resources are saved; the cloud can load the peripheral drivers according to different peripheral chips and requirements; and applying for a control and a service module required by the operating system on line by the background.
2. The intelligent wearable operating system is used for generating and compiling a self-defined online operating system DIY based on the main control chip and the peripheral chip; operating system is dressed to intelligence, and cloud limit combination module is according to controlling part and business module needs, and dynamic loading is to intelligent wrist-watch terminal, and efficiency is higher, and the matching accuracy is better.
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In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is a flow chart of the generation method of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a method for generating an intelligent wearable operating system based on cloud edge combination according to an embodiment of the present invention includes a basic operating system cloud establishment, where the basic operating system cloud establishment includes the following steps:
s1: logging in an intelligent wearable basic operating system to construct a cloud platform, and entering an intelligent wearable WearfitOS basic construction page;
s2: selecting a communication protocol;
selecting a preset communication mode for information transmission between the cloud platform and the development terminal server; the communication mode can be Bluetooth, wifi or other network modes, and various communication modes are adopted, so that the adaptability is good, and the limitation is not easy to be caused in use;
s3: identifying the obtained chip;
the cloud platform receives information of the main control chip and the peripheral chips sent by the development terminal server and identifies the models of the main control chip and the peripheral chips; the cloud platform provides matched hardware option prompts for the chip and the intelligent wearable equipment based on the type of the chip used by the intelligent wearable equipment, and provides help for the compiling system according to the type of the hardware and the type of the chip;
s4: selecting a module;
the cloud platform controls the module and the service module according to the model of the identified main control chip and the model of the peripheral chip and the set module, the control module and the service module required by the model matching of the main control chip and the peripheral chip according to the preset matching rule in the module library, and feeds back the module matching result to the development terminal server; the module library can conveniently and rapidly screen out the corresponding module matching result by the cloud platform for screening by development end workers, and the workers can compare the module matching result with a preset result, so that the working efficiency is conveniently improved by the workers, and manpower and material resources are greatly saved;
s5: module confirmation;
the development terminal server receives the module matching result, confirms the module matching result and feeds the confirmed matching result back to the cloud platform; the staff selects according to the needs based on the received module matching result, the selection efficiency and accuracy are improved, and the situation that the wearable equipment cannot normally run due to the fact that the hardware equipment and the software equipment are not matched is avoided;
s6: compiling and burning the system;
the cloud platform matches a preset corresponding system with the chip, online compiling is conducted to generate an intelligent wearable WearfitOS basic operating system, the cloud platform is connected with the burner, burner software is authorized to download the intelligent wearable WearfitOS basic operating system online, and burning of the main control chip and the peripheral chip is completed. After receiving the specific model of the chip and the required numerous hardware modules, the cloud platform can match a corresponding operating system from a preset system library; the operating system completes the burning of the chip through the burner. During burning, a 511 burning method is adopted for burning.
As a technical optimization scheme of the invention, the generation method also comprises the online upgrade of the system, and specifically comprises the following steps:
s11: monitoring a chip library and an SDK;
after the WearfitOS basic operating system is intelligently worn and started, monitoring whether a new chip base or SDK exists in the cloud;
s12: upgrading and selecting;
if a new chip library or SDK exists, loading the new chip library or SDK as required, and restarting the intelligent wearable WearfitOS basic operating system for updating;
and if the new chip library or the SDK does not exist, normally starting the WearfitOS basic operating system which is worn intelligently to run. Good follow-up upgrading assistance is provided for follow-up intelligent wearable equipment in use, so that the intelligent wearable equipment has better experience in follow-up use.
As a technical optimization scheme of the invention, the matching rule preset in the module library comprises matching information between the chip and the module; marking the model of the chip as x, the chips of different models as x1, x2, x3., the setting module as d, the setting modules of different types as d1, d2, d3., the control module as e, the control modules of different types as e1, e2, e3., the traffic module as f, and the traffic modules of different types as f1, f2, f3.;
setting x, d, e and f as a group, arranging and combining x1, x2, x3., d1, d2, d3., e1, e2, e3., f1, f2 and f3. to obtain m combinations, wherein the matching degree of each combination is n, n is not less than p and is the matching qualification, p is the preset lowest matching degree qualification parameter, and screening u qualified combinations to form a module matching result. The method comprises the steps of pre-matching chips commonly used in the market with commonly used modules, setting matching degree according to preset requirements, classifying the chips of different types and hardware modules which can be correspondingly used by the chips of different types according to the matching degree, and forming a module library to be stored in the cloud platform. After the model of the chip is subsequently provided, the selection of hardware selection can be quickly and accurately given through the cloud platform, and the working efficiency and the adaptation degree of the chip and the module are improved.
As a technical optimization scheme of the invention, the module matching result further comprises a combination u1 with the highest matching qualification degree and a combination u2 with the lowest cost price marked in the u qualified combinations, and the cost price is marked for each matching qualified combination. The two common combinations are provided for selection, the working efficiency can be improved, and basic reference is provided for the cost and the performance of the intelligent wearable equipment.
As a technical optimization scheme of the invention, after receiving the module matching result, the development terminal server selects the required combination from the u qualified combinations for system compiling and use according to the preset matching degree requirement and the preset cost price requirement.
As a technical optimization scheme of the invention, the monitoring time of the chip library and the SDK comprises three modes:
the first method comprises the following steps: after the intelligent wearable device is started, the WearfitOS basic operating system is intelligently worn to start an automatic monitoring chip library and update the SDK. The intelligent wearable device, such as an intelligent watch or a bracelet, automatically monitors the chip library and the SDK once after being started;
and the second method comprises the following steps: after the WearfitOS basic operating system is started, whether the chip library and the SDK are updated or not is automatically monitored within preset interval time. The automatic detection can be carried out once in a week or half a month and other time by the setting module, so that the long-time monitoring state is avoided, the consumption of electric quantity is accelerated, other functions are hard, and the service lives of various parts are shortened;
and the third is that: based on the number of different functions used in the intelligent wearable WearfitOS basic operating system and the number of times of each function used by a wearable device user in a preset time period, automatically monitoring;
setting the number of the used functions as w, setting the number of the used functions as y, adding w different y values and dividing by w to obtain an average value z of the number of the used functions, comparing z with a, if z is larger than or equal to a, automatically updating a monitoring chip library and an SDK by the intelligent wearable WearfitOS basic operating system, and a is a preset average value of the number of the used functions. Based on the number of each function used by the user and the number of times of each function, the demand degree of the user for the system use is judged according to the average number of the use of each function, z is larger than or equal to a, the demand degree of the user is larger, and the monitoring chip library and the SDK are automatically monitored once. More humanized, the user can obtain new use experience as soon as possible, and the disturbance of frequent upgrade reminding to the user is avoided.
A generation system of an intelligent wearable operating system based on cloud edge combination is used for a cloud platform; comprises a communication module, an identification module, a distribution module and an authorization module;
the communication module selects a preset communication mode and is used for information transmission between the cloud platform and the development terminal server;
the identification module is used for receiving the information of the main control chip and the peripheral chips sent by the development terminal server by the cloud platform and identifying the models of the main control chip and the peripheral chips;
the distribution module is used for the cloud platform to set a module, a control module and a service module required by the model matching of the main control chip and the peripheral chip according to the model of the main control chip and the model of the peripheral chip which are identified and according to a matching rule preset in a module library, and feeding back a module matching result to the development terminal server;
and the authorization module is used for matching a preset corresponding system with the chip by the cloud platform, performing online compiling to generate an intelligent wearable WearfitOS basic operating system, connecting the cloud platform with the burner, and authorizing the burner software to download the intelligent wearable WearfitOS basic operating system online to complete the burning of the main control chip and the peripheral chip.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (6)
1. A generation method of an intelligent wearable operating system based on cloud edge combination is characterized by comprising the following steps of constructing a basic operating system cloud end:
s1: logging in an intelligent wearable basic operating system to construct a cloud platform, and entering an intelligent wearable WearfitOS basic construction page;
s2: selecting a communication protocol;
selecting a preset communication mode for information transmission between the cloud platform and the development terminal server;
s3: identifying the obtained chip;
the cloud platform receives information of the main control chip and the peripheral chips sent by the development terminal server and identifies the models of the main control chip and the peripheral chips;
s4: selecting a module;
the cloud platform controls the module and the service module according to the model of the identified main control chip and the model of the peripheral chip and the set module, the control module and the service module required by the model matching of the main control chip and the peripheral chip according to the preset matching rule in the module library, and feeds back the module matching result to the development terminal server;
s5: module confirmation;
the development terminal server receives the module matching result, confirms the module matching result and feeds the confirmed matching result back to the cloud platform;
s6: compiling and burning the system;
the cloud platform matches a preset corresponding system with the chip, online compiling is conducted to generate an intelligent wearable WearfitOS basic operating system, the cloud platform is connected with the burner, burner software is authorized to download the intelligent wearable WearfitOS basic operating system online, and burning of the main control chip and the peripheral chip is completed;
the matching rule preset in the module library comprises matching information between the chip and the module; marking the model of the chip as x, the chips of different models as x1, x2, x3., the setting module as d, the setting modules of different types as d1, d2, d3., the control module as e, the control modules of different types as e1, e2, e3., the traffic module as f, and the traffic modules of different types as f1, f2, f3.;
setting x, d, e and f as a group, arranging and combining x1, x2, x3., d1, d2, d3., e1, e2, e3., f1, f2 and f3. to obtain m combinations, wherein the matching degree of each combination is n, n is not less than p and is the matching qualification, p is the preset lowest matching degree qualification parameter, and screening u qualified combinations to form a module matching result.
2. The generation method according to claim 1, further comprising a system online upgrade, specifically comprising the steps of:
s11: monitoring a chip library and an SDK;
after the WearfitOS basic operating system is intelligently worn and started, monitoring whether a new chip base or SDK exists in the cloud;
s12: upgrading and selecting;
if a new chip library or SDK exists, loading the new chip library or SDK as required, and restarting the intelligent wearable WearfitOS basic operating system for updating;
and if the new chip library or the SDK does not exist, normally starting the WearfitOS basic operating system which is worn intelligently to run.
3. The method of claim 1, wherein the module matching result further comprises marking the highest matching qualification combination u1 and the lowest cost price combination u2 in the u qualified combinations, and marking the cost price for each matching qualified combination.
4. The generation method according to claim 3, wherein the development terminal server selects a desired combination from the u qualified combinations for system compilation after receiving the module matching result according to a preset matching degree requirement and a preset cost price requirement.
5. The method of claim 4, wherein the monitoring time of the chip library and the SDK comprises three modes:
the first method comprises the following steps: after the intelligent wearable equipment is started, the WearfitOS basic operating system is intelligently worn to start an automatic monitoring chip library and update the SDK;
and the second method comprises the following steps: after the intelligent wearable WearfitOS basic operating system is started, whether the chip library and the SDK are updated or not is automatically monitored within preset interval time;
and the third is that: based on the number of different functions used in the intelligent wearable WearfitOS basic operating system and the number of times of each function used by a wearable device user in a preset time period, automatically monitoring;
setting the number of the used functions as w, setting the number of the used functions as y, adding w different y values and dividing by w to obtain an average value z of the number of the used functions, comparing z with a, if z is larger than or equal to a, automatically updating a monitoring chip library and an SDK by the intelligent wearable WearfitOS basic operating system, and a is a preset average value of the number of the used functions.
6. A generation system of an intelligent wearable operating system based on cloud edge combination is characterized in that the generation system is used for a cloud platform; comprises a communication module, an identification module, a distribution module and an authorization module;
the communication module selects a preset communication mode and is used for information transmission between the cloud platform and the development terminal server;
the identification module is used for receiving the information of the main control chip and the peripheral chips sent by the development terminal server by the cloud platform and identifying the models of the main control chip and the peripheral chips;
the distribution module is used for the cloud platform to set a module, a control module and a service module required by the model matching of the main control chip and the peripheral chip according to the model of the main control chip and the model of the peripheral chip which are identified and according to a matching rule preset in a module library, and feeding back a module matching result to the development terminal server;
the authorization module is used for matching a preset corresponding system with a chip by the cloud platform, performing online compiling to generate an intelligent wearable WearfitOS basic operating system, connecting the cloud platform with the burner, and authorizing burner software to download the intelligent wearable WearfitOS basic operating system online to complete burning of the main control chip and the peripheral chip;
the matching rule preset in the module library comprises matching information between the chip and the module; marking the model of the chip as x, the chips of different models as x1, x2, x3., the setting module as d, the setting modules of different types as d1, d2, d3., the control module as e, the control modules of different types as e1, e2, e3., the traffic module as f, and the traffic modules of different types as f1, f2, f3.;
setting x, d, e and f as a group, arranging and combining x1, x2, x3., d1, d2, d3., e1, e2, e3., f1, f2 and f3. to obtain m combinations, wherein the matching degree of each combination is n, n is not less than p and is the matching qualification, p is the preset lowest matching degree qualification parameter, and screening u qualified combinations to form a module matching result.
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