CN114172943B - Intelligent wireless router of thing networking - Google Patents

Intelligent wireless router of thing networking Download PDF

Info

Publication number
CN114172943B
CN114172943B CN202210127318.0A CN202210127318A CN114172943B CN 114172943 B CN114172943 B CN 114172943B CN 202210127318 A CN202210127318 A CN 202210127318A CN 114172943 B CN114172943 B CN 114172943B
Authority
CN
China
Prior art keywords
control scheme
acquiring
preset
value
control
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202210127318.0A
Other languages
Chinese (zh)
Other versions
CN114172943A (en
Inventor
郑伟军
洪琴
李建国
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hangzhou Snooker Technology Co ltd
Original Assignee
Hangzhou Snooker Technology Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hangzhou Snooker Technology Co ltd filed Critical Hangzhou Snooker Technology Co ltd
Priority to CN202210127318.0A priority Critical patent/CN114172943B/en
Publication of CN114172943A publication Critical patent/CN114172943A/en
Application granted granted Critical
Publication of CN114172943B publication Critical patent/CN114172943B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
    • H04L67/125—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/3331—Query processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/30—Semantic analysis
    • G—PHYSICS
    • G08—SIGNALLING
    • G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
    • G08C17/00—Arrangements for transmitting signals characterised by the use of a wireless electrical link
    • G08C17/02—Arrangements for transmitting signals characterised by the use of a wireless electrical link using a radio link
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W88/00—Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
    • H04W88/08—Access point devices

Abstract

The invention provides an intelligent wireless router of the Internet of things, which comprises: the first acquisition module is used for acquiring the function information of at least one Internet of things device which is in butt joint with the home of the user and acquiring the preference information corresponding to the user; the manufacturing module is used for manufacturing a control scheme list based on the function information and the preference information and outputting and displaying the control scheme list; the second acquisition module is used for acquiring the control scheme selected by the user from the control scheme list; and the control module is used for correspondingly controlling the equipment of the Internet of things based on the control scheme. According to the intelligent wireless router for the Internet of things, a user does not need to check the specification of the Internet of things equipment, so that the user can know all functions one by one, and the user does not need to have preference by himself, and the control scheme of the Internet of things router for all the Internet of things equipment is set, so that convenience is greatly improved, user experience is improved, and the intelligent wireless router for the Internet of things is also suitable for the old and the like.

Description

Intelligent wireless router of thing networking
Technical Field
The invention relates to the technical field of Internet of things, in particular to an intelligent wireless router for the Internet of things.
Background
At present, after an internet of things router is in butt joint with internet of things equipment (such as an intelligent sound box, intelligent lighting equipment, an intelligent television and the like) in a user home, due to the fact that the internet of things equipment is more intelligent and has more functions, a user needs to check specifications of the internet of things equipment to determine which functions exist, and also needs to set control schemes (such as light brightness of the intelligent lighting equipment in different time periods, playing music types of the intelligent sound box in different time periods and the like) of the internet of things router for each piece of internet of things equipment according to own preference, so that the internet of things router is more complicated, user experience is reduced, and the internet of things router is more inapplicable especially when the user types are old people, handicapped people and the like;
therefore, a solution is needed.
Disclosure of Invention
The invention provides an intelligent wireless router for the Internet of things, which is characterized in that after the router is in butt joint with equipment for the Internet of things, functional information of the equipment for the Internet of things and preference information of a user are obtained, a control scheme list is made based on the functional information and the preference information of the user and is used for the user to select, the user does not need to check a specification of the equipment for the Internet of things, the user knows each function one by one, the user does not need to have preference by himself, a control scheme of the router for the Internet of things for each equipment for the Internet of things is set, convenience is improved to the greatest extent, user experience is improved, and the intelligent wireless router for the Internet of things is also suitable for the old people and the like.
The invention provides an intelligent wireless router of the Internet of things, which comprises:
the first acquisition module is used for acquiring the function information of at least one piece of internet-of-things equipment which is docked in the home of the user and acquiring the preference information corresponding to the user;
the manufacturing module is used for manufacturing a control scheme list based on the function information and the preference information and outputting and displaying the control scheme list;
the second acquisition module is used for acquiring the first control scheme selected by the user from the control scheme list;
and the control module is used for correspondingly controlling the equipment of the Internet of things based on the first control scheme.
Preferably, the first obtaining module performs the following operations:
acquiring a preset docking node set, wherein the docking node set comprises: the system comprises a plurality of docking nodes, a plurality of communication nodes and a plurality of communication interfaces, wherein the docking nodes correspond to Internet of things equipment which is docked in one user home;
inquiring the access node based on a preset inquiry strategy;
acquiring at least one function information item replied by the docking node after the docking node is queried;
and integrating the acquired function information items to acquire function information and finish acquisition.
Preferably, the first obtaining module performs the following operations:
acquiring the use member information corresponding to the user, wherein the use member information comprises: a plurality of first usage members and usage weights corresponding to the first usage members;
sequentially traversing the first use member, and taking the traversed first use member as a second use member during each traversal;
acquiring a preset big data node set, wherein the big data node set comprises: the big data nodes correspond to a big data platform;
acquiring an evaluation value corresponding to the big data node, acquiring a plurality of first preference information items corresponding to the second use member through the corresponding big data node if the evaluation value is greater than or equal to a preset evaluation threshold value, and giving the first preference information items a use weight corresponding to the second use member to obtain second preference information items;
and after traversing the first user member, integrating each second preference information item to obtain the preference information corresponding to the user, and finishing the acquisition.
Preferably, the obtaining of the evaluation value corresponding to the big data node includes:
acquiring at least one guarantor for guarantying the big data node, and acquiring a first guaranty weight for the guarantor to secure the big data node;
inquiring a preset guarantor-historical behavior library, and determining a plurality of historical behaviors corresponding to the guarantor;
acquiring a preset influence behavior library, and matching the historical behaviors with the influence behaviors in the influence behavior library;
if the matching is in accordance with the preset action, acquiring a first influence value corresponding to the influence action in accordance with the matching, and acquiring a action generation time point corresponding to the history action in accordance with the matching;
generating a time weight based on a generation time point according to a preset time weight generation rule;
giving a time weight to the corresponding first influence value to obtain a second influence value;
inquiring a preset influence value-down regulation amplitude library, and determining a first down regulation amplitude corresponding to the second influence value;
based on the first downward adjustment amplitude, downward adjusting a first guarantee weight corresponding to the corresponding guarantee party;
taking the first guarantee weight after all the downward adjustment is finished as a second guarantee weight;
acquiring a plurality of node events corresponding to the big data node, and analyzing the event type of the node event, wherein the event type comprises: malicious events and contributing events;
when the event type of the node event is a malicious event, inputting the corresponding node event into a preset malicious detection model, performing malicious detection, and acquiring a malicious value output by the malicious detection model after the malicious detection is completed;
when the event type of the node event is a contribution event, inputting the corresponding node event into a preset contribution analysis model, performing contribution analysis, and acquiring a contribution value output by the contribution analysis model after the contribution analysis is completed;
accumulating and calculating the malicious values to obtain malicious value sums, and meanwhile determining the malicious values and corresponding second down-regulation amplitudes based on a preset malicious value sum-down-regulation amplitude library;
accumulating and calculating the contribution values to obtain a first contribution value sum, simultaneously, adjusting the first contribution value sum downwards based on a second downward adjustment amplitude, and taking the first contribution value sum after downward adjustment as a second contribution value sum;
and accumulating and calculating the second guarantee weight and the second contribution value sum to obtain an evaluation value corresponding to the big data node, and finishing the acquisition.
Preferably, the production module performs the following operations:
training a control scheme determination model;
inputting the function information and the preference information into a control scheme determination model, determining a control scheme, and acquiring a plurality of control scheme items output by the control scheme determination model after the control scheme determination model completes the determination of the control scheme;
acquiring a preset blank form, and filling all control scheme items into the blank form;
and when all the control scheme items needing to be filled into the blank form are completely filled, taking the blank form as a control scheme list to finish the manufacture.
Preferably, the training control scheme determination model comprises:
obtaining a sample to be trained, wherein the sample to be trained comprises: a first determination process record recorded when the plurality of manual control scheme determinations are made;
acquiring a determining party corresponding to the first determining process record, and acquiring an empirical value corresponding to the determining party;
if the experience value is larger than or equal to a preset experience threshold value, acquiring a recording process of a first determination process record recorded by a corresponding determination party;
based on a preset standard detection strategy, carrying out standard detection on the recording process to obtain a standard value;
if the standard value is larger than or equal to a preset standard threshold value, performing quality analysis on a first determination process record recorded by a corresponding determination party based on a preset quality analysis strategy to obtain a quality value;
if the quality value is less than or equal to a preset quality threshold value, rejecting the corresponding first determination process record;
when all the first determining process records needing to be removed are removed, taking the first determining process records which are removed as second determining process records;
and performing model training according to a preset model training algorithm based on the second determination process record, and acquiring a control scheme to determine the model when the training is completed.
Preferably, obtaining the empirical value corresponding to the determiner includes:
acquiring the recording time of the determining party corresponding to the first determining process record, and acquiring a determining personnel-historical experience value base corresponding to the recording time;
acquiring personnel composition information corresponding to a determining party, wherein the personnel composition information comprises: a plurality of determined persons;
determining a first historical experience value corresponding to a determined person based on the determined person-historical experience value library;
acquiring the determination weight of the determination personnel corresponding to the corresponding first determination process record;
giving a corresponding first historical experience value to determine a weight to obtain a second historical experience value;
and accumulating and calculating all the second historical experience values to obtain the experience value corresponding to the determining party.
Preferably, thing networking intelligence wireless router still includes:
and the voice control module is used for acquiring at least one first control instruction item input by a user and correspondingly controlling the Internet of things equipment based on the first control instruction item.
Preferably, the voice control module performs the following operations:
counting the number of the first control instruction items;
if the number is 1, identifying a first semantic corresponding to the first control instruction item based on a semantic identification technology, and determining a second control scheme based on the first semantic;
correspondingly controlling the Internet of things equipment based on a second control scheme;
if the number is larger than 1, identifying second semantics of each first control instruction item based on a semantic identification technology, determining a third control scheme based on the second semantics, and associating the third control scheme with the corresponding first control instruction item;
acquiring an input sequence of each first control instruction item input by a user;
sequencing all the first control instruction items based on the input sequence according to a preset sequencing rule to obtain a first control instruction item sequence;
sequentially traversing first control instruction items in the first control instruction item sequence, wherein each time of traversal, the traversed first control instruction items serve as second control instruction items;
analyzing the instruction type of the second control instruction item, and meanwhile, acquiring a verification strategy corresponding to the instruction type;
based on the verification strategy, verifying whether the second control instruction item is suitable, if not, determining a third control scheme associated with the second control instruction item, and taking the third control scheme as a fourth control scheme;
generating first unsuitable information corresponding to the fourth control scheme, and outputting and displaying the first unsuitable information;
if a first reply control instruction which is input by a user and corresponds to unsuitable prompt information is not received within a preset first time period, a corresponding fourth control scheme is removed from a third control scheme, and meanwhile, a corresponding second control instruction item is removed from a first control instruction item sequence;
when second control instruction items needing to be removed in the first control instruction item sequence are all removed, taking the first control instruction item sequence as a second control instruction item sequence;
determining a first control instruction item arranged at the head in the second control instruction item sequence and taking the first control instruction item as a third control instruction item, and taking the rest first control instruction items as fourth control instruction items;
determining a third control scheme associated with the third control instruction item as a fifth control scheme;
determining a third control scheme associated with the fourth control instruction item as a sixth control scheme;
establishing a scheme unsuitability confirmation library, confirming whether the fifth control scheme and the sixth control scheme are appropriate or not based on the scheme unsuitability confirmation library, if not, generating second unsuitability prompt information corresponding to the sixth control scheme, and outputting and displaying the second unsuitability prompt information;
if a second reply control instruction which is input by the user and corresponds to the second unsuitable prompt message is not received within a preset second time period, a corresponding sixth control scheme is removed from the third control scheme;
when the fourth control scheme and the sixth control scheme which need to be rejected in the third control scheme are rejected, the remaining third control scheme is rejected to serve as a seventh control scheme;
and correspondingly controlling the equipment of the Internet of things based on the seventh control scheme.
Preferably, the construction scheme is not suitable for validation libraries, including:
acquiring a preset collection node set, wherein the collection node set comprises: a plurality of collection nodes;
acquiring a plurality of unsuitable information items through a collection node;
acquiring a preset blank database, and filling unsuitable information items into the blank database;
and when all the unsuitable information items needing to be filled into the blank database are filled, taking the blank database as a scheme unsuitable confirmation database, and completing construction.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic diagram of an intelligent wireless router of the internet of things according to an embodiment of the present invention;
fig. 2 is a schematic diagram of another internet-of-things intelligent wireless router in the embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
The invention provides an intelligent wireless router of the internet of things, as shown in fig. 1, comprising:
the system comprises a first acquisition module 1, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring function information of at least one internet of things device which is docked in a user home and acquiring preference information corresponding to the user;
the manufacturing module 2 is used for manufacturing a control scheme list based on the function information and the preference information, and outputting and displaying the control scheme list;
a second obtaining module 3, configured to obtain a first control scheme selected by a user from the control scheme list;
and the control module 4 is used for correspondingly controlling the Internet of things equipment based on the first control scheme.
The working principle and the beneficial effects of the technical scheme are as follows:
after the user starts the Internet of things router, the Internet of things router generates Wifi, and the user connects each piece of Internet of things equipment to the Wifi, so that the butt joint is completed; the method comprises the steps of obtaining functional information of the internet of things equipment which is subjected to butt joint (for example, music is played regularly, light is turned on regularly, preference information of a user can be obtained based on a big data technology), and meanwhile obtaining preference information corresponding to the user (for example, the user likes to listen to light music in the morning and like to read books in a certain time interval in the evening); based on the function information and the preference information, a control scheme list is made (for example, the list contains different light music played in a plurality of time periods in the morning and different brightness of bedside reading lamps in a plurality of time periods in the evening), and output display (the light music can be sent to the smart television for display, and can also be sent to a mobile phone, a tablet and the like of a user for display) is carried out; the user selects a first control scheme from the control scheme list, and correspondingly controls the Internet of things equipment based on the first control scheme;
according to the embodiment of the invention, after the router is in butt joint with the Internet of things equipment, the function information of the Internet of things equipment and the preference information of the user are obtained, the control scheme column is manufactured based on the function information and the preference information, the control scheme column is selected by the user, the user does not need to check the specification of the Internet of things equipment, know each function one by one, and do not need to have more preference by the user, the control scheme of the Internet of things router for each Internet of things equipment is set, the convenience is greatly improved, the user experience is improved, and the method and the system are also suitable for the old people and the like.
The invention provides an intelligent wireless router of the Internet of things, wherein a first acquisition module 1 executes the following operations:
acquiring a preset docking node set, wherein the docking node set comprises: the system comprises a plurality of docking nodes, a plurality of communication nodes and a plurality of communication interfaces, wherein the docking nodes correspond to Internet of things equipment which is docked in one user home;
inquiring the access node based on a preset inquiry strategy;
acquiring at least one function information item replied by the docking node after the docking node is queried;
and integrating the acquired function information items to acquire function information and finish acquisition.
The working principle and the beneficial effects of the technical scheme are as follows:
the butt joint node is a network node which is in butt joint with the Internet of things router and the Internet of things equipment, and information interaction can be realized based on the butt joint node; when the function information is acquired, inquiring each butt joint node based on a preset inquiry strategy (such as a function information request); when the internet of things equipment receives the inquiry based on the docking node, the corresponding information, namely the function information item (for example, music is played regularly and the like) of the inquiry is replied through the docking node; integrating each function information item to obtain function information;
the embodiment of the invention is provided with a plurality of docking nodes, and the docking nodes correspond to all Internet of things equipment in the user home, so that the functional information can be conveniently obtained.
The invention provides an intelligent wireless router of the Internet of things, wherein a first acquisition module 1 executes the following operations:
acquiring the use member information corresponding to the user, wherein the use member information comprises: a plurality of first usage members and usage weights corresponding to the first usage members;
sequentially traversing the first use member, and taking the traversed first use member as a second use member during each traversal;
acquiring a preset big data node set, wherein the big data node set comprises: the big data nodes correspond to a big data platform;
acquiring an evaluation value corresponding to the big data node, acquiring a plurality of first preference information items corresponding to the second use member through the corresponding big data node if the evaluation value is greater than or equal to a preset evaluation threshold value, and giving the first preference information items a use weight corresponding to the second use member to obtain second preference information items;
and after traversing the first user member, integrating each second preference information item to obtain the preference information corresponding to the user, and finishing the acquisition.
The working principle and the beneficial effects of the technical scheme are as follows:
generally, more than one family member is in the home of the user, so when acquiring the preference information, the preference condition of each family member needs to be comprehensively acquired, and in addition, the system also needs to know which family member's preference condition is emphatically satisfied when making the control scheme list based on the preference information (for example, the old and the young exist in the home of the user, and the young hopefully satisfies the use requirement of the old);
therefore, when acquiring the preference information, acquiring the use member information (which can be input by the user) including a plurality of first use members and corresponding use weights, the larger the use weight is, the more important it is to satisfy the preference of the corresponding first use member when making the control scheme list based on the preference information; the big data node corresponds to a big data platform, and the big data platform is responsible for collecting preference conditions of different users (for example, collecting song listening records generated when a user listens to songs by using a mobile phone, a tablet, a computer and the like and collecting reading records of the user using an electronic book); however, the quality of data collected by the big data platform is not uniform, so that the big data platform needs to be evaluated in advance to obtain an evaluation value corresponding to the big data node, if the evaluation value is greater than or equal to a preset evaluation threshold (constant), which indicates that the obtaining is feasible, a first preference information item corresponding to a second user member traversed during each traversal is obtained through the corresponding big data node (for example, the user likes to read books at a certain time in the evening), a corresponding use weight is given to the first preference information item, and a second preference information item is obtained (which is convenient to determine which family member preference condition is satisfied emphatically); integrating each second preference information item to obtain preference information;
the embodiment of the invention considers the situation that more than one family member of the user needs to comprehensively obtain the preference information, and has higher applicability; a plurality of big data nodes corresponding to a big data platform are arranged, so that the comprehensiveness of acquiring preference information is improved; the big data platform is evaluated and screened in advance, so that the acquisition quality of the preference information is improved; when the preference information is integrated, the first preference information item is endowed with corresponding use weight, so that the preference condition of which family member is emphatically met when the control scheme list is made based on the preference information is conveniently determined subsequently.
The invention provides an intelligent wireless router of an Internet of things, which is used for acquiring an evaluation value corresponding to a big data node and comprises the following components:
acquiring at least one guarantor for guarantying the big data node, and acquiring a first guarantor weight for the guarantor to vouch for the big data node;
inquiring a preset guarantor-historical behavior library, and determining a plurality of historical behaviors corresponding to the guarantor;
acquiring a preset influence behavior library, and matching the historical behaviors with the influence behaviors in the influence behavior library;
if the matching is in accordance with the preset action, acquiring a first influence value corresponding to the influence action in accordance with the matching, and acquiring a action generation time point corresponding to the history action in accordance with the matching;
generating a time weight based on a generation time point according to a preset time weight generation rule;
giving a time weight to the corresponding first influence value to obtain a second influence value;
inquiring a preset influence value-down regulation amplitude library, and determining a first down regulation amplitude corresponding to the second influence value;
based on the first downward adjustment amplitude, downward adjusting a first guarantee weight corresponding to the corresponding guarantee party;
taking the first guarantee weight after all the downward adjustment is finished as a second guarantee weight;
acquiring a plurality of node events corresponding to the big data node, and analyzing the event type of the node event, wherein the event type comprises: malicious and contributing events;
when the event type of the node event is a malicious event, inputting the corresponding node event into a preset malicious detection model, performing malicious detection, and acquiring a malicious value output by the malicious detection model after the malicious detection is completed;
when the event type of the node event is a contribution event, inputting the corresponding node event into a preset contribution analysis model, performing contribution analysis, and acquiring a contribution value output by the contribution analysis model after the contribution analysis is completed;
accumulating and calculating the malicious values to obtain malicious value sums, and meanwhile determining the malicious values and corresponding second down-regulation amplitudes based on a preset malicious value sum-down-regulation amplitude library;
accumulating and calculating the contribution values to obtain a first contribution value sum, simultaneously, adjusting the first contribution value sum downwards based on a second downward adjustment amplitude, and taking the first contribution value sum after downward adjustment as a second contribution value sum;
and accumulating and calculating the second guarantee weight and the second contribution value sum to obtain an evaluation value corresponding to the big data node, and finishing the acquisition.
The working principle and the beneficial effects of the technical scheme are as follows:
under the trend that big data is gradually developed, more and more big data platforms provide services such as big data collection and analysis; however, different big data platforms have different data quality due to different composition architectures, technical means and the like of background personnel; in addition, some large data platforms may also provide spurious data; therefore, when the user preference information is acquired based on the big data platform, the big data platform needs to be evaluated, and the method is very necessary;
when the big data platform provides services, a guarantee party is required to guarantee the big data platform, so that the big data platform can be evaluated from the guarantee condition; therefore, a guarantor (e.g., a certain guaranty organization) that guarantees the big data node and a corresponding first guaranty weight are obtained, and the greater the first guaranty weight, the greater the guaranty strength (e.g., a higher guaranty amount); inquiring a preset guarantor-historical behavior library (a database storing historical behaviors corresponding to different guarantors), determining the historical behavior corresponding to the guarantor, and matching the historical behavior with the influence behavior (for example, guaranty loss exists in history) in the preset influence behavior library (a database storing influence behaviors which influence the guarantor's guaranty ability of different guarantors), if the matching is in accordance, obtaining a first influence value corresponding to the matched influence behavior, wherein the larger the first influence value is, the larger the influence on the guarantor's guaranty ability is, and meanwhile, obtaining a behavior generation time point corresponding to the matched historical behavior; generating a time weight based on the behavior generation time point according to a preset time weight generation rule (the farther the behavior generation time point is from the current time, the smaller the time weight), and giving a first influence value (the closer the influence behavior occurs, the larger the influence, and the farther the influence occurs, the smaller the influence), so as to obtain a second influence value; querying a preset influence value-descending amplitude library (descending amplitudes corresponding to different influence values are stored, the descending amplitudes are larger when the influence values are larger, the guarantee capability is smaller, and the descending guarantee weight is more, the descending amplitudes are larger), determining a first descending amplitude corresponding to a second influence value, and descending the first guarantee weight based on the first descending amplitude (for example, the descending value corresponding to the first descending amplitude is 0.7, the first guarantee weight is 100, the descending formula is 100 × 0.7, and the first guarantee weight after descending is 70); taking the first guarantee weight after all downward adjustments are completed (multiple times of continuous downward adjustments) as a second guarantee weight; starting with the record of data historically provided by the big data platform, obtaining a plurality of node events (records of data historically provided) corresponding to the big data nodes, analyzing the event types of the node events, wherein the event types are divided into malicious events (for example, obvious false data is found after data is provided) and contribution events (the provided data can be used for comprehensively determining the preference condition of a user), when the event type is a malicious event, inputting the corresponding node event into a preset malicious detection model (a pre-trained model for detecting the malicious degree of the malicious event, for example, a model generated after a machine learning algorithm is used for learning a large amount of judgment processes for manually judging the malicious degree of the malicious event), performing malicious detection, and when the malicious detection is completed, outputting a malicious value by the malicious detection model, the malicious value is larger, the greater the degree of maliciousness; when the event type is a contribution event, inputting the corresponding node event into a preset contribution analysis model (a model which is trained in advance and used for analyzing the contribution degree of the contribution event, and is the same as a malicious detection model in the training process and is not described in detail), and obtaining a contribution value, wherein the larger the contribution value is, the larger the contribution degree is; accumulating and calculating the malicious values to obtain malicious value sums; determining a second down-regulation amplitude based on a preset malicious value and a down-regulation amplitude library (different malicious values and corresponding down-regulation amplitudes are stored, the larger the malicious value sum is, the larger the down-regulation amplitude needs to be contributed, and the larger the down-regulation amplitude is); based on the second downward adjustment amplitude, performing downward adjustment on the first contribution value sum obtained by accumulating and calculating the contribution values (the same principle of performing downward adjustment on the first guarantee weight based on the first downward adjustment amplitude is not repeated), and obtaining a second contribution value sum; accumulating and calculating the sum of the second guarantee weight and the second contribution value to obtain an evaluation value;
the embodiment of the invention evaluates the big data platform, ensures the acquisition quality of the preference information, and has higher applicability under the trend of big data development; when evaluation is carried out, comprehensive evaluation is carried out starting from the guarantee condition and the historical node event condition, the setting is reasonable, and the accuracy of evaluation value acquisition is improved.
The invention provides an intelligent wireless router of an internet of things, wherein a manufacturing module 2 executes the following operations:
training a control scheme determination model;
inputting the function information and the preference information into a control scheme determination model, determining a control scheme, and acquiring a plurality of control scheme items output by the control scheme determination model after the control scheme determination model completes the determination of the control scheme;
acquiring a preset blank form, and filling all control scheme items into the blank form;
and when all the control scheme items needing to be filled into the blank form are filled, taking the blank form as a control scheme list to finish the manufacture.
The working principle and the beneficial effects of the technical scheme are as follows:
the control scheme list is manufactured based on the function information and the preference information, which is tedious, so that in order to improve the manufacturing efficiency of the control scheme list, a control scheme determining model is trained, the function information and the preference information are input into the control scheme determining model, the control scheme is determined (for example, the preference condition of which family member is satisfied is determined, a control scheme suitable for a user is comprehensively formulated), and after the control scheme determining model determines that the control scheme is finished, a control scheme item is output (for example, a certain light music is played in a certain morning in a certain time period); filling the control scheme items into a preset blank form (an electronic form, which has no content, belongs to the field of the prior art and is not described in detail), and taking the blank form as a control scheme list after all the control scheme items are filled;
according to the embodiment of the invention, when the control scheme list is manufactured based on the function information and the preference information, the control scheme determining model is trained, and the control scheme item is determined by the control scheme determining model, so that the manufacturing efficiency of manufacturing the control scheme list is improved.
The invention provides an intelligent wireless router of the Internet of things, a training control scheme determination model comprises the following steps:
obtaining a sample to be trained, wherein the sample to be trained comprises: a first determination process record recorded when the plurality of manual control scheme determinations are made;
acquiring a determining party corresponding to the first determining process record, and acquiring an empirical value corresponding to the determining party;
if the experience value is larger than or equal to a preset experience threshold value, acquiring a recording process of a first determination process record recorded by a corresponding determination party;
based on a preset standard detection strategy, carrying out standard detection on the recording process to obtain a standard value;
if the standard value is larger than or equal to a preset standard threshold value, performing quality analysis on a first determination process record recorded by a corresponding determination party based on a preset quality analysis strategy to obtain a quality value;
if the quality value is less than or equal to a preset quality threshold value, rejecting the corresponding first determination process record;
when all the first determining process records needing to be removed are removed, taking the first determining process records which are removed as second determining process records;
and performing model training according to a preset model training algorithm based on the second determination process record, and acquiring a control scheme to determine the model when the training is completed.
The working principle and the beneficial effects of the technical scheme are as follows:
the method comprises the steps that a control scheme is trained to determine a model, and process records suitable for a control scheme can be determined based on a large amount of manual work based on function information and preference information to carry out model training, however, due to the fact that the experience degree of the manual work is different, the quality of the process records is possibly poor, the process records need to be qualified, and when the process records are qualified, the process can be started from the experience degree of the manual work, the recording process standard condition, the data quality and the like;
therefore, a determiner (corresponding to manual work) corresponding to a first determination process record (a process record suitable for a control scheme is determined based on function information and preference information) is obtained, an experience value corresponding to the determiner is obtained, the greater the experience value is, the greater the experience degree is, and when the experience value is greater than or equal to a preset experience threshold (constant), a recording process (for facilitating model training, the recording process needs to be subjected to standard recording, for example, effective information for model training is recorded) recorded by the corresponding determiner, the recording process is subjected to standard detection based on a preset standard detection strategy (for example, whether the detection process is comprehensive or not, whether the process is reasonable or not, and the like), and a standard value is obtained, and the larger the standard value is, the more standard the recording process is obtained; if the specification value is larger than or equal to a preset specification threshold value (constant), performing quality analysis on a first determination process record of the determiner to obtain a quality value based on a preset quality analysis strategy (for example, verifying whether the logic of the process which determines to be suitable for the control scheme based on the function information and the preference information is correct, and the like); if the quality value is less than or equal to a preset quality threshold (constant), the recording quality is poor corresponding to the first determination process, and the recording quality is rejected; according to a preset model training algorithm (such as a machine learning algorithm) and based on the eliminated residual second determination process records, performing model training (the model training based on the sample belongs to the field of the prior art and is not repeated), and when the training is completed, acquiring a control scheme determination model after the training is completed;
according to the embodiment of the invention, the first determination process record is qualified, and the qualified second determination process record is screened out for model training, so that the training quality of the control scheme determination model is improved.
The invention provides an intelligent wireless router for the Internet of things, which is used for acquiring an experience value corresponding to a determining party and comprises the following components:
acquiring the recording time of the determining party corresponding to the first determining process record, and acquiring a determining personnel-historical experience value base corresponding to the recording time;
acquiring personnel composition information corresponding to a determining party, wherein the personnel composition information comprises: a plurality of determined persons;
determining a first historical experience value corresponding to the determined person based on the determined person-historical experience value library;
acquiring the determination weight of the determination personnel corresponding to the corresponding first determination process record;
giving a corresponding first historical experience value to determine a weight to obtain a second historical experience value;
and accumulating and calculating all the second historical experience values to obtain the experience value corresponding to the determining party.
The working principle and the beneficial effects of the technical scheme are as follows:
because the workload of determining the appropriate control scheme based on the function information and the preference information is large, the personnel of the determining party form a plurality of determining personnel, the experience enrichment condition of the determining personnel is constantly increased, and simultaneously, the participation condition of each determining personnel participating in the first determining process is different, so when the determining value corresponding to the determining party is obtained, the experience enrichment condition of each determining personnel needs to be comprehensively determined; acquiring a recording time (time when recording is started) recorded by a determining party corresponding to a first determining process, acquiring a determining person-historical experience value base (storing experience values of different determining persons at the recording time) corresponding to the recording time, and determining a first historical experience value corresponding to the determining person; acquiring the determination weight of the determination personnel corresponding to the corresponding first determination process record, wherein the larger the determination weight is, the more the determination personnel participate, the more decisions are made, and the like; giving a corresponding determination weight (multiplication) to the first historical experience value of the determined person to obtain a second historical experience value; accumulating and calculating all the second historical experience values to obtain experience values corresponding to the determination party;
according to the embodiment of the invention, when the experience value corresponding to the determining party is obtained, the comprehensive determination is carried out based on the experience enrichment condition and the participation condition of the determining personnel corresponding to the determining party, the setting is reasonable, and the accuracy of obtaining the experience value is improved.
The invention provides an intelligent wireless router for internet of things, as shown in fig. 2, further comprising:
and the voice control module 5 is used for acquiring at least one first control instruction item input by a user and correspondingly controlling the Internet of things equipment based on the first control instruction item.
The working principle and the beneficial effects of the technical scheme are as follows:
a voice receiving module (such as a microphone) is arranged in the router of the Internet of things, and a user can control the router of the Internet of things through voice; acquiring at least one first control instruction item (for example, 'I want to listen to dynamic music') input by a user, and correspondingly controlling the Internet of things equipment (for example, controlling a sound box to randomly play songs in a dynamic music menu) based on the first control instruction item;
according to the embodiment of the invention, the user can control the router of the Internet of things through voice, so that the equipment of the Internet of things is controlled, and convenience and user experience are further improved.
The invention provides an intelligent wireless router of the Internet of things, wherein a voice control module 5 executes the following operations:
counting the number of the first control instruction items;
if the number is 1, identifying a first semantic corresponding to the first control instruction item based on a semantic identification technology, and determining a second control scheme based on the first semantic;
correspondingly controlling the Internet of things equipment based on a second control scheme;
if the number is larger than 1, identifying second semantics of each first control instruction item based on a semantic identification technology, determining a third control scheme based on the second semantics, and associating the third control scheme with the corresponding first control instruction item;
acquiring an input sequence of each first control instruction item input by a user;
sequencing all the first control instruction items based on the input sequence according to a preset sequencing rule to obtain a first control instruction item sequence;
sequentially traversing first control instruction items in the first control instruction item sequence, wherein each time of traversal, the traversed first control instruction items serve as second control instruction items;
analyzing the instruction type of the second control instruction item, and meanwhile, acquiring a verification strategy corresponding to the instruction type;
based on the verification strategy, verifying whether the second control instruction item is suitable, if not, determining a third control scheme associated with the second control instruction item, and taking the third control scheme as a fourth control scheme;
generating first unsuitable information corresponding to the fourth control scheme, and outputting and displaying the first unsuitable information;
if a first return control instruction which is input by a user and corresponds to unsuitable prompt information is not received within a preset first time period, a corresponding fourth control scheme is removed from a third control scheme, and meanwhile, a corresponding second control instruction item is removed from a first control instruction item sequence;
when second control instruction items needing to be removed in the first control instruction item sequence are all removed, taking the first control instruction item sequence as a second control instruction item sequence;
determining a first control instruction item arranged at the head in the second control instruction item sequence and taking the first control instruction item as a third control instruction item, and taking the rest first control instruction items as fourth control instruction items;
determining a third control scheme associated with the third control instruction item, and taking the third control scheme as a fifth control scheme;
determining a third control scheme associated with the fourth control instruction item as a sixth control scheme;
establishing a scheme unsuitability confirmation library, confirming whether the fifth control scheme and the sixth control scheme are appropriate or not based on the scheme unsuitability confirmation library, if not, generating second unsuitability prompt information corresponding to the sixth control scheme, and outputting and displaying the second unsuitability prompt information;
if a second reply control instruction which is input by the user and corresponds to the second unsuitable prompt message is not received within a preset second time period, a corresponding sixth control scheme is removed from the third control scheme;
when the fourth control scheme and the sixth control scheme which need to be rejected in the third control scheme are rejected, the remaining third control scheme is rejected to serve as a seventh control scheme;
and correspondingly controlling the equipment of the Internet of things based on the seventh control scheme.
The working principle and the beneficial effects of the technical scheme are as follows:
generally, a user wants to control a plurality of internet of things devices (for example, when getting up in the morning, the user wants to open a curtain, a sound box plays light music, and a water heater prepares hot water), but the user needs to input a voice instruction for a plurality of times (for example, after the curtain is opened, a voice instruction of 'i want to listen to light music' is input), which is tedious, the user needs to wait at intervals, and the experience is poor; in addition, when a user wants to control a plurality of internet of things devices, particularly the old and the like, whether the working modes of the physical devices are suitable or not can not be considered comprehensively (for example, the sound box plays dynamic music, the air purifier starts a high-power purification mode, and the sound in a room is too loud, which is not suitable);
therefore, the number of the first control instruction items is counted, if the number is 1, the user only sends a voice instruction, the first semantic meaning is identified (for example, curtain opening is performed, semantic meaning identification is in the prior art and is not repeated), the second control scheme is determined, and corresponding control is performed on the equipment of the Internet of things (for example, curtain opening is performed); when the number is larger than 1, similarly, identifying the second semantic, determining a third control scheme, and associating the third control scheme with the corresponding first control instruction item; acquiring an input sequence (input sequence) of each first control instruction item input by a user, sequencing each first control instruction item based on the input sequence according to a preset sequencing rule (the voice instruction input firstly is arranged in front), and acquiring a first control instruction item sequence; sequentially traversing the first control instruction item, analyzing the instruction type (for example, an air purifier control instruction) of the traversed second control instruction item during each traversal, obtaining a verification strategy corresponding to the instruction type (for example, verifying whether the currently-started air purifier is proper), verifying whether the corresponding second control instruction item is proper (for example, if the air purifier is started for more than 5 hours before and the air quality value is mostly maintained in a good value range, the currently-started air purifier causes electricity waste and is not proper), and if not, generating first improper information corresponding to a fourth control scheme (for example, "the currently-started air purifier causes electricity waste"), and outputting and displaying (for example, voice broadcasting of an internet of things router); if a first return control instruction input by a user is not received within a preset first time period (for example: 3 seconds) (for example: the air purifier is still turned on), rejecting a corresponding second control instruction item; when the second control instruction items needing to be removed are all removed, the first control instruction item sequence is used as a second control instruction item sequence; next, whether each voice instruction conflicts directly or not is verified, the user can speak the voice instruction of the internet of things device which most wants to be controlled at first, then speak other voice instructions, and the system judges whether the voice instructions are suitable or not; establishing a scheme unsuitable confirmation library (a plurality of unsuitable matching groups are stored, such as dynamic music played by a sound box and a high-power purification mode started by an air purifier, and the like), determining whether a fifth control scheme (such as dynamic music played by the sound box and the high-power purification mode started by the air purifier) corresponding to a first control instruction item arranged at the head of a second control instruction item sequence is suitable or not (determining whether the unsuitable matching group is arranged in the unsuitable confirmation library or not, if so, the unsuitable matching group is not suitable), and if not, generating second unsuitable prompt information corresponding to the sixth control scheme (such as 'the noise in a room is too large when the air purifier is started with high power'), and outputting and displaying; if the corresponding second reply control instruction is not received within a preset second time period (for example: 2 seconds) (for example: 'the high power mode of the air purifier is still started'), removing the corresponding sixth control scheme; based on the seventh control scheme of removing the surplus, correspondingly controlling the Internet of things equipment;
according to the embodiment of the invention, a user can input a plurality of voice instructions at one time, and can speak the voice instruction of the Internet of things equipment which is most desired to be controlled at first, after the voice instruction is input, the system can determine whether the control schemes corresponding to the voice instruction are proper or not, and also determine whether the control schemes corresponding to the voice instruction are proper or not, when the control schemes corresponding to the voice instruction are determined to be not proper, improper prompt information is generated to remind the user, the user can perform forced voice control intervention, the suitability of the control of the Internet of things equipment is elastically ensured, and the system is more suitable for the old and the like.
The invention provides an intelligent wireless router of the Internet of things, which constructs a solution unsuitable confirmation library and comprises the following steps:
acquiring a preset collection node set, wherein the collection node set comprises: a plurality of collection nodes;
acquiring a plurality of unsuitable information items through a collection node;
acquiring a preset blank database, and filling unsuitable information items into the blank database;
and when all the unsuitable information items needing to be filled into the blank database are filled, taking the blank database as a scheme unsuitable confirmation database, and completing construction.
The working principle and the beneficial effects of the technical scheme are as follows:
when the construction scheme is not suitable for the confirmation library, a plurality of collecting nodes are obtained, the collecting nodes correspond to a collecting party which is not suitable for collecting the matched groups (such as playing dynamic music by a sound box, starting a high-power purification mode by an air purifier and the like), and the collecting party uploads the collected data to the collecting nodes after the collecting is finished; acquiring a plurality of unsuitable information items, namely unsuitable matching groups, through the collection nodes, and completely filling the unsuitable information items into a preset blank database to complete the construction of a solution unsuitable confirmation database;
with the increase of the types of the equipment of the Internet of things, the inappropriate work among the equipment of the Internet of things is more and more, so that the embodiment of the invention is provided with a plurality of collecting nodes for constructing the inappropriate confirmation library of the scheme, thereby improving the construction comprehensiveness and the coping capability of the inappropriate confirmation library of the scheme.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims (9)

1. The utility model provides an intelligent wireless router of thing networking which characterized in that includes:
the first acquisition module is used for acquiring the function information of at least one piece of internet of things equipment which is docked in the home of a user and acquiring the preference information corresponding to the user;
the manufacturing module is used for manufacturing a control scheme list based on the function information and the preference information and outputting and displaying the control scheme list;
the second acquisition module is used for acquiring the first control scheme selected from the control scheme list by the user;
the control module is used for correspondingly controlling the Internet of things equipment based on the first control scheme; the first obtaining module performs the following operations:
acquiring the use member information corresponding to the user, wherein the use member information comprises: a plurality of first usage members and usage weights corresponding to the first usage members;
sequentially traversing the first using members, wherein each traversal time is used for taking the traversed first using member as a second using member;
acquiring a preset big data node set, wherein the big data node set comprises: a plurality of big data nodes, the big data nodes corresponding to a big data platform;
acquiring an evaluation value corresponding to the big data node, and if the evaluation value is greater than or equal to a preset evaluation threshold value, acquiring a plurality of first preference information items corresponding to the second user member corresponding to the big data node, and giving the first preference information items a use weight corresponding to the second user member to obtain a second preference information item;
and after traversing the first user member is finished, integrating each second preference information item to obtain preference information corresponding to the user, and finishing the acquisition.
2. The intelligent wireless router of claim 1, wherein the first obtaining module performs the following operations:
acquiring a preset docking node set, wherein the docking node set comprises: the system comprises a plurality of docking nodes, a plurality of communication nodes and a plurality of communication interfaces, wherein the docking nodes correspond to Internet of things equipment which is docked in one user home;
inquiring the butt joint node based on a preset inquiry strategy;
acquiring at least one function information item replied by the docking node after the docking node is queried;
and integrating the acquired function information items to acquire function information and finish acquisition.
3. The intelligent wireless router of the internet of things as claimed in claim 1, wherein obtaining the evaluation value corresponding to the big data node comprises:
obtaining at least one guarantor that vouches for the big data node, and simultaneously obtaining a first guaranty weight at which the guarantor vouches for the big data node;
inquiring a preset guarantor-historical behavior library, and determining a plurality of historical behaviors corresponding to the guarantor;
acquiring a preset influence behavior library, and matching the historical behaviors with influence behaviors in the influence behavior library;
if the matching is in accordance with the preset action, acquiring a first influence value corresponding to the influence action in accordance with the matching, and acquiring a action generation time point corresponding to the history action in accordance with the matching;
generating a time weight based on the generation time point according to a preset time weight generation rule;
giving the time weight corresponding to the first influence value to obtain a second influence value;
inquiring a preset influence value-down regulation amplitude library, and determining a first down regulation amplitude corresponding to the second influence value;
based on the first downward adjustment amplitude, downward adjusting a first guarantee weight corresponding to the guarantee party;
taking the first guarantee weight after all downward adjustments are completed as a second guarantee weight;
acquiring a plurality of node events corresponding to the big data node, and analyzing the event type of the node event, wherein the event type comprises: malicious and contributing events;
when the event type of the node event is a malicious event, inputting the node event corresponding to the node event into a preset malicious detection model, performing malicious detection, and acquiring a malicious value output by the malicious detection model after malicious detection;
when the event type of the node event is a contribution event, inputting the corresponding node event into a preset contribution analysis model, performing contribution analysis, and acquiring a contribution value output by the contribution analysis model after the contribution analysis is completed;
accumulating and calculating the malicious value to obtain a malicious value sum, and meanwhile, determining the malicious value and a corresponding second down-regulation amplitude based on a preset malicious value sum-down-regulation amplitude library;
accumulating and calculating the contribution values to obtain a first contribution value sum, simultaneously, adjusting the first contribution value sum downwards based on the second downward adjustment amplitude, and taking the first contribution value sum after downward adjustment as a second contribution value sum;
and accumulating and calculating the second guarantee weight and the second contribution value sum to obtain an evaluation value corresponding to the big data node, and finishing the acquisition.
4. The intelligent wireless router of claim 1, wherein the production module performs the following operations:
training a control scheme determination model;
inputting the function information and the preference information into the control scheme determination model, determining a control scheme, and acquiring a plurality of control scheme items output by the control scheme determination model after the control scheme determination model completes the determination of the control scheme;
acquiring a preset blank form, and filling all the control scheme items into the blank form;
and when all the control scheme items needing to be filled into the blank form are filled, taking the blank form as a control scheme list to finish manufacturing.
5. The intelligent wireless router of claim 4, wherein training the control scheme determination model comprises:
obtaining a sample to be trained, wherein the sample to be trained comprises: a first determination process record recorded when the plurality of manual control scheme determinations are made;
acquiring a determining party corresponding to the first determining process record, and acquiring an empirical value corresponding to the determining party;
if the experience value is greater than or equal to a preset experience threshold value, acquiring a recording process of recording the first determination process record corresponding to the determination party;
based on a preset standard detection strategy, carrying out standard detection on the recording process to obtain a standard value;
if the specification value is larger than or equal to a preset specification threshold value, performing quality analysis on the first determination process record corresponding to the determiner record based on a preset quality analysis strategy to obtain a quality value;
if the quality value is less than or equal to a preset quality threshold value, rejecting the corresponding first determination process record;
when all the first determining process records needing to be removed are removed, taking the first determining process records which are removed and remained as second determining process records;
and performing model training according to a preset model training algorithm based on the second determination process record, and acquiring a control scheme to determine a model when the training is completed.
6. The intelligent wireless router of claim 5, wherein obtaining the empirical value corresponding to the determining party comprises:
acquiring the recording time of the determining party record corresponding to the first determining process record, and acquiring a determining personnel-historical experience value base corresponding to the recording time;
acquiring personnel composition information corresponding to the determination party, wherein the personnel composition information comprises: a plurality of determined persons;
determining a first historical experience value corresponding to the determined person based on the determined person-historical experience value library;
acquiring the determination weight of the determination personnel corresponding to the first determination process record;
giving the determined weight corresponding to the first historical experience value to obtain a second historical experience value;
and accumulating and calculating all the second historical experience values to obtain the experience value corresponding to the determining party.
7. The intelligent wireless router of the internet of things of claim 1, further comprising:
and the voice control module is used for acquiring at least one first control instruction item input by the user and correspondingly controlling the Internet of things equipment based on the first control instruction item.
8. The intelligent wireless router of claim 7, wherein the voice control module performs the following operations:
counting the number of the first control instruction items;
if the number is 1, identifying a first semantic corresponding to the first control instruction item based on a semantic identification technology, and determining a second control scheme based on the first semantic;
correspondingly controlling the Internet of things equipment based on the second control scheme;
if the number is larger than 1, identifying second semantics of each first control instruction item based on a semantic identification technology, determining a third control scheme based on the second semantics, and associating the third control scheme with the corresponding first control instruction item;
acquiring an input sequence of each first control instruction item input by the user;
sequencing all the first control instruction items based on the input sequence according to a preset sequencing rule to obtain a first control instruction item sequence;
sequentially traversing the first control instruction items in the first control instruction item sequence, wherein each traversal takes the traversed first control instruction items as second control instruction items;
analyzing the instruction type of the second control instruction item, and meanwhile, acquiring a verification strategy corresponding to the instruction type;
based on the verification strategy, verifying whether the second control instruction item is suitable, if not, determining the third control scheme associated with the second control instruction item, and taking the third control scheme as a fourth control scheme;
generating first unsuitable information corresponding to the fourth control scheme, and outputting and displaying the first unsuitable information;
if a first reply control instruction corresponding to the unsuitable information and input by the user is not received within a preset first time period, removing the corresponding fourth control scheme from the third control scheme, and simultaneously removing the corresponding second control command item from the first control command item sequence;
when the second control instruction items needing to be removed in the first control instruction item sequence are all removed, taking the first control instruction item sequence as a second control instruction item sequence;
determining the first control instruction item arranged at the head in the second control instruction item sequence to be used as a third control instruction item, and simultaneously using the rest first control instruction items as fourth control instruction items;
determining a third control scheme associated with the third control instruction item, and using the third control scheme as a fifth control scheme;
determining a third control scheme associated with the fourth control instruction item as a sixth control scheme;
establishing a scheme unsuitability confirmation library, confirming whether the fifth control scheme and the sixth control scheme are suitable or not based on the scheme unsuitability confirmation library, and if not, generating second unsuitability information corresponding to the sixth control scheme and outputting and displaying the second unsuitability information;
if a second reply control instruction corresponding to the second unsuitable information and input by the user is not received within a preset second time period, removing a corresponding sixth control scheme from the third control scheme;
when the fourth control scheme and the sixth control scheme which need to be rejected in the third control scheme are rejected, the remaining third control scheme which needs to be rejected is taken as a seventh control scheme;
and correspondingly controlling the Internet of things equipment based on the seventh control scheme.
9. The intelligent wireless router of claim 8, wherein constructing a solution unsuitability validation library comprises:
acquiring a preset collection node set, wherein the collection node set comprises: a plurality of collection nodes;
acquiring a plurality of unsuitable information items through the collection node;
acquiring a preset blank database, and filling the unsuitable information item into the blank database;
and when the unsuitable information items needing to be filled into the blank database are all filled, taking the blank database as a scheme unsuitable confirmation database, and completing construction.
CN202210127318.0A 2022-02-11 2022-02-11 Intelligent wireless router of thing networking Active CN114172943B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210127318.0A CN114172943B (en) 2022-02-11 2022-02-11 Intelligent wireless router of thing networking

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210127318.0A CN114172943B (en) 2022-02-11 2022-02-11 Intelligent wireless router of thing networking

Publications (2)

Publication Number Publication Date
CN114172943A CN114172943A (en) 2022-03-11
CN114172943B true CN114172943B (en) 2022-05-24

Family

ID=80489716

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210127318.0A Active CN114172943B (en) 2022-02-11 2022-02-11 Intelligent wireless router of thing networking

Country Status (1)

Country Link
CN (1) CN114172943B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115289683A (en) * 2022-06-28 2022-11-04 青岛海尔科技有限公司 Gas water heater evaluation method and device based on Internet of things and storage medium

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105827696A (en) * 2016-03-11 2016-08-03 合肥联宝信息技术有限公司 Control method, internet-of-things gateway device, and internet-of-things system
CN109067820A (en) * 2018-06-07 2018-12-21 四川斐讯信息技术有限公司 A kind of Internet of Things centralization intelligent device management method and system based on router

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030217125A1 (en) * 2002-05-15 2003-11-20 Lucent Technologies, Inc. Intelligent end user gateway device
CN101782768A (en) * 2010-02-09 2010-07-21 华南理工大学 Smart home system based on context awareness
CN102891866A (en) * 2011-07-18 2013-01-23 中兴通讯股份有限公司 IoT (Internet of Things) equipment remote monitoring method, equipment and system
CN103607353A (en) * 2013-11-19 2014-02-26 普联技术有限公司 Router, router setting method and router setting system
CN104007741B (en) * 2014-06-12 2017-01-18 深圳市智能帮科技有限公司 Plug and play type intelligent housing system
CN104166396B (en) * 2014-08-27 2016-09-28 深圳创维－Rgb电子有限公司 A kind of intelligent home furnishing control method and system
CN104915225B (en) * 2015-05-19 2018-05-29 小米科技有限责任公司 Control the method and device of smart machine
CN104991461B (en) * 2015-07-06 2018-07-06 武汉星分科技有限公司 A kind of wireless intelligent house system
US9584335B1 (en) * 2015-11-16 2017-02-28 Securifi Corporation System and method of WiFi router based presence detection and control
CN108549251A (en) * 2018-06-11 2018-09-18 武汉兴火源科技有限责任公司 A kind of the self study user custom control system and its control method of smart home
CN110958618B (en) * 2019-10-14 2021-12-14 珠海格力电器股份有限公司 Control method and device based on Bluetooth gateway, computer equipment and storage medium

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105827696A (en) * 2016-03-11 2016-08-03 合肥联宝信息技术有限公司 Control method, internet-of-things gateway device, and internet-of-things system
CN109067820A (en) * 2018-06-07 2018-12-21 四川斐讯信息技术有限公司 A kind of Internet of Things centralization intelligent device management method and system based on router

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
Automatic Device Selection and Access Policy;M. Al-Shaboti;《2019 18th IEEE 》;20191031;全文 *

Also Published As

Publication number Publication date
CN114172943A (en) 2022-03-11

Similar Documents

Publication Publication Date Title
CN102654859B (en) Method and system for recommending songs
US7696427B2 (en) Method and system for recommending music
CN102654860B (en) Personalized music recommendation method and system
CN110415681B (en) Voice recognition effect testing method and system
US20020088336A1 (en) Method of identifying pieces of music
CN107272607A (en) A kind of intelligent home control system and method
CN106991163A (en) A kind of song recommendations method based on singer's sound speciality
CN114172943B (en) Intelligent wireless router of thing networking
CN102404278A (en) Song request system based on voiceprint recognition and application method thereof
JP2007164545A (en) Preference profile generator, preference profile generation method, and profile generation program
CN111475714A (en) Information recommendation method, device, equipment and medium
CN108153810A (en) A kind of music recommends method, apparatus, equipment and storage medium
CN106302987A (en) A kind of audio frequency recommends method and apparatus
Venkatesh et al. Artificially synthesising data for audio classification and segmentation to improve speech and music detection in radio broadcast
JP2001514768A (en) Speaker certification system
CN109829075A (en) The method and apparatus that intelligence plays music
CN109582819A (en) A kind of method for playing music, device, storage medium and air-conditioning
CN108777804B (en) Media playing method and device
CN110516151A (en) Vaild act detection and personalized recommendation method
CN113707128B (en) Test method and system for full duplex voice interaction system
CN112973092B (en) Training assisting method and device, storage medium, electronic equipment and bicycle
KR20150005804A (en) Music recommendation system and method for providing user's feedback, and service apparatus applied to the same
CN114613364A (en) Sound control method and system based on voice control
CN113438516A (en) IPTV terminal law consultation method and system based on intelligent interaction
CN109377988A (en) For the exchange method of intelligent sound box, medium, device and calculate equipment

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant