CN105678319B - A kind of laundry is tactful to determine method, system and Cloud Server, terminal - Google Patents

A kind of laundry is tactful to determine method, system and Cloud Server, terminal Download PDF

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Publication number
CN105678319B
CN105678319B CN201511022252.5A CN201511022252A CN105678319B CN 105678319 B CN105678319 B CN 105678319B CN 201511022252 A CN201511022252 A CN 201511022252A CN 105678319 B CN105678319 B CN 105678319B
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clothing
clustered
grouping
washing
laundry
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CN105678319A (en
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荀晶
杨鹏
魏峰
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Hisense Visual Technology Co Ltd
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Qingdao Hisense Electronics Co Ltd
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G06F18/232—Non-hierarchical techniques
    • G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
    • G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering

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Abstract

The invention discloses a kind of laundry strategies to determine method, system and Cloud Server, terminal, main contents include: the mark that Cloud Server receives every clothing in the current more than one piece clothing to be washed that terminal determines, according to the mark of the every clothing, the attribute information of every clothing is matched from clothing database, according to the attribute information of the every clothing matched, it determines the laundry strategy for being directed to more than one piece clothing to be washed, and the laundry strategy is sent to the terminal.Identification grouping is carried out to avoid user and treat washing clothing by subjective judgement, improves the accuracy of grouping, meanwhile, improve the laundry experience of user.

Description

A kind of laundry is tactful to determine method, system and Cloud Server, terminal
Technical field
The present invention relates to smart home fields more particularly to a kind of laundry strategy to determine method, system and Cloud Server, end End.
Background technique
In existing household field, washing machine has obtained quick development and improvement as important home equipment.
Currently, user is when using washing of drum type washing machine clothing, it is contemplated that the difference of the type of clothing to be washed, firstly, needing It treats washing clothing and carries out simple manual identified grouping, then, suitable washing mode pair is selected according to the difference of grouping Clothing to be washed is washed.
However, it is this washing grouping and washing mode method of determination it is excessively cumbersome, need user to every clothing into Row discriminance analysis depends on user's subjective judgement, is easy to lead to packet error due to obscuring for identification, it is likely that will cause cannot The clothing shuffled is brought together washing, and due to the washing mode of different types of clothing difference, in turn result in the dye of clothing Color or damage.Moreover, the time of this occupancy user for washing tactful method of determination may be excessive comes with energy to be washed It washs clothing and carries out identification grouping, it cannot be guaranteed that the accuracy of grouping, moreover, user experience is poor.
Summary of the invention
The embodiment of the present invention provides a kind of laundry strategy and determines method, system and Cloud Server, terminal, to promote user Laundry experience.
The embodiment of the present invention uses following technical scheme:
A kind of determining method of laundry strategy, which comprises
The Cloud Server receives the mark of every clothing in the current more than one piece clothing to be washed that terminal determines；
The Cloud Server matches the attribute of every clothing according to the mark of the every clothing from clothing database Information, wherein the attribute information includes at least: kinds of laundry, clothing ingredient；
The Cloud Server determines according to the attribute information of the every clothing matched and is directed to more than one piece clothing to be washed Laundry strategy, wherein the laundry strategy includes at least: washing packet count and each washing grouping in comprising clothing correspondence Mark；
The laundry strategy is sent to the terminal by the Cloud Server.
Optionally, according to the attribute information of the every clothing matched, washing for more than one piece clothing to be washed is determined Clothing strategy, specifically includes:
According to the attribute information of the every clothing matched, detecting, which whether there is in more than one piece clothing to be washed, to mix The clothing washed；
If it exists, then laundry strategy is determined for the clothing that should not be shuffled；And
Clothing remaining in more than one piece clothing to be washed is believed as clothing to be clustered, and according to the attribute of clothing to be clustered Breath determines the laundry strategy for being directed to the clothing to be clustered；
If it does not exist, then using more than one piece clothing to be washed as clothing to be clustered, and according to the clothing to be clustered Attribute information determines the laundry strategy for being directed to the clothing to be clustered.
Optionally, the attribute information according to clothing to be clustered determines the laundry strategy for being directed to the clothing to be clustered, It specifically includes:
According to the attribute information of the clothing to be clustered, the total weight of the clothing to be clustered is determined；
According to the total weight and preset capacity threshold value of the clothing to be clustered, initially washing for the clothing to be clustered is determined Wash packet count N1；
Using clustering algorithm, according to the initial wash packet count N1 of the clothing to be clustered, the category of current clothing to be clustered Property information and history wash grouping set, determine be directed to the clothing to be clustered laundry strategy.
Optionally, according to the attribute information of the clothing to be clustered, the total weight of the clothing to be clustered is determined, it is specific to wrap It includes:
According to the kinds of laundry of every clothing in the clothing to be clustered, the volume of every clothing is determined；
According to the clothing ingredient of every clothing in the clothing to be clustered, the density of every clothing is determined；
According to the volume and density of every determining clothing, the total weight of the clothing to be clustered is counted.
Optionally, using clustering algorithm, according to the initial wash packet count N1 of the clothing to be clustered, current clothing to be clustered The attribute information and history of object wash grouping set, determine the laundry strategy for being directed to the clothing to be clustered, specifically include:
Grouping set is washed according to by current clothing set and history to be clustered, determines the reference of current clothing to be clustered Set, wherein the element in the clothing set to be clustered characterizes a clothing in clothing to be clustered respectively, and described to poly- Each element in class clothing set is made of the vector for characterizing each clothing ingredient in the clothing；The history washing grouping Element in set characterizes each history washing grouping respectively, and characterizes corresponding clothing comprising several in the washing grouping of each history The element of object；Element in the reference set characterizes a clothing respectively, and each element in the reference set by Characterize the vector composition of each clothing ingredient in the clothing；
From determining reference set, N1 element is randomly selected as initial cluster center；
It is true according to the reference set of the determining current clothing to be clustered and initial cluster center using clustering algorithm Surely it is directed to the laundry strategy of the clothing to be clustered.
Optionally, grouping set is washed according to by current clothing set and history to be clustered, determines current clothing to be clustered The reference set of object, specifically includes:
History washing grouping each in history washing grouping set is compared with the set to be clustered, is obtained several A first intersection；
It is determined from several described first intersections comprising the most set of element as maximum set, and judgement is described most Whether the element number for including in big collection is more than preset threshold；
If being more than, the second intersection is determined according to current clothing set and maximum set to be clustered, and hand over according to second The average vector for second intersection is calculated in collection；The average vector is combined to form reference set with maximum set It closes；
If being not above, using clothing set to be clustered as reference set.
Optionally, using clustering algorithm, according to the reference set of the determining current clothing to be clustered and initial poly- Class center determines the laundry strategy for being directed to the clothing to be clustered, specifically includes:
Step a1: initial clustering point is carried out to each element in the reference set according to the initial cluster center of selection Group obtains N1 initial packet, and calculates initial sample variance corresponding to each initial packet and this Clustering institute Corresponding initial sample variance summation；
Step a2: it according to the element for each initial packet that cluster obtains, is redefined in cluster for each initial packet The heart；
Step a3: carrying out Clustering to each element in the reference set according to the cluster centre redefined, And sample variance corresponding to each grouping is calculated, and recalculate the corresponding sample variance summation of this time cluster；
Step a4: the sample variance summation recalculated is compared with initial sample variance summation, if difference Less than the first convergency value, then go to step a5, otherwise, the grouping that will be clustered according to the cluster centre redefined For initial packet, and the a2 that gos to step；
Step a5: judging whether sample variance corresponding to each grouping obtained after cluster is greater than the second convergency value, if It is to then follow the steps a6, otherwise, go to step a7；
Step a6: determining that sample variance is greater than the grouping number N2 of the second convergency value, from this N2 grouping, randomly selects N2+1 element is as initial cluster center, and the a1 that gos to step；
Step a7: will obtained all washing packet counts and each washing grouping in comprising the corresponding mark of clothing as Laundry strategy；
Wherein, described N1, N2 are positive integer, and N1 is greater than N2.
Optionally, before executing step a7, the method also includes:
Judge whether the total weight of all clothings corresponding to element in each grouping is greater than preset capacity threshold value；
If so, it is greater than the grouping of preset capacity threshold value for the total weight of clothing, it will be corresponding to element in the grouping Clothing re-starts Clustering as clothing to be clustered；
Otherwise, go to step a7.
Optionally, the attribute information further include: clothing color；
Before executing step a7, the method also includes:
Judge whether the clothing color of clothing in each grouping meets default colour fading condition；
If so, in addition the clothing for meeting default colour fading condition is grouped；
Otherwise, step a7 is jumped directly to.
Optionally, the clothing database is established at least through one of following manner:
The attribute information of clothing is added in such a way that user is manually entered；Alternatively,
Attribute information adding clothing by way of scanning the bar code or two dimensional code of clothing；Alternatively,
The attribute information of clothing is added by way of shooting, identifying garment labels.
Optionally, the laundry strategy further include: washing mode；
The method also includes:
Washing mode in the laundry strategy is sent to washing machine, wherein the washing mode includes at least: washing Water temperature, washing intensity and washing times.
A kind of determining method of laundry strategy, comprising:
Determine the mark of every clothing in current more than one piece clothing to be washed；
The mark of the every clothing is sent to Cloud Server, so that the Cloud Server is according to the every clothing Mark, the attribute information of every clothing is matched from clothing database, according to the attribute information of the every clothing matched, Determine the laundry strategy for being directed to more than one piece clothing to be washed, wherein the attribute information includes at least: kinds of laundry, clothing Ingredient, it includes the corresponding mark of clothing that the laundry strategy, which includes at least in washing packet count and each washing grouping,；
It receives and shows the laundry strategy.
Optionally, the laundry strategy further includes washing mode；
The method also includes: the washing mode is sent to washing machine, wherein the washing mode includes at least: Wash water temperature, washing intensity and washing times.
A kind of Cloud Server, comprising:
First receiving unit, for receiving the mark of every clothing in the current more than one piece clothing to be washed that terminal determines；
Matching unit, the mark of the every clothing for being received according to first receiving unit, from clothing number According to the attribute information for matching every clothing in library, wherein the attribute information includes at least: kinds of laundry, clothing ingredient；
First determination unit, the attribute information of the every clothing for being matched according to the matching unit, determination are directed to The laundry strategy of the more than one piece clothing to be washed, wherein the laundry strategy includes at least: washing packet count and each washing It include the corresponding mark of clothing in grouping；
First transmission unit, the laundry strategy for determining first determination unit are sent to the end End.
Optionally, first determination unit, is specifically used for:
According to the attribute information of the every clothing matched, detecting, which whether there is in more than one piece clothing to be washed, to mix The clothing washed；
If it exists, then laundry strategy is determined for the clothing that should not be shuffled；And
Clothing remaining in more than one piece clothing to be washed is believed as clothing to be clustered, and according to the attribute of clothing to be clustered Breath determines the laundry strategy for being directed to the clothing to be clustered；
If it does not exist, then using more than one piece clothing to be washed as clothing to be clustered, and according to the clothing to be clustered Attribute information determines the laundry strategy for being directed to the clothing to be clustered.
Optionally, first determination unit is determined according to the attribute information of clothing to be clustered for the clothing to be clustered When the laundry strategy of object, it is specifically used for:
According to the attribute information of the clothing to be clustered, the total weight of the clothing to be clustered is determined；
According to the total weight and preset capacity threshold value of the clothing to be clustered, initially washing for the clothing to be clustered is determined Wash packet count N1；
Using clustering algorithm, according to the initial wash packet count N1 of the clothing to be clustered, the category of current clothing to be clustered Property information and history wash grouping set, determine be directed to the clothing to be clustered laundry strategy.
Optionally, first determination unit is determining the clothing to be clustered according to the attribute information of the clothing to be clustered When the total weight of object, it is specifically used for:
According to the kinds of laundry of every clothing in the clothing to be clustered, the volume of every clothing is determined；
According to the clothing ingredient of every clothing in the clothing to be clustered, the density of every clothing is determined；
According to the volume and density of every determining clothing, the total weight of the clothing to be clustered is counted.
Optionally, first determination unit is utilizing clustering algorithm, according to the initial wash of the clothing to be clustered point Group number N1, the attribute information of current clothing to be clustered and history wash grouping set, determine for the clothing to be clustered When laundry strategy, it is specifically used for:
Grouping set is washed according to by current clothing set and history to be clustered, determines the reference of current clothing to be clustered Set, wherein the element in the clothing set to be clustered characterizes a clothing in clothing to be clustered respectively, and described to poly- Each element in class clothing set is made of the vector for characterizing each clothing ingredient in the clothing；The history washing grouping Element in set characterizes each history washing grouping respectively, and characterizes corresponding clothing comprising several in the washing grouping of each history The element of object；Element in the reference set characterizes a clothing respectively, and each element in the reference set by Characterize the vector composition of each clothing ingredient in the clothing；
From determining reference set, N1 element is randomly selected as initial cluster center；
It is true according to the reference set of the determining current clothing to be clustered and initial cluster center using clustering algorithm Surely it is directed to the laundry strategy of the clothing to be clustered.
Optionally, first determination unit is washing set of packets according to by current clothing set and history to be clustered It closes, when determining the reference set of current clothing to be clustered, is specifically used for:
History washing grouping each in history washing grouping set is compared with the set to be clustered, is obtained several A first intersection；
It is determined from several described first intersections comprising the most set of element as maximum set, and judgement is described most Whether the element number for including in big collection is more than preset threshold；
If being more than, the second intersection is determined according to current clothing set and maximum set to be clustered, and hand over according to second The average vector for second intersection is calculated in collection；The average vector is combined to form reference set with maximum set It closes；
If being not above, using clothing set to be clustered as reference set.
Optionally, first determination unit is utilizing clustering algorithm, according to the determining current clothing to be clustered When reference set and initial cluster center determine the laundry strategy for being directed to the clothing to be clustered, it is specifically used for executing following step It is rapid:
Step a1: initial clustering point is carried out to each element in the reference set according to the initial cluster center of selection Group obtains N1 initial packet, and calculates initial sample variance corresponding to each initial packet and this Clustering institute Corresponding initial sample variance summation；
Step a2: it according to the element for each initial packet that cluster obtains, is redefined in cluster for each initial packet The heart；
Step a3: carrying out Clustering to each element in the reference set according to the cluster centre redefined, And sample variance corresponding to each grouping is calculated, and recalculate the corresponding sample variance summation of this time cluster；
Step a4: the sample variance summation recalculated is compared with initial sample variance summation, if difference Less than the first convergency value, then go to step a5, otherwise, the grouping that will be clustered according to the cluster centre redefined For initial packet, and the a2 that gos to step；
Step a5: judging whether sample variance corresponding to each grouping obtained after cluster is greater than the second convergency value, if It is to then follow the steps a6, otherwise, go to step a7；
Step a6: determining that sample variance is greater than the grouping number N2 of the second convergency value, from this N2 grouping, randomly selects N2+1 element is as initial cluster center, and the a1 that gos to step；
Step a7: will obtained all washing packet counts and each washing grouping in comprising the corresponding mark of clothing as Laundry strategy；
Wherein, described N1, N2 are positive integer, and N1 is greater than N2.
Optionally, before executing step a7, first determination unit is also used to:
Judge whether the total weight of all clothings corresponding to element in each grouping is greater than preset capacity threshold value；
If so, it is greater than the grouping of preset capacity threshold value for the total weight of clothing, it will be corresponding to element in the grouping Clothing re-starts Clustering as clothing to be clustered；
Otherwise, go to step a7.
Optionally, the attribute information further include: clothing color；
First determination unit is for being also used to before executing step a7:
Judge whether the clothing color of clothing in each grouping meets default colour fading condition；
If so, in addition the clothing for meeting default colour fading condition is grouped；
Otherwise, step a7 is jumped directly to.
Optionally, the clothing database is established at least through one of following manner:
The attribute information of clothing is added in such a way that user is manually entered；Alternatively,
Attribute information adding clothing by way of scanning the bar code or two dimensional code of clothing；Alternatively,
The attribute information of clothing is added by way of shooting, identifying garment labels.
Optionally, the laundry strategy further include: washing mode；
First transmission unit is also used to the washing mode in the laundry strategy being sent to washing machine, wherein institute It states washing mode to include at least: washing water temperature, washing intensity and washing times.
A kind of terminal, comprising:
Second determination unit, for determining the mark of every clothing in current more than one piece clothing to be washed；
Second transmission unit, for the mark of the every clothing to be sent to Cloud Server, so that the cloud service Device matches the attribute information of every clothing, according to what is matched according to the mark of the every clothing from clothing database The attribute information of every clothing determines the laundry strategy for being directed to more than one piece clothing to be washed, wherein the attribute information is at least Include: kinds of laundry, clothing ingredient, the laundry strategy includes at least: including in washing packet count and each washing grouping The corresponding mark of clothing；
Second receiving unit, for receiving and showing the laundry strategy.
Optionally, the laundry strategy further include: washing mode corresponding with each washing grouping；
Second transmission unit is also used to the washing mode being sent to washing machine, wherein the washing mode is extremely It less include: washing water temperature, washing intensity and washing times.
A kind of laundry policy determination system, comprising: terminal, Cloud Server and washing machine；
Wherein, the terminal is used to determine the mark of every clothing in current more than one piece clothing to be washed；And it will be every described The mark of clothing is sent to Cloud Server；And it receives and shows laundry strategy；
The Cloud Server is used to receive the mark of every clothing in the current more than one piece clothing to be washed that the terminal determines； According to the mark of the every clothing, the attribute information of every clothing is matched from clothing database, wherein the attribute letter Breath includes at least: kinds of laundry, clothing ingredient；According to the attribute information of every clothing, determines and be directed to more than one piece clothing to be washed The laundry strategy of object, wherein the laundry strategy includes at least: including clothing pair in washing packet count and each washing grouping The mark answered, and washing mode corresponding with each washing grouping；The laundry strategy is sent to the terminal；
The use in washing machine is in the washing mode for receiving the Cloud Server or terminal transmission.
According to the technical solution of the present invention, Cloud Server is treated washing clothing according to the clustering algorithm of storage and is grouped, And determine the washing mode of each group after washing clothing grouping, determining washing strategy is sent eventually by Cloud Server To terminal, washing machine can also be sent to by terminal by terminal display to user, thus, it realizes between washing machine It connects control or directly controls, promote user experience.Moreover, the laundry strategy determined according to clustering algorithm of Cloud Server more subject to Really, the problems such as can be avoided dyeing caused by shuffling as clothing, damaging, moreover, the clothing database can be according to user's Demand real-time update, and record storage is carried out to the modification for the laundry strategy that user carries out, as a result, according to possessed self study Function, can fully consider user demand, rationally determine Clustering information.In addition, the program can also be for determination Clothing to be washed in each grouping determines reasonable according to the characteristic of the most material of content in the grouping for each grouping Washing mode, thus, optimal washing strategy is shown for user, promotes the usage experience and demand of user.
Detailed description of the invention
To describe the technical solutions in the embodiments of the present invention more clearly, make required in being described below to embodiment Attached drawing is briefly introduced, it should be apparent that, drawings in the following description are only some embodiments of the invention, for this For the those of ordinary skill in field, without any creative labor, it can also be obtained according to these attached drawings His attached drawing.
Fig. 1 strategy of doing washing involved in the embodiment of the present invention determines the system architecture schematic diagram protected of scheme；
Fig. 2 (a) is that the laundry strategy that the embodiment of the present invention one provides determines method schematic diagram；
Fig. 2 (b) is the method schematic diagram for the Clustering that the embodiment of the present invention one provides；
Fig. 3 is that laundry strategy provided by Embodiment 2 of the present invention determines method schematic diagram；
Fig. 4 is a kind of structural schematic diagram for Cloud Server that the embodiment of the present invention three provides；
Fig. 5 is a kind of structural schematic diagram for terminal that the embodiment of the present invention four provides.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with attached drawing to the present invention make into It is described in detail to one step, it is clear that described embodiments are only a part of the embodiments of the present invention, rather than whole implementation Example.Based on the embodiments of the present invention, obtained by those of ordinary skill in the art without making creative efforts All other embodiment, shall fall within the protection scope of the present invention.
In embodiments of the present invention, in order to provide reasonable laundry strategy for user, using Cloud Server and terminal, And the system of washing machine composition carries out information exchange, specifically, the mark of clothing to be washed is determined by terminal, it then, will These marks are sent to Cloud Server, and Cloud Server is according to the mark of every clothing to be washed from the clothing database of itself Allot the attribute information of corresponding clothing, and the attribute information according to clothing to be washed is according to clustering algorithm, it will clothing be washed Carry out Clustering, wherein, can also be according to the laundry rule of setting, it is impossible to mixed before or after carrying out clustering algorithm The clothing washed independently is grouped, and then, is sent to terminal for finally obtained grouping information as washing strategy, and pass through terminal exhibition Show to user so that clothing to be washed rationally is grouped by user according to the washing strategy determined, thus, it is possible to avoid due to The problems such as dyeing caused by clothing shuffles, damage, moreover, the clothing database can real-time update according to the demand of user, and Carrying out record storage to the modification for the laundry strategy that user carries out can be abundant as a result, according to the function of possessed self study Consider user demand, rationally determines Clustering information.In addition, the program can also be for be washed in determining each grouping Clothing is washed, according to the characteristic of the most material of content in the grouping, determines reasonable washing mode for each grouping, thus, it is User shows optimal washing strategy, promotes the usage experience and demand of user.
Technical solution according to the present invention is described in detail below by specific embodiment, the present invention include but It is not limited to following embodiment.
As shown in Figure 1, the system architecture that laundry strategy determines that scheme is protected involved in the embodiment of the present invention is shown It is intended to, includes: terminal 11, Cloud Server 12 and washing machine 13 in the laundry policy determination system, wherein terminal 11 can be The terminal devices such as mobile phone, computer, pad, further, the terminal 11 have network module, can connect with Cloud Server 12 logical Letter；The Cloud Server 12 can be the core web server equipment with distributed computing function, or in local area network Server apparatus, be mainly used for receive clothing attribute information, and store and update clothing database in clothing category Property information；Under normal circumstances, user goes control washing machine to carry out washing operation by the laundry strategy that terminal 11 is shown, meanwhile, Washing machine 13 also has network module, can connect Cloud Server 12, thus, (dotted line institute is directly controlled by Cloud Server 12 Show)；Or be connected in local area network with the terminal 11, by the control of terminal 11.In fact, washing machine 13 can also be accompanied with display Screen, with facilitate user directly pass through washing machine input clothing to be washed attribute information or scanning obtain the category of clothing to be washed Property information.
Embodiment one:
As shown in Fig. 2 (a), determine that method schematic diagram, this method are main for the laundry strategy that the embodiment of the present invention one provides The following steps are included:
Step 21: receiving the mark of every clothing in the current more than one piece clothing to be washed that terminal determines.
Step 22: according to the mark of every clothing, the attribute information of every clothing is matched from clothing database.
Wherein, the attribute information includes at least: kinds of laundry, clothing ingredient.
Using the mark of determining clothing, the kinds of laundry, clothing of every clothing are successively matched from clothing database The attribute informations such as ingredient.
Wherein, clothing database can be located in Cloud Server, in order to carry out cloud company according to the service condition of user It connects and updates.The attribute information of more than one piece clothing is stored in clothing database, comprising: kinds of laundry (underwear, jacket, trousers, skirt Son, housing, socks, bedding, shoes, cap, packet, other), clothing mark, clothing ingredient (clothing web types and place Percentage), washing water temperature, washing times etc..
Optionally, which the operation such as can be added according to the demand of user, delete, modifying, inquiring.Example Such as: the attribute information of new clothing is added, alternatively, for clothing mark or clothing ingredient in the attribute information of the clothing added It modifies.Wherein, the present invention provides three kinds of main attribute information addition manners:
Mode one is added in such a way that user is manually entered；For example, firstly, inputting the category of related clothing at the terminal Property information, or select from the attribute information list of clothing the attribute information of related clothing, be then sent to Cloud Server into Row classification storage.
Mode two, being added by way of scanning the bar code or two dimensional code of clothing, for example, utilizing the scanning function of terminal Can, the bar code or two dimensional code that carry on clothing are scanned, by parsing two dimensional code or bar code information from network retrieval Or the attribute information of related clothing is crawled, it is then sent to Cloud Server and carries out classification storage.
Mode three is added by way of shooting, identifying garment labels, for example, can be shot by the camera of terminal Label on clothing extracts the attribute information of related clothing using image recognition analytic technique, be then sent to Cloud Server into Row classification storage.
The present invention is not defined specific addition manner.
Step 23: according to the attribute information of the every clothing matched, determining washing for more than one piece clothing to be washed Clothing strategy.
Wherein, the laundry strategy includes at least: corresponding comprising clothing in washing packet count and each washing grouping Mark, and washing mode corresponding with each washing grouping.
Optionally, since the quality of clothing and type are different, some clothings should not shuffle, for example, according to user Personal habits, shoes should not shuffle with other clothings, and packet should not also be shuffled with other clothings, can not be shuffled with shoes, with Exempt to damage personal clothing in actual laundering process and pollute.In embodiments of the present invention, step 23 can have It is following steps that body, which executes:
The first step detects in more than one piece clothing to be washed according to the attribute information of the every clothing matched with the presence or absence of not The clothing preferably shuffled；If it exists, then second step is jumped to, otherwise, jumps to third step.
Wherein, the clothing that should not be shuffled and must individually wash are as follows: underwear, bedding, shoes, packet, these four types of clothings It is not recommended that shuffled with other clothings, also it is not recommended that shuffling between each other, preferably individually washing, such as: more than one piece underwear washs simultaneously, Or multiple pairs of shoes washs simultaneously.
Optionally, in embodiments of the present invention, the clothing that should not be shuffled can also include: the clothing to fade.Wherein, it fades Clothing can know from garment labels, user can also be according to oneself according to various ways identification, under normal circumstances Demand carry out edit definition, can also according to ingredient speculate assert.Such as: for a pile clothing to be washed, wherein color compared with The deep clothing that can be assumed that be easy to fade, the shallower clothing that can be assumed that be not easy to fade of color.For being easy These clothings can be individually grouped by the clothing of color, and determine suitable washing mould according to the material of these clothings and type Formula.
In actual detection process, can according to the attribute information of each part clothing, such as: according to the title of clothing detect With the presence or absence of the clothing that should not be shuffled in clothing.Furthermore it is also possible to therefrom be matched according to the color of clothing greater than colour gamut threshold value Clothing, and be grouped individually washing.Specifically testing conditions can flexible setting according to the demand of user.
Second step, the clothing for that should not shuffle determine laundry strategy；And by clothing remaining in more than one piece clothing to be washed Object is as clothing to be clustered.
Specifically, for the clothing that should not be shuffled, laundry strategy is individually washing.Then, it should not be shuffled according to this Clothing type, determine washing mode and washing water temperature etc..Such as: more than one piece underwear is independent independently of other kinds of clothing Washing, it is contemplated that the frivolous softness of underwear, washing mode should be adjusted to washing times it is less, washing intensity it is smaller and It is moderate to wash water temperature.
Third step, using more than one piece clothing to be washed as clothing to be clustered.
4th step determines the laundry strategy for being directed to the clothing to be clustered according to the attribute information of the clothing to be clustered.
Optionally, in embodiments of the present invention, the 4th step can specifically execute are as follows: according to the attribute of the clothing to be clustered Information determines the total weight of the clothing to be clustered；According to the total weight and preset capacity threshold value of the clothing to be clustered, really The initial wash packet count N1 of the fixed clothing to be clustered；Using clustering algorithm, according to the initial wash of the clothing to be clustered Packet count, the attribute information set of current clothing to be clustered and history wash grouping set, determine and are directed to the clothing to be clustered The laundry strategy of object.
Through the above scheme, when to determine washing strategy wait wash clothing, considering whether to exist first should not be shuffled Clothing, specifically can be according to the type of clothing or the color of clothing as testing conditions.It is thus possible to should not tentatively shuffle Clothing pick out, due to these grouping conditions it is relatively fixed, such as: assuming that determine wait wash, there are two pairs of shoes in clothing Son, a packet, three underwears, n part sweater, m part trousers and housing, q part skirt, p part T-shirt, wherein have one in three underwears For black, other two pieces are white (assuming that defining black at this time is colour fading color).So, scheme is primarily determined according to above-mentioned, Two pairs of shoes, packet, three underwears must be washed individually.I.e. two pairs of shoes can be divided to grouping 1, and a packet can be divided to 2 are grouped, the black underwear and white underwear in three underwears can be respectively divided into grouping 3 and be grouped 4.In addition, remaining n part Sweater, m part trousers and housing, q part skirt, p part T-shirt are as clothing to be clustered.
Optionally, it according to the attribute information of the clothing to be clustered, determines the total weight of the clothing to be clustered, can have Body determines the volume of every clothing according to the kinds of laundry of every clothing in the clothing to be clustered；According to the clothing to be clustered The clothing ingredient of every clothing, determines the density of every clothing in object；According to the volume and density of every determining clothing, statistics The total weight of the clothing to be clustered.
Specifically, in clothing database, the approximate volume or capacity of each type clothing are pre-defined, thus, it can According to the volume Vi of the type of every clothing estimation clothing；Further, each material contained according to clothing and each material Matter percentage estimates the density p i of every clothing；It is thus possible to estimate the weight mi of every clothing to be clustered.Then, The total weight M of all clothings to be clustered is counted again.
In fact, the total weight of clothing to be clustered why is calculated, it is contemplated that washing machine has certain washing capacity, i.e., most Big washing kilogram number T.After the total weight for calculating clothing to be clustered, so that it may according to washing capacity T, primarily determine to poly- The initial wash packet count N1 of class clothing.
In embodiments of the present invention, in order to which more accurately micro- clothing to be clustered determines suitable washing strategy, most Mainly determine that packet count, the present invention carry out Clustering to clothing to be clustered using algorithm, then judgement cluster obtains each The clustering convergence situation of a grouping finally determines grouping information.Due to being related to clustering algorithm, it is thus necessary to determine that used in cluster Feature, in embodiments of the present invention, it is contemplated that washing clothing when washing is mainly distinguished with clothing material, such as: wool Clothing and cotton clothing can distinguish washing, and since wool clothing is more soft, it is excessive should not to wash intensity, and cotton clothing can With the washing mode excessive using intensity.
Therefore, clustering algorithm according to the present invention mainly using this attribute information of clothing ingredient as cluster feature to Amount.Firstly, the clothing ingredient of all clothings to be clustered of statistics, each element as feature vector.For example, clothing to be clustered In, it altogether include 10 class materials, respectively S1-S10.For every clothing to be clustered, determine the clothing of the clothing to be clustered at Divide, i.e. the feature vector of the clothing to be clustered are as follows:
Ck=(x1, x2, x3, x4……x10)
Wherein, xiThe ingredient is indicated in clothing percentage, if xiIt is 0, then it represents that the material is not contained in the clothing. To which, every clothing to be clustered can be indicated with Ck.Preferably, it is each determine washing strategy when, can to clothing at The classification number divided carries out flexible setting selection, however it is not limited to 10 class material of the present invention.
Optionally, scheme is mainly illustrated by taking K-MEANS clustering algorithm as an example the present invention in detail below, the advantage is that It is high-efficient, but it is more for sample in the case where, calculated result may be not fully up to expectations, due to the usage scenario in the present invention Middle sample (clothing i.e. to be clustered) is not too big, so, just correspondingly evade its disadvantage.Certainly, if there is more powerful Computing cluster, can also be higher using other efficiency, and more accurate clustering algorithm.
Optionally, for clothing to be clustered, grouping scheme can be executed according to the following steps:
Firstly, washing grouping set according to by current clothing set and history to be clustered, current clothing to be clustered is determined Reference set, wherein the element in the clothing set to be clustered characterizes a clothing in clothing to be clustered, and institute respectively The each element stated in clothing set to be clustered is made of the vector for characterizing each clothing ingredient in the clothing；The history is washed It washs the element in grouping set and characterizes each history washing grouping respectively, and include several characterizations in the washing grouping of each history The element of corresponding clothing；Element in the reference set characterizes a clothing respectively, and each member in the reference set Element is made of the vector for characterizing each clothing ingredient in the clothing.
Specifically, the collection of current clothing to be clustered is combined into A={ C1, C2, C3 ... Ck }, wherein each element is every in A Vector composed by each clothing ingredient of part clothing；History washs grouping set H={ Q1, Q2, Q3 ... Qr }, wherein in H Each element is that Qr={ C1, C2, C3 ... Ck } can use history and wash when the member in the element and A in Qr is known as intersection It washs grouping set H and carries out auxiliary cluster.
Optionally, in order to reduce cluster complexity, accelerate clustering algorithm, improve the accuracy of grouping, history can be quoted History in data washs grouping set, can specifically execute are as follows:
History is washed each element Qr in grouping set H to be compared with current clothing set A to be clustered respectively, is obtained To several intersections Br, and the set B most comprising element (clothing i.e. to be clustered) is determined from intersection Br；And judge set B In include element number whether more than 0.2*k, i.e., 0.2 times of clothing total quantity to be clustered；
If being more than, need further to execute:
Intersection P is determined according to current clothing set A and set B to be clustered, and average vector Cp is calculated according to intersection P, Such as: current clothing set A={ C1, C2, C3 ... Ck } to be clustered, set B={ C1, C2, C3 }, then intersection P=C1, C2, C3 }, it obtains average vector CP, then, fills into the supplementary set of set A and set B, i.e., determining reference set A '=Cp, Cp, Cp, C4 ... Ck }, and the a2 that gos to step.
If being not above, by set A as reference set A ', and the a2 that gos to step.
It include n+m+p+q element, i.e. n+m+p+q in the reference set A ' that determines it is assumed that after step a1 Part clothing, i.e. k=n+m+p+q.
Then, from determining reference set, N1 element is randomly selected as initial cluster center.
Specifically, it is contemplated that the estimation of total weight is carried out to clothing to be clustered before, so that it is determined that initial packet number N1, at this point it is possible to which number of the initial packet number N1 as initial cluster center, carries out initial clustering.For example, from reference set A ' 3 elements of middle selection are as initial cluster center, respectively C2, C3, C7.
Clustering scheme is introduced below by specific embodiment.In conjunction with shown in Fig. 2 (b), the cluster point Group mainly comprises the steps that
Step a1: initial clustering point is carried out to each element in the reference set according to the initial cluster center of selection Group obtains N1 initial packet, and calculates initial sample variance corresponding to each initial packet and this Clustering institute Corresponding initial sample variance summation.
Specifically, in step a1, for remaining n+m+p+q-3 part clothing, each element distance three is calculated separately The Euclidean distance (its embodiments is similarity, and the nearlyr expression similarity of distance is higher) of initial cluster center, and will The smallest element of distance apart from initial cluster center is divided to this apart from corresponding cluster centre.Such as: it is directed to Elements C 1, point Not Ji Suan C1 the distance d (2) apart from initial cluster center C2, C3, C7, d (3), d (7) respectively C1 is drawn if d (3) is minimum Divide to C3 institute in a packet.Similar, for the other elements other than initial cluster center C2, C3, C7, successively gathered Class divides, and obtains three initial packet U (w1), U (w2), U (w3).Wherein, w1+w2+w3=n+m+p+q, i.e., grouping U (w1) with C2 is that initial cluster center includes altogether w1 element, and grouping U (w2) includes w2 by initial cluster center of C3 altogether Element, it includes w3 element that grouping U (w3), which is had altogether using C7 as initial cluster center,.
Meanwhile for each initial packet, calculate initial sample variance corresponding to each initial packet, i.e., it is each initial Each element (removing initial cluster center) Euclidean distance quadratic sum in grouping, specifically, for the initial sample side of U (w1) Poor Y (w1), the initial sample variance Y (w2) of U (w2), U (w3) initial sample variance Y (w3).And corresponding to this cluster Initial sample variance summation, i.e. Y (w1)+Y (w2)+Y (w3).
Step a2: it according to the element for each initial packet that cluster obtains, is redefined in cluster for each initial packet The heart.
Specifically, for each initial packet U (w1), U (w2), U (w3), again according to the element in each initial packet Determine the cluster centre of each grouping.Such as: firstly, calculating the average vector of each initial packet, then, calculate separately each In initial packet, distance of the other elements apart from the average vector, and determine that the corresponding element of minimum range is this initial point The cluster centre of group.
Step a3: carrying out Clustering to each element in the reference set according to the cluster centre redefined, And sample variance corresponding to each grouping is calculated, and recalculate the corresponding sample variance summation of this time cluster.
Specifically, according to cluster centre C2, C5, the C8 redefined, three grouping U (w4), U (w5), U (w6) are obtained, Wherein, w4+w5+w6=n+m+p+q, i.e., it includes w4 element that grouping U (w4), which is had altogether using C2 as initial cluster center, is grouped U (w5) being had altogether using C5 as initial cluster center includes w5 element, and grouping U (w6) includes altogether using C8 as initial cluster center There is w6 element.
For the initial sample variance Y (w4) of U (w4), the initial sample variance Y (w5) of U (w5), U (w6) initial sample Variance Y (w6).And the initial sample variance summation that this cluster is corresponding, i.e. Y (w4)+Y (w5)+Y (w6).
Step a4: the sample variance summation recalculated is compared with initial sample variance summation, if difference Less than the first convergency value, then go to step a5, otherwise, the grouping that will be clustered according to the cluster centre redefined For initial packet, and the a2 that gos to step.
Y (w4)+Y (w5)+Y (w6) and Y (w1)+Y (w2)+Y (w3) is compared, if difference is less than the first convergency value ED1, then it represents that the Clustering has been restrained, i.e. the accuracy of the grouping clustered in step a3 is higher, then can be into one Step executes step a5；If difference is greater than the first convergency value ED1, then it represents that the Clustering is also not converged, in each Clustering Similarity have relatively large deviation, need further Clustering, then will be clustered to obtain according to the cluster centre that redefines Be grouped into initial packet, and re-execute the steps a2 until convergence.
Step a5: judging whether sample variance corresponding to each grouping obtained after cluster is greater than the second convergency value, if It is to then follow the steps a6, otherwise, go to step a7.
In embodiments of the present invention, in order to verify every group element similarity, obtained after can further judging cluster Whether sample variance corresponding to each grouping is greater than the second convergency value ED2, if so, illustrating the similarity of each grouping not Height needs further to execute step a6；If it is not, then illustrate that the similarity of each grouping is very high, the Clustering be it is believable, then Step a7 can be executed.
Step a6: determining that sample variance is greater than the grouping number N2 of the second convergency value, from this N2 grouping, randomly selects N2+1 element is as initial cluster center, and the a1 that gos to step.
If the similarity of each grouping is not high, need to further determine that point of the sample variance greater than the second convergency value ED2 The number of group, such as: if finally the sample variance of determining grouping U (w4), U (w5), middle grouping U (w5) of U (w6) is greater than the second receipts Value ED2 is held back, then shows that grouping U (w5) cannot be clustered individually always, then redefines initial cluster center number, i.e. 3-1=2 It is a, and 3 elements are randomly selected as initial cluster center from this 2 groupings, and the a1 that gos to step.
Step a7: using element information in obtained all groupings and each grouping as laundry strategy；Wherein, described N1, N2 are positive integer, and N1 is greater than N2.Specifically, it is carried out clustering finally obtained grouping according to above-mentioned steps a1-a10, Determine laundry strategy, wherein the laundry strategy may include the grouping number that cluster obtains, the element of each grouping.
Optionally, before executing step a7, it can also judge the total of all clothings corresponding to element in each grouping Whether weight is greater than preset capacity threshold value, if so, being greater than the grouping of preset capacity threshold value for the total weight of clothing, by this point Clothing corresponding to element re-starts Clustering as clothing to be clustered in group；Otherwise, go to step a7.
After determining the sample variance for clustering obtained each grouping convergence, then further judge first in each grouping Clothing corresponding to element, and the total weight of all clothings in the grouping is counted, then judge whether to be greater than preset capacity threshold value T, If so, for clothing total weight be greater than preset capacity threshold value grouping, using clothing corresponding to element in the grouping as to Cluster clothing re-starts Clustering, and otherwise, go to step a7.Wherein, the corresponding initial wash grouping of grouping U (w6) Number can be determined according to the ratio relation of its total weight and preset capacity threshold value.
Optionally, the attribute information further include: clothing color；Before executing step a7, this method can also judge Whether the clothing color of clothing meets default colour fading condition in each grouping；If so, the clothing that default colour fading condition will be met In addition it is grouped；Otherwise, step a7 is jumped directly to.
It should be noted that in embodiments of the present invention, to carry out judging that clothing is again after Clustering to clothing No colour fading preferably, can guarantee to mark off less grouping during subsequent Clustering in this way.
It optionally, is that after obtaining grouping information, can also further determine that each grouping in example in the present invention Washing mode specifically for each grouping, counts the material type of all clothings in the grouping, determines shared in the grouping The maximum material of ratio refers to material as the washing of the grouping, then determines optimal washing time according to the characteristic of the material Number, washing intensity and washing water temperature.Such as: the clothing for including in grouping U (w6) is essentially all woollen sweater, it is determined that this point The washing of group is wool with reference to material, and wool is more soft, and washing times can be 2 times, washing intensity for low-intensity (or Person is divided into 1-n grade according to washing intensity), washing water temperature is 40 °.
Step 24: laundry strategy is sent to terminal.
After Cloud Server determines laundry strategy, the laundry strategy is saved into clothing database, meanwhile, it will wash The laundry strategy such as grouping information, washing mode is sent to terminal, and shows user, is carried out with indicating that user treats washing clothing Reasonable classification, and be that each grouping adjusts suitable washing times, washing intensity and washing water according to determining washing mode Temperature.To realize purpose that is water-saving, energy saving and reducing washing damage caused by clothing.In addition, user can also be to terminal The laundry strategy of displaying is modified, and modified laundry policy synchronization to Cloud Server is realized clothing number by terminal According to the update in library.
Optionally, the Cloud Server in the embodiment of the present invention can also real-time update itself storage clothing database and Therefore historical packet data library enables the clustering algorithm to achieve the purpose that self study.
Optionally, Cloud Server confirms after the strategy that will do washing is sent to terminal by user, if washing machine and terminal It not in same local area network, then can not be communicated with washing machine, at this point, terminal can be by the laundry plan after user confirms Cloud Server is slightly returned to, then the washing mode in strategy of doing washing is sent to laundry according to the instruction of terminal by Cloud Server Machine, wherein the washing mode includes at least: washing water temperature, washing intensity and washing times.To without terminal exhibition Show to user, directly controlling washing machine is to be grouped corresponding clothing accordingly to be adjusted to optimal washing mode, thus more preferably intelligence Energyization, facilitation.
Embodiment two:
Belong to same inventive concept with above-described embodiment one, second embodiment of the present invention provides a kind of tactful determination sides of laundry Method, this method are illustrated by taking terminal side as an example, specifically, as shown in figure 3, this method mainly comprises the steps that
Step 31: determining the mark of every clothing in current more than one piece clothing to be washed.
The mark of clothing can negotiate the clothing ID or symbol that define for terminal and Cloud Server.
Step 32: the mark of the every clothing being sent to Cloud Server, so that the Cloud Server is according to The mark of every clothing matches the attribute information of every clothing from clothing database, according to the every clothing matched Attribute information determines the laundry strategy for being directed to more than one piece clothing to be washed, wherein the attribute information includes at least: clothing Type, clothing ingredient, the laundry strategy include at least: corresponding comprising clothing in washing packet count and each washing grouping Mark, and washing mode corresponding with each washing grouping.
Step 33: receiving and show the laundry strategy.
Optionally, laundry strategy further includes washing mode, then terminal, will also be described after receiving and showing laundry strategy Washing mode is sent to washing machine, wherein washing mode includes at least: washing water temperature, washing intensity and washing times.
Embodiment three:
Belong to same inventive concept with above-described embodiment one, the embodiment of the invention also provides a kind of Cloud Servers, such as Fig. 4 Shown, which specifically includes that
First receiving unit 41, for receiving the mark of every clothing in the current more than one piece clothing to be washed that terminal determines. Matching unit 42, the mark of the every clothing for being received according to the first receiving unit 41, matches from clothing database The attribute information of every clothing, wherein attribute information includes at least: kinds of laundry, clothing ingredient, color.First determination unit 43, the attribute information of the every clothing for being matched according to matching unit 42 determines the laundry for being directed to more than one piece clothing to be washed Strategy, wherein laundry strategy includes at least: including the corresponding mark of clothing in washing packet count and each washing grouping, with And washing mode corresponding with each washing grouping.First transmission unit 44 is washed for determine the first determination unit 43 Clothing strategy is sent to the terminal.
Optionally, the first determination unit 43 is specifically used for according to the attribute information of every clothing matched, described in detection With the presence or absence of the clothing that should not be shuffled in more than one piece clothing to be washed；If it exists, then laundry is determined for the clothing that should not be shuffled Strategy；And using clothing remaining in more than one piece clothing to be washed as clothing to be clustered, and according to the attribute of clothing to be clustered Information determines the laundry strategy for being directed to the clothing to be clustered；If it does not exist, then using more than one piece clothing to be washed as to poly- Class clothing, and according to the attribute information of the clothing to be clustered, determine the laundry strategy for being directed to the clothing to be clustered.
Optionally, the first determination unit 43 is determined according to the attribute information of clothing to be clustered for the clothing to be clustered Laundry strategy when, specifically for the attribute information according to the clothing to be clustered, determine the total weight of the clothing to be clustered； According to the total weight and preset capacity threshold value of the clothing to be clustered, the initial wash packet count of the clothing to be clustered is determined N1；Using clustering algorithm according to the initial wash packet count N1 of the clothing to be clustered, the attribute information of current clothing to be clustered Set and history wash grouping set, determine the laundry strategy for being directed to the clothing to be clustered.
Optionally, the first determination unit 43 is in the total weight for determining clothing to be clustered according to the attribute information of clothing to be clustered When, specifically for the kinds of laundry according to every clothing in the clothing to be clustered, determine the volume of every clothing；According to described The clothing ingredient of every clothing, determines the density of every clothing in clothing to be clustered；According to the volume of every determining clothing and Density counts the total weight of the clothing to be clustered.
Optionally, the first determination unit 43 is utilizing clustering algorithm, is grouped according to the initial wash of the clothing to be clustered Number N1, the attribute information of current clothing to be clustered and history wash grouping set, determine washing for the clothing to be clustered When clothing strategy, it is specifically used for: washs grouping set according to by current clothing set and history to be clustered, determines current to be clustered The reference set of clothing, wherein the element in the clothing set to be clustered characterizes a clothing in clothing to be clustered respectively, And each element in the clothing set to be clustered is made of the vector for characterizing each clothing ingredient in the clothing；It is described to go through Element in history washing grouping set characterizes each history washing grouping respectively, and includes several in the washing grouping of each history Characterize the element of corresponding clothing；Element in the reference set characterizes a clothing respectively, and every in the reference set A element is made of the vector for characterizing each clothing ingredient in the clothing；From determining reference set, N1 are randomly selected Element is as initial cluster center；Using clustering algorithm, according to the reference set of the determining current clothing to be clustered and Initial cluster center determines the laundry strategy for being directed to the clothing to be clustered.
First determination unit 43 is washing grouping set according to by current clothing set and history to be clustered, determines current When the reference set of clothing to be clustered, it is specifically used for washing history each history washing in grouping set and is grouped with described to poly- Class set is compared, and obtains several the first intersections；The collection most comprising element is determined from several described first intersections Cooperation is maximum set, and judges whether the element number for including in the maximum set is more than preset threshold；If being more than, root The second intersection is determined according to current clothing set and maximum set to be clustered, and is calculated according to the second intersection for described the The average vector of two intersections；The average vector is combined to form reference set with maximum set；It, will be to poly- if being not above Class clothing set is as reference set.
Optionally, the first determination unit 43 utilize clustering algorithm, according to the initial wash packet count N1 of clothing to be clustered, The attribute information set and history of current clothing to be clustered wash grouping set, determine the laundry for being directed to the clothing to be clustered When tactful, it is specifically used for executing following steps:
Step a1: initial clustering point is carried out to each element in the reference set according to the initial cluster center of selection Group obtains N1 initial packet, and calculates initial sample variance corresponding to each initial packet and this Clustering institute Corresponding initial sample variance summation；
Step a2: it according to the element for each initial packet that cluster obtains, is redefined in cluster for each initial packet The heart；
Step a3: carrying out Clustering to each element in the reference set according to the cluster centre redefined, And sample variance corresponding to each grouping is calculated, and recalculate the corresponding sample variance summation of this time cluster；
Step a4: the sample variance summation recalculated is compared with initial sample variance summation, if difference Less than the first convergency value, then go to step a5, otherwise, the grouping that will be clustered according to the cluster centre redefined For initial packet, and the a2 that gos to step；
Step a5: judging whether sample variance corresponding to each grouping obtained after cluster is greater than the second convergency value, if It is to then follow the steps a6, otherwise, go to step a7；
Step a6: determining that sample variance is greater than the grouping number N2 of the second convergency value, from this N2 grouping, randomly selects N2+1 element is as initial cluster center, and the a2 that gos to step；
Step a7: will obtained all washing packet counts and each washing grouping in comprising the corresponding mark of clothing as Laundry strategy；Wherein, described N1, N2 are positive integer, and N1 is greater than N2.
Optionally, before executing step a7, the first determination unit is also used to judge in each grouping corresponding to element Whether the total weight of all clothings is greater than preset capacity threshold value, if so, the total weight for clothing is greater than preset capacity threshold value Grouping, re-start Clustering for clothing corresponding to element in the grouping as clothing to be clustered；Otherwise, step is executed a7。
Optionally, the attribute information of clothing according to the present invention further include: clothing color；First determination unit 43 with Before executing step a7, it is also used to judge whether the clothing color of clothing in each grouping meets default colour fading condition；If so, Then in addition the clothing for meeting default colour fading condition is grouped；Otherwise, step a7 is jumped directly to.
Optionally, clothing database according to the present invention is established at least through one of following manner: manual by user The mode of input adds the attribute information of clothing；Alternatively, adding clothing by way of the bar code or two dimensional code for scanning clothing Attribute information；Alternatively, adding the attribute information of clothing by way of shooting, identifying garment labels.
Optionally, the first transmission unit 44 is also used to the washing mode in laundry strategy being sent to washing machine, wherein washes The mode of washing includes at least: washing water temperature, washing intensity and washing times.
Example IV:
Belong to same inventive concept with above-described embodiment, the embodiment of the invention also provides a kind of terminals.
As shown in figure 5, for a kind of terminal that the embodiment of the present invention four provides, which is specifically included that
Second determination unit 51, for determining the mark of every clothing in current more than one piece clothing to be washed.
The mark of second transmission unit 52, the every clothing for determining the second determination unit 51 is sent to cloud service Device, so that mark of the Cloud Server according to every clothing, matches the attribute information of every clothing, root from clothing database According to the attribute information of the every clothing matched, the laundry strategy for being directed to more than one piece clothing to be washed is determined, wherein attribute information is extremely It less include: kinds of laundry, clothing ingredient, laundry strategy includes at least: comprising clothing in washing packet count and each washing grouping The corresponding mark of object, and washing mode corresponding with each washing grouping.
Second receiving unit 53, for receiving and showing laundry strategy.
Optionally, laundry strategy further include: washing mode corresponding with each washing grouping；Second transmission unit 52 is also used In the washing mode is sent to washing machine, wherein washing mode includes at least: washing water temperature, washing intensity and washing time Number.
It should be understood by those skilled in the art that, the embodiment of the present invention can provide as method, system or computer program Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the present invention Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the present invention, which can be used in one or more, The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces The form of product.
The present invention be referring to according to the method for the embodiment of the present invention, the process of equipment (system) and computer program product Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates, Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one The step of function of being specified in a box or multiple boxes.
Although preferred embodiments of the present invention have been described, it is created once a person skilled in the art knows basic Property concept, then additional changes and modifications may be made to these embodiments.So it includes excellent that the following claims are intended to be interpreted as It selects embodiment and falls into all change and modification of the scope of the invention.
Obviously, various changes and modifications can be made to the invention without departing from essence of the invention by those skilled in the art Mind and range.In this way, if these modifications and changes of the present invention belongs to the range of the claims in the present invention and its equivalent technologies Within, then the present invention is also intended to include these modifications and variations.

Claims (21)

1. a kind of laundry strategy determines method, which is characterized in that the described method includes:
Cloud Server receives the mark of every clothing in the current more than one piece clothing to be washed that terminal determines；
The Cloud Server matches the attribute letter of every clothing according to the mark of the every clothing from clothing database Breath, wherein the attribute information includes at least: kinds of laundry, clothing ingredient；
Whether the Cloud Server detects and deposits in more than one piece clothing to be washed according to the attribute information of the every clothing matched In the clothing that should not be shuffled, and if it exists, using clothing remaining in more than one piece clothing to be washed as clothing to be clustered, if not depositing , then using more than one piece clothing to be washed as clothing to be clustered,
According to the attribute information of the clothing to be clustered, the total weight of the clothing to be clustered is determined；
According to the total weight and preset capacity threshold value of the clothing to be clustered, the initial wash point of the clothing to be clustered is determined Group number N1；
Using clustering algorithm, believed according to the attribute of the initial wash packet count N1 of the clothing to be clustered, current clothing to be clustered Breath and history wash grouping set, determine the laundry strategy for being directed to the clothing to be clustered, wherein the laundry strategy is at least It include: in washing packet count and each washing grouping comprising the corresponding mark of clothing；
The laundry strategy is sent to the terminal by the Cloud Server.
2. the method as described in claim 1, which is characterized in that further include:
Laundry strategy is determined for the clothing that should not be shuffled.
3. the method as described in claim 1, which is characterized in that according to the attribute information of the clothing to be clustered, determine described in The total weight of clothing to be clustered, specifically includes:
According to the kinds of laundry of every clothing in the clothing to be clustered, the volume of every clothing is determined；
According to the clothing ingredient of every clothing in the clothing to be clustered, the density of every clothing is determined；
According to the volume and density of every determining clothing, the total weight of the clothing to be clustered is counted.
4. the method as described in claim 1, which is characterized in that clustering algorithm is utilized, according to the initial of the clothing to be clustered It washs packet count N1, the attribute information of current clothing to be clustered and history and washs grouping set, determine for described to be clustered The laundry strategy of clothing, specifically includes:
Grouping set is washed according to by current clothing set and history to be clustered, determines the reference set of current clothing to be clustered It closes, wherein the element in the clothing set to be clustered characterizes a clothing in clothing to be clustered respectively, and described to be clustered Each element in clothing set is made of the vector for characterizing each clothing ingredient in the clothing；The history washs set of packets Element in conjunction characterizes each history washing grouping respectively, and characterizes corresponding clothing comprising several in the washing grouping of each history Element；Element in the reference set characterizes a clothing respectively, and each element in the reference set is by table Levy the vector composition of each clothing ingredient in the clothing；
From determining reference set, N1 element is randomly selected as initial cluster center；
Using clustering algorithm, needle is determined according to the reference set of the determining current clothing to be clustered and initial cluster center To the laundry strategy of the clothing to be clustered.
5. method as claimed in claim 4, which is characterized in that according to by current clothing set and history washing point to be clustered Group set determines the reference set of current clothing to be clustered, specifically includes:
History washing grouping each in history washing grouping set is compared with the clothing set to be clustered, is obtained several A first intersection；
It is determined from several described first intersections comprising the most set of element as maximum set, and judges the maximum collection Whether the element number for including in conjunction is more than preset threshold；
If being more than, the second intersection is determined according to current clothing set and maximum set to be clustered, and according to the second intersection meter It calculates and obtains the average vector for second intersection；The average vector is combined to form reference set with maximum set；
If being not above, using clothing set to be clustered as reference set.
6. method as claimed in claim 4, which is characterized in that clustering algorithm is utilized, according to determining described current to be clustered The reference set and initial cluster center of clothing determine the laundry strategy for being directed to the clothing to be clustered, specifically include:
Step a1: carrying out initial clustering grouping to each element in the reference set according to the initial cluster center of selection, Obtain N1 initial packet, and calculate initial sample variance corresponding to each initial packet and this Clustering institute it is right The initial sample variance summation answered；
Step a2: according to the element for each initial packet that cluster obtains, cluster centre is redefined for each initial packet；
Step a3: Clustering is carried out to each element in the reference set according to the cluster centre redefined, and is counted Sample variance corresponding to each grouping is calculated, and recalculates the corresponding sample variance summation of this time cluster；
Step a4: the sample variance summation recalculated is compared with initial sample variance summation, if difference is less than First convergency value, then go to step a5, otherwise, is grouped into what is clustered according to the cluster centre redefined just Begin grouping, and the a2 that gos to step；
Step a5: judging whether sample variance corresponding to each grouping obtained after cluster is greater than the second convergency value, if so, Step a6 is executed, otherwise, go to step a7；
Step a6: determining that sample variance is greater than the grouping number N2 of the second convergency value, from this N2 grouping, randomly selects N2+1 A element is as initial cluster center, and the a1 that gos to step；
Step a7: laundry will be used as comprising the corresponding mark of clothing in obtained all washing packet counts and each washing grouping Strategy；
Wherein, described N1, N2 are positive integer, and N1 is greater than N2.
7. method as claimed in claim 6, which is characterized in that before executing step a7, the method also includes:
Judge whether the total weight of all clothings corresponding to element in each grouping is greater than preset capacity threshold value；
If so, being greater than the grouping of preset capacity threshold value for the total weight of clothing, by clothing corresponding to element in the grouping Clustering is re-started as clothing to be clustered；
Otherwise, go to step a7.
8. method as claimed in claim 6, which is characterized in that the attribute information further include: clothing color；
Before executing step a7, the method also includes:
Judge whether the clothing color of clothing in each grouping meets default colour fading condition；
If so, in addition the clothing for meeting default colour fading condition is grouped；
Otherwise, step a7 is jumped directly to.
9. the method as described in claim 1, which is characterized in that the clothing database is built at least through one of following manner It is vertical:
The attribute information of clothing is added in such a way that user is manually entered；Alternatively,
Attribute information adding clothing by way of scanning the bar code or two dimensional code of clothing；Alternatively,
The attribute information of clothing is added by way of shooting, identifying garment labels.
10. the method as described in claim 1, which is characterized in that the laundry strategy further include: washing mode；
The method also includes:
Washing mode in the laundry strategy is sent to washing machine, wherein the washing mode includes at least: washing water Temperature, washing intensity and washing times.
11. a kind of Cloud Server characterized by comprising
First receiving unit, for receiving the mark of every clothing in the current more than one piece clothing to be washed that terminal determines；
Matching unit, the mark of the every clothing for being received according to first receiving unit, from clothing database In match the attribute information of every clothing, wherein the attribute information includes at least: kinds of laundry, clothing ingredient；
First determination unit, the attribute information of the every clothing for being matched according to the matching unit, detects the more than one piece Wait wash in clothing with the presence or absence of the clothing that should not be shuffled；If it exists, using clothing remaining in more than one piece clothing to be washed as Clothing to be clustered, if it does not exist, then using more than one piece clothing to be washed as clothing to be clustered, according to the clothing to be clustered Attribute information determines the total weight of the clothing to be clustered；According to the total weight and preset capacity threshold of the clothing to be clustered Value, determines the initial wash packet count N1 of the clothing to be clustered；Using clustering algorithm, according to the initial of the clothing to be clustered It washs packet count N1, the attribute information of current clothing to be clustered and history and washs grouping set, determine for described to be clustered The laundry strategy of clothing, wherein the laundry strategy includes at least: including clothing in washing packet count and each washing grouping Corresponding mark；
First transmission unit, the laundry strategy for determining first determination unit are sent to the terminal.
12. Cloud Server as claimed in claim 11, which is characterized in that first determination unit is also used to:
Laundry strategy is determined for the clothing that should not be shuffled.
13. Cloud Server as claimed in claim 11, which is characterized in that first determination unit is according to described to be clustered When the attribute information of clothing determines the total weight of the clothing to be clustered, it is specifically used for:
According to the kinds of laundry of every clothing in the clothing to be clustered, the volume of every clothing is determined；
According to the clothing ingredient of every clothing in the clothing to be clustered, the density of every clothing is determined；
According to the volume and density of every determining clothing, the total weight of the clothing to be clustered is counted.
14. Cloud Server as claimed in claim 11, which is characterized in that first determination unit is utilizing clustering algorithm, According to the initial wash packet count N1 of the clothing to be clustered, the attribute information of current clothing to be clustered and history washing grouping Set is specifically used for when determining the laundry strategy for being directed to the clothing to be clustered:
Grouping set is washed according to by current clothing set and history to be clustered, determines the reference set of current clothing to be clustered It closes, wherein the element in the clothing set to be clustered characterizes a clothing in clothing to be clustered respectively, and described to be clustered Each element in clothing set is made of the vector for characterizing each clothing ingredient in the clothing；The history washs set of packets Element in conjunction characterizes each history washing grouping respectively, and characterizes corresponding clothing comprising several in the washing grouping of each history Element；Element in the reference set characterizes a clothing respectively, and each element in the reference set is by table Levy the vector composition of each clothing ingredient in the clothing；
From determining reference set, N1 element is randomly selected as initial cluster center；
Using clustering algorithm, needle is determined according to the reference set of the determining current clothing to be clustered and initial cluster center To the laundry strategy of the clothing to be clustered.
15. Cloud Server as claimed in claim 14, which is characterized in that first determination unit is according to by currently to poly- Class clothing set and history wash grouping set, when determining the reference set of current clothing to be clustered, are specifically used for:
History washing grouping each in history washing grouping set is compared with the clothing set to be clustered, is obtained several A first intersection；
It is determined from several described first intersections comprising the most set of element as maximum set, and judges the maximum collection Whether the element number for including in conjunction is more than preset threshold；
If being more than, the second intersection is determined according to current clothing set and maximum set to be clustered, and according to the second intersection meter It calculates and obtains the average vector for second intersection；The average vector is combined to form reference set with maximum set；
If being not above, using clothing set to be clustered as reference set.
16. Cloud Server as claimed in claim 14, which is characterized in that first determination unit is utilizing clustering algorithm, It determines according to the reference set of the determining current clothing to be clustered and initial cluster center and is directed to the clothing to be clustered Laundry strategy when, be specifically used for execute following steps:
Step a1: carrying out initial clustering grouping to each element in the reference set according to the initial cluster center of selection, Obtain N1 initial packet, and calculate initial sample variance corresponding to each initial packet and this Clustering institute it is right The initial sample variance summation answered；
Step a2: according to the element for each initial packet that cluster obtains, cluster centre is redefined for each initial packet；
Step a3: Clustering is carried out to each element in the reference set according to the cluster centre redefined, and is counted Sample variance corresponding to each grouping is calculated, and recalculates the corresponding sample variance summation of this time cluster；
Step a4: the sample variance summation recalculated is compared with initial sample variance summation, if difference is less than First convergency value, then go to step a5, otherwise, is grouped into what is clustered according to the cluster centre redefined just Begin grouping, and the a2 that gos to step；
Step a5: judging whether sample variance corresponding to each grouping obtained after cluster is greater than the second convergency value, if so, Step a6 is executed, otherwise, go to step a7；
Step a6: determining that sample variance is greater than the grouping number N2 of the second convergency value, from this N2 grouping, randomly selects N2+1 A element is as initial cluster center, and the a1 that gos to step；
Step a7: laundry will be used as comprising the corresponding mark of clothing in obtained all washing packet counts and each washing grouping Strategy；
Wherein, described N1, N2 are positive integer, and N1 is greater than N2.
17. Cloud Server as claimed in claim 16, which is characterized in that before executing step a7, described first determines list Member is also used to:
Judge whether the total weight of all clothings corresponding to element in each grouping is greater than preset capacity threshold value；
If so, being greater than the grouping of preset capacity threshold value for the total weight of clothing, by clothing corresponding to element in the grouping Clustering is re-started as clothing to be clustered；
Otherwise, go to step a7.
18. Cloud Server as claimed in claim 16, which is characterized in that the attribute information further include: clothing color；
First determination unit is for being also used to before executing step a7:
Judge whether the clothing color of clothing in each grouping meets default colour fading condition；
If so, in addition the clothing for meeting default colour fading condition is grouped；
Otherwise, step a7 is jumped directly to.
19. Cloud Server as claimed in claim 11, which is characterized in that the clothing database at least through following manner it One establishes:
The attribute information of clothing is added in such a way that user is manually entered；Alternatively,
Attribute information adding clothing by way of scanning the bar code or two dimensional code of clothing；Alternatively,
The attribute information of clothing is added by way of shooting, identifying garment labels.
20. Cloud Server as claimed in claim 11, which is characterized in that the laundry strategy further include: washing mode；
First transmission unit is also used to the washing mode in the laundry strategy being sent to washing machine, wherein described to wash The mode of washing includes at least: washing water temperature, washing intensity and washing times.
21. a kind of laundry policy determination system characterized by comprising terminal, Cloud Server and washing machine；
Wherein, the terminal is used to determine the mark of every clothing in current more than one piece clothing to be washed；And by the every clothing Mark be sent to Cloud Server；And it receives and shows laundry strategy；
The Cloud Server is used to receive the mark of every clothing in the current more than one piece clothing to be washed that the terminal determines；According to The mark of the every clothing, matches the attribute information of every clothing from clothing database, wherein the attribute information is extremely It less include: kinds of laundry, clothing ingredient；According to the attribute information of every clothing, detect in more than one piece clothing to be washed whether In the presence of the clothing that should not be shuffled；If it exists, using clothing remaining in more than one piece clothing to be washed as clothing to be clustered, if not depositing , then using more than one piece clothing to be washed as clothing to be clustered, according to the attribute information of the clothing to be clustered, determine described in The total weight of clothing to be clustered；According to the total weight and preset capacity threshold value of the clothing to be clustered, determine described to be clustered The initial wash packet count N1 of clothing；Using clustering algorithm, according to the initial wash packet count N1 of the clothing to be clustered, currently The attribute information and history of clothing to be clustered wash grouping set, determine the laundry strategy for being directed to the clothing to be clustered, In, the laundry strategy includes at least: including the corresponding mark of clothing, Yi Jiyu in washing packet count and each washing grouping Each washing is grouped corresponding washing mode；The laundry strategy is sent to the terminal；
The use in washing machine is in the washing mode for receiving the Cloud Server or terminal transmission.
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