CN105094321A

CN105094321A - Method and apparatus for controlling intelligent device

Info

Publication number: CN105094321A
Application number: CN201510395490.4A
Authority: CN
Inventors: 张鹏飞; 夏勇峰; 屈恒; 王益冬
Original assignee: Xiaomi Inc
Current assignee: Beijing Xiaomi Technology Co Ltd; Xiaomi Inc
Priority date: 2015-07-07
Filing date: 2015-07-07
Publication date: 2015-11-25
Anticipated expiration: 2035-07-07
Also published as: CN105094321B

Abstract

The invention relates to a method and an apparatus for controlling an intelligent device, which belong to the Internet field, wherein the method comprises: determining an identification of a target intelligent device; the identification of the target intelligent device is the identification of the intelligent device that is being used currently by a user; acquiring life sign datum of the user corresponding to the identification of the target intelligent device based on the identification of the target intelligent device; and controlling the target intelligent device based on the identification of the target intelligent device and the life sign datum. According to the invention, manual control of the user to the target intelligent device is avoided, thus improving the control efficiency to the target intelligent device.

Description

The control method of smart machine and device

Technical field

The disclosure relates to internet arena, particularly relates to a kind of control method and device of smart machine.

Background technology

Along with the development of technology, apply more and more widely as the smart machines such as smart mobile phone, intelligent air condition, intelligent television obtain.In order to play smart machine function to greatest extent, can control smart machine, and in the related, being all generally that user manually controls to the control of smart machine.

Summary of the invention

For overcoming Problems existing in correlation technique, the disclosure provides a kind of control method and device of smart machine.

According to the first aspect of disclosure embodiment, provide a kind of control method of smart machine, described method comprises:

Determine Intelligent target device identification, described Intelligent target device identification is the mark of the current smart machine used of user;

Based on described Intelligent target device identification, obtain the vital sign data corresponding with described Intelligent target device identification of described user;

Based on described Intelligent target device identification and described vital sign data, described Intelligent target equipment is controlled.

In conjunction with first aspect, in the first possible implementation of above-mentioned first aspect, describedly determine Intelligent target device identification, comprising:

Receive the opening of device information that described Intelligent target equipment sends, described opening of device information carries described Intelligent target device identification, and described opening of device information is opened for identifying described Intelligent target equipment.

In conjunction with first aspect, in the implementation that the second of above-mentioned first aspect is possible, describedly determine Intelligent target device identification, comprising:

Detect the user behavior of current time;

Based on described user behavior, from the first presetting database, obtain Intelligent target device identification, described first presetting database comprises user behavior, corresponding relation between smart machine mark with first frequency.

In conjunction with the implementation that the second of first aspect is possible, in the third possible implementation of above-mentioned first aspect, described based on described user behavior, from the first presetting database, obtain Intelligent target device identification, comprising:

Based on described user behavior, comprise user behavior from described first presetting database, smart machine identifies the corresponding relation between first frequency, obtain first frequency of at least one smart machine mark and at least one smart machine described mark correspondence;

Based on first frequency that described at least one smart machine mark is corresponding, determine the probability of described at least one smart machine mark;

Based on the probability of described at least one smart machine mark, determine Intelligent target device identification.

In conjunction with the third possible implementation of first aspect, in the 4th kind of possible implementation of above-mentioned first aspect, the described probability based on described at least one smart machine mark, determine Intelligent target device identification, comprising:

Based on the probability of described at least one smart machine mark, at least one smart machine mark described in judging, whether there is the smart machine mark that probability is more than or equal to probability threshold value;

When there is probability in described at least one smart machine mark and being more than or equal to the smart machine mark of described probability threshold value, from described at least one smart machine mark, the smart machine mark that select probability is maximum;

The smart machine of selection mark is defined as Intelligent target device identification.

In conjunction with the third possible implementation of first aspect, in the 5th kind of possible implementation of above-mentioned first aspect, described first frequency corresponding based on described at least one smart machine mark, determine the probability of described at least one smart machine mark, comprising:

Determine the accumulated value of first frequency of each smart machine mark correspondence in described at least one smart machine mark, obtain first total frequency;

For the arbitrary smart machine mark in described at least one smart machine mark, by first corresponding for the described smart machine mark frequency divided by described first total frequency, obtain the probability of described smart machine mark.

In conjunction with first aspect, in the 6th kind of possible implementation of above-mentioned first aspect, describedly determine Intelligent target device identification, comprising:

Determine the time period at current time place;

Based on the described time period, from the second presetting database, obtain Intelligent target device identification, described second presetting database comprises time period, corresponding relation between smart machine mark with second frequency.

In conjunction with the 6th kind of possible implementation of first aspect, in the 7th kind of possible implementation of above-mentioned first aspect, described based on the described time period, from the second presetting database, obtain Intelligent target device identification, comprising:

Based on the described time period, identify the corresponding relation between second frequency from the time period that described second presetting database comprises, smart machine, obtain second frequency of at least one smart machine mark and at least one smart machine described mark correspondence;

Based on second frequency that described at least one smart machine mark is corresponding, determine the probability of described at least one smart machine mark;

In conjunction with the 7th kind of possible implementation of first aspect, in the 8th kind of possible implementation of above-mentioned first aspect, described second frequency corresponding based on described at least one smart machine mark, determine the probability of described at least one smart machine mark, comprising:

Determine the accumulated value of second frequency of each smart machine mark correspondence in described at least one smart machine mark, obtain second total frequency;

For the arbitrary smart machine mark in described at least one smart machine mark, by second corresponding for the described smart machine mark frequency divided by described second total frequency, obtain the probability of described smart machine mark.

In conjunction with first aspect, in the 9th kind of possible implementation of above-mentioned first aspect, described based on described Intelligent target device identification, obtain the vital sign data corresponding with described Intelligent target device identification of described user, comprising:

Based on described Intelligent target device identification, from the corresponding relation between the smart machine mark stored and vital sign attribute, obtain corresponding vital sign attribute;

Based on described vital sign attribute, the vital sign corresponding to described user detects, and obtains the vital sign data corresponding with described Intelligent target device identification of described user.

In conjunction with first aspect, in the tenth kind of possible implementation of above-mentioned first aspect, described based on described Intelligent target device identification and described vital sign data, described Intelligent target equipment is controlled, comprising:

Based on described Intelligent target device identification, described vital sign data is sent to server, described server is controlled described Intelligent target equipment based on described vital sign data;

Or,

Based on described Intelligent target device identification, described vital sign data is sent to described Intelligent target equipment by server, described Intelligent target equipment is controlled described Intelligent target equipment based on described vital sign data.

According to the second aspect of disclosure embodiment, provide a kind of control device of smart machine, described device comprises:

Determination module, for determining Intelligent target device identification, described Intelligent target device identification is the mark of the current smart machine used of user;

Acquisition module, for based on described Intelligent target device identification, obtains the vital sign data corresponding with described Intelligent target device identification of described user;

Control module, for based on described Intelligent target device identification and described vital sign data, controls described Intelligent target equipment.

In conjunction with second aspect, in the first possible implementation of above-mentioned second aspect, described determination module comprises:

Receiving element, for receiving the opening of device information that described Intelligent target equipment sends, described opening of device information carries described Intelligent target device identification, and described opening of device information is opened for identifying described Intelligent target equipment.

In conjunction with second aspect, in the implementation that the second of above-mentioned second aspect is possible, described determination module comprises:

First detecting unit, for detecting the user behavior of current time;

First acquiring unit, for based on described user behavior, from the first presetting database, obtains Intelligent target device identification, and described first presetting database comprises user behavior, corresponding relation between smart machine mark with first frequency.

In conjunction with the implementation that the second of second aspect is possible, in the third possible implementation of above-mentioned second aspect, described first acquiring unit comprises:

First obtains subelement, for based on described user behavior, comprise user behavior from described first presetting database, smart machine identifies the corresponding relation between first frequency, obtain first frequency of at least one smart machine mark and at least one smart machine described mark correspondence;

First determines subelement, for first frequency based on described at least one smart machine mark correspondence, determines the probability of described at least one smart machine mark;

Second determines subelement, for the probability based on described at least one smart machine mark, determines Intelligent target device identification.

In conjunction with the third possible implementation of second aspect, in the 4th kind of possible implementation of above-mentioned second aspect, described second determine subelement specifically for:

In conjunction with the third possible implementation of second aspect, in the 5th kind of possible implementation of above-mentioned second aspect, described first determine subelement specifically for:

In conjunction with second aspect, in the 6th kind of possible implementation of above-mentioned second aspect, described determination module comprises:

First determining unit, for determining the time period at current time place;

Second acquisition unit, for based on the described time period, from the second presetting database, obtains Intelligent target device identification, and described second presetting database comprises time period, corresponding relation between smart machine mark with second frequency.

In conjunction with the 6th kind of possible implementation of second aspect, in the 7th kind of possible implementation of above-mentioned second aspect, described second acquisition unit comprises:

Second obtains subelement, for based on the described time period, identify the corresponding relation between second frequency from the time period that described second presetting database comprises, smart machine, obtain second frequency of at least one smart machine mark and at least one smart machine described mark correspondence;

3rd determines subelement, for second frequency based on described at least one smart machine mark correspondence, determines the probability of described at least one smart machine mark;

4th determines subelement, for the probability based on described at least one smart machine mark, determines Intelligent target device identification.

In conjunction with the 7th kind of possible implementation of second aspect, in the 8th kind of possible implementation of above-mentioned second aspect, the described 3rd determine subelement specifically for:

In conjunction with second aspect, in the 9th kind of possible implementation of above-mentioned second aspect, described acquisition module comprises:

3rd acquiring unit, for based on described Intelligent target device identification, from the corresponding relation between the smart machine mark stored and vital sign attribute, obtains corresponding vital sign attribute;

Second detecting unit, based on described vital sign attribute, the vital sign corresponding to described user detects, and obtains the vital sign data corresponding with described Intelligent target device identification of described user.

In conjunction with second aspect, in the tenth kind of possible implementation of above-mentioned second aspect, described control module comprises:

First transmitting element, for based on described Intelligent target device identification, sends to server by described vital sign data, and described server is controlled described Intelligent target equipment based on described vital sign data;

Or,

Second transmitting element, for based on described Intelligent target device identification, sends to described Intelligent target equipment by described vital sign data by server, and described Intelligent target equipment is controlled described Intelligent target equipment based on described vital sign data.

The third aspect, provides a kind of control device of smart machine, and described device comprises:

Processor;

For the storer of storage of processor executable instruction;

Wherein, described processor is configured to:

The technical scheme that embodiment of the present disclosure provides can comprise following beneficial effect: in the disclosed embodiments, the Intelligent worn device of being dressed by user determines the current Intelligent target device identification used of user, and based on this Intelligent target device identification, obtain the vital sign data corresponding with Intelligent target device identification of user, based on this Intelligent target device identification and vital sign data, this Intelligent target equipment is controlled, thus avoid the Non-follow control of user to Intelligent target equipment, improve the control efficiency of Intelligent target equipment.

Should be understood that, it is only exemplary and explanatory that above general description and details hereinafter describe, and can not limit the disclosure.

Accompanying drawing explanation

Accompanying drawing to be herein merged in instructions and to form the part of this instructions, shows embodiment according to the invention, and is used from instructions one and explains principle of the present invention.

Fig. 1 is the control system Organization Chart of a kind of smart machine according to an exemplary embodiment.

Fig. 2 is the process flow diagram of the control method of a kind of smart machine according to an exemplary embodiment.

Fig. 3 is the process flow diagram of the control method of another kind of smart machine according to an exemplary embodiment.

Fig. 4 is the control device structural representation of a kind of smart machine according to an exemplary embodiment.

Fig. 5 is the structural representation of a kind of determination module according to an exemplary embodiment.

Fig. 6 is the one first acquiring unit structural representation according to an exemplary embodiment.

Fig. 7 is the structural representation of the another kind of determination module according to an exemplary embodiment.

Fig. 8 is a kind of second acquisition unit structural representation according to an exemplary embodiment.

Fig. 9 is the structural representation of a kind of acquisition module according to an exemplary embodiment.

Figure 10 is the block diagram of a kind of control device for smart machine according to an exemplary embodiment.

Embodiment

Here will be described exemplary embodiment in detail, its sample table shows in the accompanying drawings.When description below relates to accompanying drawing, unless otherwise indicated, the same numbers in different accompanying drawing represents same or analogous key element.Embodiment described in following exemplary embodiment does not represent all embodiments consistent with the present invention.On the contrary, they only with as in appended claims describe in detail, the example of apparatus and method that aspects more of the present invention are consistent.

Fig. 1 is the control system Organization Chart of a kind of smart machine that disclosure embodiment provides.See Fig. 1, this system comprises Intelligent worn device, mobile terminal, server and Intelligent target equipment.This Intelligent worn device can be connected by network with mobile terminal, and this mobile terminal can be connected by network with server, and this server also can be connected by network with Intelligent target equipment.Intelligent worn device, for detecting vital sign data, also can send/receive information; Mobile terminal is the communications intermediary equipment between Intelligent worn device and server, for the information sent between server and Intelligent worn device being forwarded; Server is the communications intermediary equipment between mobile terminal and Intelligent target equipment, for the information sent between mobile terminal and Intelligent target equipment being forwarded.

Fig. 2 is the process flow diagram of the control method of a kind of smart machine according to an exemplary embodiment, see Fig. 2, comprises the following steps.

In step 201, determine Intelligent target device identification, this Intelligent target device identification is the mark of the current smart machine used of user.

In step 202., based on this Intelligent target device identification, obtain the vital sign data corresponding with Intelligent target device identification of user.

In step 203, based on this Intelligent target device identification and this vital sign data, this Intelligent target equipment is controlled.

In the disclosed embodiments, the Intelligent worn device of being dressed by user determines the current Intelligent target device identification used of user, and based on this Intelligent target device identification, obtain the vital sign data corresponding with Intelligent target device identification of user, based on this Intelligent target device identification and this vital sign data, this Intelligent target equipment is controlled, thus avoids Intelligent target equipment Non-follow control, improve the control efficiency of Intelligent target equipment.

In another embodiment of the present disclosure, determine Intelligent target device identification, comprising:

The opening of device information that receiving target smart machine sends, this opening of device information carries this Intelligent target device identification, and this opening of device information is opened for identifying this Intelligent target equipment.

Detect the user behavior of current time;

Based on detect user behavior, from the first presetting database, obtain this Intelligent target device identification, the first presetting database comprise user behavior, smart machine mark with first frequency between corresponding relation.

In another embodiment of the present disclosure, based on user behavior, from the first presetting database, obtain Intelligent target device identification, comprising:

Based on this user behavior, comprise user behavior from the first presetting database, smart machine identifies the corresponding relation between first frequency, obtain first frequency of at least one smart machine mark and this at least one smart machine mark correspondence;

Based on first frequency that this at least one smart machine mark is corresponding, determine the probability that this at least one smart machine identifies;

Based on the probability of this at least one smart machine mark, determine this Intelligent target device identification.

In another embodiment of the present disclosure, based on the probability of this at least one smart machine mark, determine Intelligent target device identification, comprising:

Based on this at least one smart machine mark probability, judge at least one smart machine mark in whether exist probability be more than or equal to probability threshold value smart machine mark;

When there is probability in this at least one smart machine mark and being more than or equal to the smart machine mark of this probability threshold value, from this at least one smart machine mark, the smart machine mark that select probability is maximum;

In another embodiment of the present disclosure, based on first frequency that this at least one smart machine mark is corresponding, determine to comprise the probability that this at least one smart machine identifies:

Determine the accumulated value of first frequency of each smart machine mark correspondence in this at least one smart machine mark, obtain first total frequency;

For the arbitrary smart machine mark in this at least one smart machine mark, by first corresponding for the smart machine mark frequency divided by this first total frequency, obtain the probability of this smart machine mark.

Determine the time period at current time place;

Based on the time period determined, from the second presetting database, obtain this Intelligent target device identification, this second presetting database comprise the time period, smart machine mark with second frequency between corresponding relation.

In another embodiment of the present disclosure, based on this time period, from the second presetting database, obtain Intelligent target device identification, comprising:

Based on this time period, identify the corresponding relation between second frequency from the time period that the second presetting database comprises, smart machine, obtain second frequency of at least one smart machine mark and this at least one smart machine mark correspondence;

Based on second frequency that this at least one smart machine mark is corresponding, determine the probability that this at least one smart machine identifies;

Based on the probability of this at least one smart machine mark, determine Intelligent target device identification.

In another embodiment of the present disclosure, based on second frequency that this at least one smart machine mark is corresponding, determine to comprise the probability that this at least one smart machine identifies:

Determine the accumulated value of second frequency of each smart machine mark correspondence in this at least one smart machine mark, obtain second total frequency;

For the arbitrary smart machine mark in this at least one smart machine mark, by second corresponding for this smart machine mark frequency divided by this second total frequency, obtain the probability of this smart machine mark.

In another embodiment of the present disclosure, based target smart machine identifies, and obtains the vital sign data corresponding with Intelligent target device identification of user, comprising:

Based target smart machine identifies, and from the corresponding relation between the smart machine mark stored and vital sign attribute, obtains corresponding vital sign attribute;

Based on the vital sign attribute obtained, the vital sign corresponding to user detects, and obtains the vital sign data corresponding with Intelligent target device identification of this user.

In another embodiment of the present disclosure, based on this Intelligent target device identification and this vital sign data, Intelligent target equipment is controlled, comprising:

Based on this Intelligent target device identification, this vital sign data is sent to server, this server is controlled this Intelligent target equipment based on this vital sign data;

Or,

Based on this Intelligent target device identification, this vital sign data is sent to Intelligent target equipment by server, this Intelligent target equipment is controlled this Intelligent target equipment based on this vital sign data.

Above-mentioned all alternatives, all can form embodiment of the present disclosure according to combining arbitrarily, disclosure embodiment repeats no longer one by one to this.

Fig. 3 is the process flow diagram of the control method of a kind of smart machine according to an exemplary embodiment.See Fig. 3, the method comprises the following steps.

In step 301, determine Intelligent target device identification, Intelligent target device identification is the mark of the current smart machine used of user.

In order to improve the control efficiency of Intelligent target equipment, when user is using Intelligent target equipment, the Intelligent worn device can dressed by this user is being controlled this Intelligent target equipment.And before controlling this Intelligent target equipment, this Intelligent worn device can determine this Intelligent target device identification, in the disclosed embodiments, Intelligent worn device can determine Intelligent target device identification by following three kinds of modes, comprising:

First kind of way, the opening of device information that receiving target smart machine sends, this opening of device information carries Intelligent target device identification, and opening of device information is opened for identifying Intelligent target equipment.

For first kind of way, when user opens this Intelligent target equipment, this Intelligent target equipment can to server transmitting apparatus opening information.When server receives the opening of device information of this Intelligent target equipment transmission, this opening of device information is sent to mobile terminal by this server.After this mobile terminal receives this opening of device information, this opening of device information is transmitted to Intelligent worn device.After Intelligent worn device receives this opening of device information, the Intelligent target device identification that user is using can be confirmed.

Wherein, in the disclosed embodiments, when mobile terminal communicates with Intelligent worn device, need a wearable device client is installed in the terminal, this wearable device client comprises the interface between wearable device client and Intelligent worn device, therefore, this mobile terminal can by communicating between this interface with Intelligent worn device.

In addition, along with the development of technology, Intelligent worn device also directly can communicate with server.Therefore, in first kind of way, when server receives the opening of device information of Intelligent target equipment transmission, this opening of device information directly can be sent to Intelligent worn device by this server, and without the need to forwarding through mobile terminal, improve information interaction efficiency.

It should be noted that, this Intelligent worn device can be Intelligent bracelet, intelligent watch, intelligent glasses or intelligent necklace, and certainly, Intelligent worn device can also be the smart machine of other Wearable, and disclosure embodiment is not specifically limited this.

In addition, Intelligent target device identification is the mark of Intelligent target equipment, this Intelligent target device identification is used for this Intelligent target equipment of unique identification, and this Intelligent target device identification can be the sequence number etc. that dispatches from the factory of the model of Intelligent target equipment, the title of Intelligent target equipment or Intelligent target equipment, certainly, this Intelligent target device identification can also be that other can represent the mark of Intelligent target equipment, and disclosure embodiment does not do concrete restriction to this.

Moreover, communication mode between Intelligent worn device and mobile terminal can be Wi-Fi (WirelessFidelity, Wireless Fidelity), NFC (NearFieldcommunication, wireless near field communication) or bluetooth, certainly, communication mode between Intelligent worn device and mobile terminal can also be other communication modes, such as infrared communication mode, and disclosure embodiment is not specifically limited this.

The second way, detects the user behavior of current time; Based on the user behavior detected, from the first presetting database, obtain Intelligent target device identification, the first presetting database comprises user behavior, corresponding relation between smart machine mark with first frequency.

For the second way, this Intelligent worn device can detect the user behavior of current time, based on this user behavior, from the first presetting database comprise user behavior, smart machine mark with first frequency between corresponding relation, obtain corresponding smart machine mark and first frequency, obtain first frequency that at least one smart machine identifies and this at least one smart machine mark is corresponding; Based on first frequency that this at least one smart machine mark is corresponding, determine the probability that this at least one smart machine identifies; Based on the probability of this at least one smart machine mark, determine Intelligent target device identification.

Wherein, this Intelligent worn device is based on first frequency of this at least one smart machine mark correspondence, determine that the operation of the probability that this at least one smart machine identifies can be: this Intelligent worn device determines the accumulated value of first frequency that each smart machine mark is corresponding in this at least one smart machine mark, obtains first total frequency; For the arbitrary smart machine mark in this at least one smart machine mark, by first corresponding for this smart machine mark frequency divided by first total frequency, obtain the probability of this smart machine mark, thus obtain the probability of this at least one smart machine mark.

In addition, the probability that this Intelligent worn device identifies based on this at least one smart machine, determine that the operation of Intelligent target device identification can be: the probability that this at least one smart machine identifies by this Intelligent worn device and probability threshold value compare, thus judge this at least one smart machine mark in whether exist probability be more than or equal to probability threshold value smart machine mark; When there is probability in this at least one smart machine mark and being more than or equal to the smart machine mark of probability threshold value, from this at least one smart machine mark, the smart machine mark that select probability is maximum; The smart machine of selection mark is defined as Intelligent target device identification.

Such as, Intelligent worn device detects that the user behavior of current time is for " running ", now, this Intelligent worn device can based on this user behavior, from user behavior as shown in table 1 below, in corresponding relation between smart machine mark and first frequency, obtain corresponding smart machine mark and first frequency, obtain at least one smart machine mark and be respectively intelligent television, intelligent running machine and intelligent earphone, and to obtain first frequency corresponding to intelligent television be 1 time, first frequency that intelligent running machine is corresponding is 28 times, first frequency that intelligent earphone is corresponding is 2 times, therefore, the accumulated value of first frequency that each smart machine mark is corresponding in this at least one smart machine mark can be determined, obtaining first total frequency is 31 times, by first corresponding for the intelligent television frequency divided by this first total frequency, obtaining probability corresponding to intelligent television is 0.032, by first corresponding for the intelligent running machine frequency divided by this first total frequency, obtaining probability corresponding to intelligent running machine is 0.903, by first corresponding for the intelligent earphone frequency divided by this first total frequency, obtaining probability corresponding to intelligent earphone is 0.065.If probability threshold value is 0.9, probability corresponding to this intelligent television, intelligent running machine and intelligent earphone is all compared with this probability threshold value, determine that the probability that intelligent running machine is corresponding is greater than probability threshold value, and the maximum probability that this intelligent running machine is corresponding.Therefore, when the user behavior of current time is for " running ", intelligent running machine can be defined as Intelligent target device identification.

Table 1

User behavior	Smart machine identifies	First frequency
			Run	Intelligent television	1 time
Run	Intelligent running machine	28 times
			Run	Intelligent earphone	2 times

It should be noted that, in the disclosed embodiments, the corresponding relation only identified between first frequency for the user behavior shown in above-mentioned table 1, smart machine is described, and above-mentioned table 1 does not form restriction to disclosure embodiment.

Further, when there is not probability in this at least one smart machine mark and being more than or equal to the smart machine mark of probability threshold value, that is to say, the probability of this at least one smart machine mark is all less than probability threshold value, now, this Intelligent worn device can by the device identification of above-mentioned first kind of way determination Intelligent target, and disclosure embodiment is no longer described in detail at this.

It should be noted that, the user behavior stored in first presetting database, between smart machine mark and first frequency, corresponding relation obtains based on the behavioral data of user in the first preset time period, that is to say, this Intelligent worn device can gather the user behavior produced in the first preset time period, the smart machine be associated with this user behavior identifies, and the degree of incidence that this user behavior and this smart machine identify, and then by this user behavior, the smart machine be associated with this user behavior identifies, the degree of incidence that this user behavior and this smart machine identify is stored in the user behavior that the first presetting database comprises, between smart machine mark and first frequency in corresponding relation.

Wherein, this first presetting database can be stored in Intelligent worn device, certainly, this first presetting database can also be stored in other equipment, such as server, afterwards, this first presetting database can be downloaded to this locality by this Intelligent worn device from server, and the disclosure does not do concrete restriction to this.

Wherein, the length of the first preset time period arranges in advance, and the first preset time period can be 1 month, 2 months or 3 months before current time, and may be also other times length certainly, the disclosure do concrete restriction to this.In addition, probability threshold value can be arrange in advance, and such as, this probability threshold value is 0.9,0.95 etc., and disclosure embodiment is not specifically limited this equally.

Such as, Intelligent worn device gathers user in May, 2015, when user behavior is for " running ", the smart machine be associated with " running " is designated intelligent television, intelligent running machine and intelligent earphone, and the degree of incidence of intelligent television is 1 time, the degree of incidence of intelligent running machine is 28 times, and the degree of incidence of intelligent earphone is 2 times.To " run ", " intelligent television " and " 1 time " be stored in the user behavior shown in above-mentioned table 1, smart machine mark with first frequency between corresponding relation in, in like manner, to " run ", " intelligent running machine " and " 28 times ", and will " run ", " intelligent earphone " and " 2 times " be stored in this user behavior shown in above-mentioned table 1, smart machine mark with first frequency between corresponding relation in.

The third mode, detects the time period at current time place; Based on the time period detected, from the second presetting database, obtain Intelligent target device identification, the second presetting database comprises time period, corresponding relation between smart machine mark with second frequency.

For the third mode, this Intelligent worn device detects the time period at current time place; Based on the time period detected, identify the corresponding relation between second frequency from the time period that the second presetting database comprises, smart machine, obtain corresponding smart machine mark and second frequency, obtain second frequency that at least one smart machine identifies and this at least one smart machine mark is corresponding; Based on second frequency that this at least one smart machine mark is corresponding, determine the probability that this at least one smart machine identifies; Based on the probability of this at least one smart machine mark, determine Intelligent target device identification.

It should be noted that, when this Intelligent worn device detects the time period at current time place, the time period that this Intelligent worn device can comprise based on the second presetting database, time period in corresponding relation between smart machine mark and second frequency is determined, certainly, the time period that this Intelligent worn device also can not comprise based on the second presetting database, time period in corresponding relation between smart machine mark and second frequency is determined, that is to say, the time period at this Intelligent worn device detection current time place can be identical with the time period at current time place in the second presetting database, also the time period at current time place in the second presetting database can be less than, disclosure embodiment does not do concrete restriction to this.

In addition, the length of the time period at current time place can be 20 minutes, 25 minutes or 30 minutes, and may be also other times segment length certainly, the disclosure do concrete restriction to this.

Wherein, this Intelligent worn device is based on second frequency of this at least one smart machine mark correspondence, determine that the operation of the probability that this at least one smart machine identifies can be: this Intelligent worn device determines the accumulated value of second frequency that each smart machine mark is corresponding in this at least one smart machine mark, obtains second total frequency; For the arbitrary smart machine mark in this at least one smart machine mark, by second corresponding for this smart machine mark frequency divided by second total frequency, obtain the probability of this smart machine mark, thus obtain the probability of this at least one smart machine mark.

In addition, the probability that this Intelligent worn device identifies based on this at least one smart machine, determine that the operation of Intelligent target device identification can be: the probability that this at least one smart machine identifies by this Intelligent worn device and probability threshold value compare, thus judge this at least one smart machine mark in whether exist probability be more than or equal to probability threshold value smart machine mark; When there is probability in this at least one smart machine mark and being more than or equal to the smart machine mark of this probability threshold value, from this at least one smart machine mark, the smart machine mark that select probability is maximum; The smart machine of selection mark is defined as Intelligent target device identification.

Such as, Intelligent worn device detects that the time period at current time place is for " 19:00 ~ 19:30 ", now, this Intelligent worn device can based on this time period, from the time period as shown in table 2 below, in corresponding relation between smart machine mark and second frequency, obtain corresponding smart machine mark and second frequency, obtain at least one smart machine mark and be respectively intelligent television and pad, and to obtain second frequency corresponding to intelligent television be 29 times, second frequency that pad is corresponding is 2 times, therefore, the accumulated value of second frequency that each smart machine mark is corresponding in this at least one smart machine mark can be determined, obtaining second total frequency is 31 times, by second corresponding for the intelligent television frequency divided by second total frequency, obtaining probability corresponding to intelligent television is 0.935, by second corresponding for the pad frequency divided by this second total frequency, obtaining probability corresponding to pad is 0.065.If probability threshold value is 0.9, intelligent television and probability corresponding to pad is all compared with this probability threshold value, determines that the probability that intelligent television is corresponding is greater than probability threshold value, and the maximum probability that this intelligent television is corresponding.Therefore, when the time period at current time place is " 19:00 ~ 19:30 ", intelligent television can be defined as Intelligent target device identification.

Table 2

Time period	Smart machine identifies	Second frequency
			19：00～19：30	Televisor	29 times
19：00～19：30	Pad	2 times

It should be noted that, in the disclosed embodiments, the corresponding relation only identified between second frequency for the time period shown in above-mentioned table 2, smart machine is described, and above-mentioned table 2 does not form restriction to disclosure embodiment.

It should be noted that, the time period stored in second presetting database, corresponding relation between smart machine mark and second frequency obtains based on the state of each smart machine in the time cycle multiple in the second preset time period, that is to say, this Intelligent worn device can gather the state of each smart machine in multiple time cycle in the second preset time period, obtain the smart machine mark being in open mode, the time period at place when determining that this smart machine is in open mode, and the degree of incidence that the smart machine of this time period and acquisition identifies, and then by this time period, the smart machine mark obtained, the degree of incidence that the smart machine of this time period and acquisition identifies is stored in the time period that the second presetting database comprises, between smart machine mark and second frequency in corresponding relation.

Wherein, this second presetting database can be stored in Intelligent worn device, certainly, this second presetting database can also be stored in other equipment, such as server, afterwards, this first presetting database can be downloaded to this locality by this Intelligent worn device from server, and the disclosure does not do concrete restriction to this.

Wherein, the length of the second preset time period arranges in advance, and the first preset time period can be 1 month, 2 months or 3 months before current time, and may be also other times length certainly, the disclosure do concrete restriction to this.

Such as, Intelligent worn device acquires in 31 days Mays in 2015 of user, time period is when being " 19:00 ~ 19:30 ", the smart machine being in open mode when " 19:00 ~ 19:30 " is designated intelligent television and pad, and the degree of incidence of intelligent television is 29 times, the degree of incidence of pad is 2 times." 19:00 ~ 19:30 ", " intelligent television " and " 29 times " are stored in the time period of above-mentioned table 2, corresponding relation between smart machine mark with second frequency, in like manner, " 19:00 ~ 19:30 ", " pad " and " 2 times " are stored in the time period of above-mentioned table 2, corresponding relation between smart machine mark with second frequency.

In step 302, based target smart machine identifies, and from the corresponding relation between the smart machine mark stored and vital sign attribute, obtains corresponding vital sign attribute.

For different Intelligent target device identifications, this vital sign attribute corresponding to Intelligent target device identification is different, such as, the vital sign attribute that " intelligent air condition " is corresponding is " body temperature ", and the vital sign attribute of " intelligent running machine " correspondence is " running frequency ".Therefore, this Intelligent worn device, before detection vital sign data, needs based on this Intelligent target device identification, from the corresponding relation between the smart machine mark stored and vital sign attribute, obtains corresponding vital sign attribute.

Such as, Intelligent worn device detects being designated " intelligent air condition " of the smart machine that user is using, now, before this intelligence is worn on and detects vital sign data, need to identify based on this smart machine, from the corresponding relation between Intelligent target device identification as shown in table 3 below and vital sign attribute, obtain corresponding vital sign attribute, thus vital sign attribute can be obtained for " body temperature ".

Table 3

Intelligent target device identification	Vital sign attribute
		Intelligent air condition	Body temperature
Intelligent television	Heart rate
		Intelligent earphone	Heart rate
Intelligent running machine	Operating frequency

It should be noted that, in the disclosed embodiments, be only described for the corresponding relation between the smart machine mark shown in above-mentioned table 3 and vital sign attribute, above-mentioned table 3 does not form restriction to disclosure embodiment.

In addition, vital sign attribute is user's vital sign character, such as, vital sign attribute can be body temperature, heart rate, operating frequency or movement range, certainly, this vital sign attribute can also be other vital sign character, and disclosure embodiment is not specifically limited this.

Moreover the corresponding relation between smart machine mark and vital sign attribute can be stored in Intelligent worn device or server, and certainly, this corresponding relation can also be stored in other equipment, and the disclosure does not do concrete restriction to this.

In step 303, based on this vital sign attribute, the vital sign corresponding to this user detects, and obtains the vital sign data corresponding with Intelligent target device identification of this user.

After obtaining vital sign attribute corresponding to Intelligent target device identification, this Intelligent worn device based on this vital sign attribute, can detect the vital sign data corresponding with this vital sign attribute.

Such as, when the vital sign attribute of user is body temperature, this Intelligent worn device can detect the vital sign data corresponding with body temperature, obtains 36.5 degrees Celsius.

In step 304, based target smart machine mark and vital sign data, control Intelligent target equipment.

In the disclosed embodiments, not only server can control Intelligent target equipment, this Intelligent target equipment also can control itself, therefore, after this Intelligent worn device detects the vital sign data corresponding with Intelligent target device identification of user, this Intelligent worn device can be controlled Intelligent target equipment by following two kinds of modes, comprising:

First kind of way, based target smart machine identifies, and vital sign data is sent to server, server is controlled Intelligent target equipment based on vital sign data.

For first kind of way, this vital sign data is sent to mobile terminal by Intelligent worn device, after mobile terminal receives this vital sign data, this vital sign data is sent to server, judge that whether this vital sign data is abnormal by server, when this vital sign data is abnormal, then identified by server based target smart machine, transmit control signal to this Intelligent target equipment, thus realize the control to Intelligent target equipment.

Further, when this vital sign data is normal, this server does not then control Intelligent target equipment, and then wait-receiving mode vital sign data next time.

Wherein, for different smart machines mark and different vital sign attributes, server judges to be illustrated the method difference whether vital sign data is abnormal, that is: by following two kinds of determination methods

Determination methods one, judges this vital sign data whether in normal vital signs data area, when this vital sign data is not in this normal vital signs data area, then determines that this vital sign data is abnormal.When this vital sign data is in this normal vital signs data area, then determine that this vital sign data is normal.

Wherein, normal vital signs data area is the scope at user vital sign data place when carrying out normal behaviour.

In addition, when vital sign data is abnormal, this vital sign data may be less than the minimum value of normal vital signs data area, or, this vital sign data may be greater than the maximal value of normal vital signs data area, and therefore, server can control Intelligent target equipment further by two kinds of strategies, that is: when vital sign data is less than the minimum value of normal vital signs data area, this server can be controlled by tactful twin target smart machine; When vital sign data is greater than the maximal value of this normal vital signs data area, this server can be controlled by strategy two pairs of Intelligent target equipment.

It should be noted that, for different vital sign datas, and different smart machines, strategy one may be different with the particular content of strategy two, and strategy one can be identical with strategy two, also can be different, and disclosure embodiment does not do concrete restriction to this.

Such as, user's normal body temperature range that Intelligent worn device stores is 36.5 ~ 36.8 degrees Celsius, when user uses intelligent air condition, Intelligent worn device detects that the temperature data of user is 36.3 degrees Celsius, and this temperature data is not in normal body temperature range, determine that this temperature data is abnormal, and this temperature data is less than the minimum value of this normal body temperature range, server then adopts tactful twin target smart machine to control, namely send the first control information to intelligent air condition processed, make this intelligent air condition raise indoor temperature.If, Intelligent worn device detects that the temperature data of user is 36.9 degrees Celsius, this temperature data is not in normal body temperature range, determine that this temperature data is abnormal, and this temperature data is greater than the maximal value of this normal body temperature range, server then adopts strategy two pairs of Intelligent target equipment to control, and namely sends the second control information to intelligent air condition, makes this intelligent air condition reduce indoor temperature.

Determination methods two, judges whether the rate of change of this vital sign data is expecting within the scope of vital sign data rate of change, when the rate of change of vital sign data is not when expecting within the scope of vital sign data rate of change, then determines that this vital sign data is abnormal.When the rate of change of vital sign data is when expecting within the scope of vital sign data rate of change, then determine that this vital sign data is normal.

Further, when server often receives a vital sign data, the time of reception of vital sign data and this vital sign data received can be stored.When this server judges that the rate of change of this vital sign data is whether when expecting within the scope of vital sign data rate of change, to subtract each other from the vital sign data that current time the last time receives before the vital sign data that current time can receive by this server and current time, obtain vital sign data variable quantity, to subtract each other from the time of reception of vital sign data that current time the last time receives before current time and current time, obtain time of reception interval, and then by this vital sign data variable quantity divided by time of reception interval, namely the rate of change of vital sign data can be obtained.

In addition, expection vital sign data rate of change scope arranges in advance, and the rate of change scope at the vital sign data place that this expection vital sign data rate of change scope is user when using Intelligent target equipment and produce a desired effect, as intelligent television plays horrow movie, vital sign data is heart rate, therefore, expect that change rate of heartbeat scope is that user reaches when watching this horrow movie and expects the change rate of heartbeat scope of terrified effect.

Moreover, when vital sign data is abnormal, this vital sign data rate of change may be less than the minimum value of expection vital sign data rate of change scope, or, this vital sign data rate of change may be greater than the maximal value of expection vital sign data rate of change scope, therefore, server can control Intelligent target equipment further by two kinds of strategies, that is: when vital sign data rate of change is less than the minimum value of this expection vital sign data rate of change scope, this server can be controlled by strategy three pairs of Intelligent target equipment; When vital sign data rate of change is greater than the maximal value of this expection vital sign data rate of change scope, this server can be controlled by strategy four pairs of Intelligent target equipment;

It should be noted that, for different vital sign datas, and different smart machines, strategy three may be different with the particular content of strategy four, and strategy three can be identical with strategy four, also can be different, and disclosure embodiment does not do concrete restriction to this.

Such as, when user sees horror film by intelligent television, expection change rate of heartbeat scope is 5 ~ 10 beats/min, when the change rate of heartbeat that Intelligent worn device detects user is 0 beat/min, determine this change rate of heartbeat not within the scope of expection change rate of heartbeat, determine that this heart rate is abnormal, and this change rate of heartbeat is less than the minimum value of expection change rate of heartbeat scope, server then adopts strategy three pairs of TVs to control, namely send information to this intelligent television, make this intelligent television point out user to change a film; When the change rate of heartbeat that Intelligent worn device detects user is 15 beats/min, determine this change rate of heartbeat not within the scope of expection change rate of heartbeat, determine that this heart rate is abnormal, and this change rate of heartbeat is greater than the maximal value of expection change rate of heartbeat scope, server then adopts strategy two pairs of intelligent televisions to control, namely information is sent to this intelligent television, this intelligent television is made to point out user to change a film, or send to this intelligent television and stop broadcast information, make this intelligent television stop playing this horrow movie.

The second way, based target smart machine identifies, and vital sign data is sent to Intelligent target equipment by server, Intelligent target equipment is controlled Intelligent target equipment based on vital sign data.

For the second way, this vital sign data is sent to mobile terminal by Intelligent worn device, after mobile terminal receives this vital sign data, this vital sign data is sent to server, after server receives this vital sign data, this vital sign data is sent to Intelligent target equipment, judge that whether this vital sign data is abnormal by Intelligent target equipment again, when this vital sign data is abnormal, then control this Intelligent target equipment itself, thus realize the control to Intelligent target equipment.

Further, when this vital sign data is normal, this Intelligent target equipment then itself does not control this Intelligent target equipment, and then wait-receiving mode vital sign data next time.

In the disclosed embodiments, the Intelligent worn device of being dressed by user determines the current Intelligent target device identification used of user, and based on this Intelligent target device identification, obtain the vital sign data corresponding with Intelligent target device identification of user, based on this Intelligent target device identification and vital sign data, this Intelligent target equipment is controlled, thus avoids the Non-follow control of user to Intelligent target equipment, improve the control efficiency of Intelligent target equipment.

Fig. 4 is control device 400 block diagram of a kind of smart machine according to an exemplary embodiment.See Fig. 4, this device comprises:

Determination module 401, for determining Intelligent target device identification, this Intelligent target device identification is the mark of the current smart machine used of user;

Acquisition module 402, for based on this Intelligent target device identification, obtains the vital sign data corresponding with Intelligent target device identification of this user;

Control module 403, for based on this Intelligent target device identification and this vital sign data, controls this Intelligent target equipment.

In another embodiment of the present disclosure, determination module 401 comprises:

Receiving element, for receiving the opening of device information that this Intelligent target equipment sends, this opening of device information carries this Intelligent target device identification, and opening of device information is opened for identifying this Intelligent target equipment.

In another embodiment of the present disclosure, see Fig. 5, determination module 401 comprises:

First detecting unit 4011, for detecting the user behavior of current time;

First acquiring unit 4012, for based on this user behavior, from the first presetting database, obtains Intelligent target device identification, and the first presetting database comprises user behavior, corresponding relation between smart machine mark with first frequency.

In another embodiment of the present disclosure, see Fig. 6, the first acquiring unit 4012 comprises:

First obtains subelement 40121, for based on this user behavior, comprise user behavior from the first presetting database, smart machine identifies the corresponding relation between first frequency, obtain first frequency of at least one smart machine mark and at least one smart machine mark correspondence;

First determines subelement 40122, for first frequency based at least one smart machine mark correspondence, determines the probability that this at least one smart machine identifies;

Second determines subelement 40123, for the probability identified based on this at least one smart machine, determines Intelligent target device identification.

In another embodiment of the present disclosure, second determine subelement 40123 specifically for:

In another embodiment of the present disclosure, first determine subelement 40122 specifically for:

Determine the accumulated value of first frequency that each smart machine mark is corresponding at least one smart machine mark, obtain first total frequency;

For the arbitrary smart machine mark in this at least one smart machine mark, by first corresponding for the smart machine mark frequency divided by first total frequency, obtain the probability of this smart machine mark.

In another embodiment of the present disclosure, see Fig. 7, determination module 401 comprises:

First determining unit 4013, for determining the time period at current time place;

Second acquisition unit 4014, for based on this time period, from the second presetting database, obtains Intelligent target device identification, and the second presetting database comprises time period, corresponding relation between smart machine mark with second frequency.

In another embodiment of the present disclosure, see Fig. 8, second acquisition unit 4014 comprises:

Second obtains subelement 40141, for based on the time period, identify the corresponding relation between second frequency from the time period that the second presetting database comprises, smart machine, obtain second frequency of at least one smart machine mark and at least one smart machine mark correspondence;

3rd determines subelement 40142, for second frequency based on this at least one smart machine mark correspondence, determines the probability that this at least one smart machine identifies;

4th determines subelement 40143, for the probability identified based at least one smart machine, determines Intelligent target device identification.

In another embodiment of the present disclosure, the 3rd determine subelement 40142 specifically for:

Determine the accumulated value of second frequency that each smart machine mark is corresponding in this at least one smart machine mark, obtain second total frequency;

For the arbitrary smart machine mark in this at least one smart machine mark, by second corresponding for this smart machine mark frequency divided by second total frequency, obtain the probability of this smart machine mark.

In another embodiment of the present disclosure, see Fig. 9, acquisition module 402 comprises:

3rd acquiring unit 4021, for based target smart machine mark, from the corresponding relation between the smart machine mark stored and vital sign attribute, obtains corresponding vital sign attribute;

Second detecting unit 4022, based on this vital sign attribute, the vital sign corresponding to user detects, and obtains the vital sign data corresponding with Intelligent target device identification of user.

In another embodiment of the present disclosure, control module 403 comprises:

First transmitting element, for based on this Intelligent target device identification, sends to server by this vital sign data, and server is controlled this Intelligent target equipment based on this vital sign data;

Or,

Second transmitting element, for based target smart machine mark, sends to this Intelligent target equipment by this vital sign data by server, Intelligent target equipment is controlled this Intelligent target equipment based on this vital sign data.

About the device in above-described embodiment, wherein the concrete mode of modules executable operations has been described in detail in about the embodiment of the method, will not elaborate explanation herein.

Figure 10 is the block diagram of a kind of control device 1000 for smart machine according to an exemplary embodiment.Such as, device 1000 can be Intelligent bracelet, intelligent glasses, intelligent ear muff, intelligent necklace, mobile phone, computing machine, digital broadcast terminal, messaging devices, game console, tablet device, Medical Devices, body-building equipment, personal digital assistant etc.

With reference to Figure 10, device 1000 can comprise following one or more assembly: processing components 1002, storer 1004, power supply module 1006, multimedia groupware 1008, audio-frequency assembly 1010, the interface 1012 of I/O (I/O), sensor module 1014, and communications component 1016.

The integrated operation of the usual control device 1000 of processing components 1002, such as with display, call, data communication, camera operation and record operate the operation be associated.Treatment element 1002 can comprise one or more processor 1020 to perform instruction, to complete all or part of step of above-mentioned method.In addition, processing components 1002 can comprise one or more module, and what be convenient between processing components 1002 and other assemblies is mutual.Such as, processing element 1002 can comprise multi-media module, mutual with what facilitate between multimedia groupware 1008 and processing components 1002.

Storer 1004 is configured to store various types of data to be supported in the operation of equipment 1000.The example of these data comprises for any application program of operation on device 1000 or the instruction of method, vital sign data, time, video etc.Storer 1004 can be realized by the volatibility of any type or non-volatile memory device or their combination, as static RAM (SRAM), Electrically Erasable Read Only Memory (EEPROM), Erasable Programmable Read Only Memory EPROM (EPROM), programmable read only memory (PROM), ROM (read-only memory) (ROM), magnetic store or flash memory.

The various assemblies that electric power assembly 1006 is device 1000 provide electric power.Electric power assembly 1006 can comprise power-supply management system, one or more power supply, and other and the assembly generating, manage and distribute electric power for device 1000 and be associated.

Multimedia groupware 1008 is included in the screen providing an output interface between described device 1000 and user.In certain embodiments, screen can comprise liquid crystal display (LCD) and touch panel (TP).If screen comprises touch panel, screen may be implemented as touch-screen, to receive the input signal from user.Touch panel comprises one or more touch sensor with the gesture on sensing touch, slip and touch panel.Described touch sensor can the border of not only sensing touch or sliding action, but also detects the duration relevant to described touch or slide and pressure.In certain embodiments, multimedia groupware 1008 comprises a front-facing camera and/or post-positioned pick-up head.When equipment 1000 is in operator scheme, during as screening-mode or video mode, front-facing camera and/or post-positioned pick-up head can receive outside multi-medium data.Each front-facing camera and post-positioned pick-up head can be fixing optical lens systems or have focal length and optical zoom ability.

Audio-frequency assembly 1010 is configured to export and/or input audio signal.Such as, audio-frequency assembly 1010 comprises a microphone (MIC), and when device 1000 is in operator scheme, during as call model, logging mode and speech recognition mode, microphone is configured to receive external audio signal.The sound signal received can be stored in storer 1004 further or be sent via communications component 1016.In certain embodiments, audio-frequency assembly 1010 also comprises a loudspeaker, for output audio signal.

I/O interface 1012 is for providing interface between processing components 1002 and peripheral interface module, and above-mentioned peripheral interface module can be keyboard, some striking wheel, button etc.These buttons can include but not limited to: home button, volume button, start button and locking press button.

Sensor module 1014 comprises one or more sensor, for providing the state estimation of various aspects for device 1000.Such as, sensor module 1014 can detect the opening/closing state of equipment 1000, the relative positioning of assembly, such as described assembly is display and the keypad of device 1000, the position of all right pick-up unit 1000 of sensor module 1014 or device 1000 assemblies changes, the presence or absence that user contacts with device 1000, the temperature variation of device 1000 orientation or acceleration/deceleration and device 1000.Sensor module 1014 can comprise proximity transducer, be configured to without any physical contact time detect near the existence of object.Sensor module 1014 can also comprise optical sensor, as CMOS or ccd image sensor, for using in imaging applications.In certain embodiments, this sensor module 1014 can also comprise acceleration transducer, gyro sensor, Magnetic Sensor, pressure transducer or temperature sensor.

Communications component 1016 is configured to the communication being convenient to wired or wireless mode between device 1000 and other equipment.Device 1000 can access the wireless network based on communication standard, as WiFi, 2G or 3G, or their combination.In one exemplary embodiment, communication component 1016 receives from the broadcast singal of external broadcasting management system or broadcast related information via broadcast channel.In one exemplary embodiment, described communication component 1016 also comprises near-field communication (NFC) module, to promote junction service.Such as, can based on radio-frequency (RF) identification (RFID) technology in NFC module, Infrared Data Association (IrDA) technology, ultra broadband (UWB) technology, bluetooth (BT) technology and other technologies realize.

In the exemplary embodiment, device 1000 can be realized, for performing said method by one or more application specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing appts (DSPD), programmable logic device (PLD) (PLD), field programmable gate array (FPGA), controller, microcontroller, microprocessor or other electronic components.

In the exemplary embodiment, additionally provide a kind of non-transitory computer-readable recording medium comprising instruction, such as, comprise the storer 1004 of instruction, above-mentioned instruction can perform said method by the processor 1020 of device 1000.

Such as, described non-transitory computer-readable recording medium can be ROM, random access memory (RAM), CD-ROM and optical data storage devices etc.

A kind of non-transitory computer-readable recording medium, when the instruction in described storage medium is performed by the processor of mobile terminal, make mobile terminal can perform a kind of control method of smart machine, described method comprises:

Determine Intelligent target device identification, this Intelligent target device identification is the mark of the current smart machine used of user;

Based target smart machine identifies, and obtains the vital sign data corresponding with Intelligent target device identification of user;

Based target smart machine mark and vital sign data, control this Intelligent target equipment.

Detect the user behavior of current time;

Based on user behavior, from the first presetting database, obtain Intelligent target device identification, the first presetting database comprises user behavior, corresponding relation between smart machine mark with first frequency.

Based on this user behavior, comprise user behavior from the first presetting database, smart machine identifies the corresponding relation between first frequency, obtain first frequency of at least one smart machine mark and at least one smart machine mark correspondence;

Based on first frequency that this at least one smart machine mark is corresponding, determine the probability that at least one smart machine identifies;

Based on the probability that at least one smart machine identifies, determine Intelligent target device identification.

In another embodiment of the present disclosure, based on the probability that at least one smart machine identifies, determine Intelligent target device identification, comprising:

Based on the probability that at least one smart machine identifies, judge at least one smart machine mark in whether exist probability be more than or equal to probability threshold value smart machine mark;

When there is probability at least one smart machine mark and being more than or equal to the smart machine mark of this probability threshold value, from least one smart machine mark, the smart machine mark that select probability is maximum;

In another embodiment of the present disclosure, based on first frequency that at least one smart machine mark is corresponding, determine to comprise the probability that at least one smart machine identifies:

For the arbitrary smart machine mark at least one smart machine mark, by first corresponding for the smart machine mark frequency divided by first total frequency, obtain the probability of this smart machine mark.

Determine the time period at current time place;

Based on the time period, from the second presetting database, obtain Intelligent target device identification, this second presetting database comprises time period, corresponding relation between smart machine mark with second frequency.

Based on this time period, identify the corresponding relation between second frequency from the time period that the second presetting database comprises, smart machine, obtain second frequency of at least one smart machine mark and at least one smart machine mark correspondence;

In another embodiment of the present disclosure, based on second frequency that at least one smart machine mark is corresponding, determine to comprise the probability that this at least one smart machine identifies:

Determine the accumulated value of second frequency that each smart machine mark is corresponding at least one smart machine mark, obtain second total frequency;

For the arbitrary smart machine mark at least one smart machine mark, by second corresponding for this smart machine mark frequency divided by this second total frequency, obtain the probability of this smart machine mark.

Based on vital sign attribute, the vital sign corresponding to user detects, and obtains the vital sign data corresponding with Intelligent target device identification of user.

In another embodiment of the present disclosure, based target smart machine mark and vital sign data, control Intelligent target equipment, comprising:

Based target smart machine identifies, and vital sign data is sent to server, this server is controlled this Intelligent target equipment based on this vital sign data;

Or,

Based target smart machine identifies, and vital sign data is sent to Intelligent target equipment by server, this Intelligent target equipment is controlled this Intelligent target equipment based on this vital sign data.

Those skilled in the art, at consideration instructions and after putting into practice invention disclosed herein, will easily expect other embodiment of the present invention.The application is intended to contain any modification of the present invention, purposes or adaptations, and these modification, purposes or adaptations are followed general principle of the present invention and comprised the undocumented common practise in the art of the disclosure or conventional techniques means.Instructions and embodiment are only regarded as exemplary, and true scope of the present invention and spirit are pointed out by claim below.

Should be understood that, the present invention is not limited to precision architecture described above and illustrated in the accompanying drawings, and can carry out various amendment and change not departing from its scope.Scope of the present invention is only limited by appended claim.

Claims

1. a control method for smart machine, is characterized in that, described method comprises:

2. the method for claim 1, is characterized in that, describedly determines Intelligent target device identification, comprising:

3. the method for claim 1, is characterized in that, describedly determines Intelligent target device identification, comprising:

Detect the user behavior of current time;

4. method as claimed in claim 3, is characterized in that, described based on described user behavior, from the first presetting database, obtains Intelligent target device identification, comprising:

5. method as claimed in claim 4, is characterized in that, the described probability based on described at least one smart machine mark, determines Intelligent target device identification, comprising:

6. method as claimed in claim 4, is characterized in that, described first frequency corresponding based on described at least one smart machine mark, determines the probability of described at least one smart machine mark, comprising:

7. the method for claim 1, is characterized in that, describedly determines Intelligent target device identification, comprising:

Determine the time period at current time place;

8. method as claimed in claim 7, is characterized in that, described based on the described time period, from the second presetting database, obtains Intelligent target device identification, comprising:

9. method as claimed in claim 8, is characterized in that, described second frequency corresponding based on described at least one smart machine mark, determines the probability of described at least one smart machine mark, comprising:

10. the method for claim 1, is characterized in that, described based on described Intelligent target device identification, obtains the vital sign data corresponding with described Intelligent target device identification of described user, comprising:

11. the method for claim 1, is characterized in that, described based on described Intelligent target device identification and described vital sign data, control, comprising described Intelligent target equipment:

Or,

The control device of 12. 1 kinds of smart machines, is characterized in that, described device comprises:

13. devices as claimed in claim 12, it is characterized in that, described determination module comprises:

14. devices as claimed in claim 12, it is characterized in that, described determination module comprises:

First detecting unit, for detecting the user behavior of current time;

15. devices as claimed in claim 14, it is characterized in that, described first acquiring unit comprises:

16. devices as claimed in claim 15, is characterized in that,

Described second determine subelement specifically for:

17. devices as claimed in claim 15, is characterized in that,

Described first determine subelement specifically for:

18. devices as claimed in claim 12, it is characterized in that, described determination module comprises:

First determining unit, for determining the time period at current time place;

19. devices as claimed in claim 18, it is characterized in that, described second acquisition unit comprises:

20. devices as claimed in claim 19, is characterized in that,

Described 3rd determine subelement specifically for:

21. devices as claimed in claim 12, it is characterized in that, described acquisition module comprises:

22. devices as claimed in claim 12, it is characterized in that, described control module comprises:

Or,

The control device of 23. 1 kinds of smart machines, is characterized in that, described device comprises:

Processor;

For the storer of storage of processor executable instruction;

Wherein, described processor is configured to: