CN108173722B - Automatic operation method of intelligent household equipment - Google Patents

Abstract

The invention relates to an automatic operation method of intelligent household equipment, which is used for a plurality of pieces of equipment which are accessed to a home server and are allowed to automatically operate, and comprises the following steps: an initial learning stage and a use and feedback updating stage; by recording the use condition of the equipment in each time period and a statistical method of data, whether the equipment needs to automatically run according to the habit of a user can be analyzed, and the habitual operation of the user can be controlled.

Description

Automatic operation method of intelligent household equipment

Technical Field

The invention relates to the field of home control, in particular to an automatic operation method of intelligent home equipment.

Background

Several current smart home control modes: 1. only the control mode is changed, the physical key is changed into modes such as gestures, voice and the like, but the user is still required to start the keyboard by himself; 2. the identity, expression or behavior of the user is judged by adopting a camera and combining an image detection and identification technology, but the method needs to configure the camera at home, is difficult to judge if the camera is not shot, and has certain requirements on data processing; 3. the user configures the rules for the intelligent household appliance starting, but the user is still required to configure the rules by himself, and the process is over-modeled. In summary, the current smart home control cannot achieve the purpose of enabling users to really feel intelligent and convenient.

Disclosure of Invention

The invention provides an automatic operation method of intelligent household equipment, which aims to analyze whether the equipment needs to be automatically operated according to the habit of a user or not by recording the use condition of the equipment in each time period and a data statistical method, and can realize control on the habitual operation of the user.

The purpose of the invention is realized by adopting the following technical scheme:

an automatic operation method of smart home equipment, which is used for a plurality of devices which are accessed to a home server and are allowed to automatically operate, and is characterized by comprising the following steps: an initial learning stage and a use and feedback updating stage;

the initial learning phase includes: dividing each day into N time intervals, wherein N is a positive integer value, setting an equipment operation two-dimensional table Tai for each equipment ai which is allowed to automatically operate and accessed to a server, wherein 1< = i < = M and M, i are positive integer values, recording whether the equipment is in an operation state in each time interval j of each day in a corresponding learning cycle of the equipment, wherein 1< = j < = N and j are positive integer values, if the equipment is in the operation state, recording the operation value of the time interval of the day as 1 in the Tai, and if not, recording the operation value of the time interval of the day as 0; finally obtaining an equipment operation two-dimensional table Tai with the horizontal axis being days and the vertical axis being time periods;

accumulating the data of each time interval of the period and then calculating an average value to obtain a time interval running average value of the equipment running in the time interval, wherein the average value is in an interval [0,1 ];

setting a threshold value related to running equipment, and when the time interval running average value of a certain time interval is greater than a preset threshold value, setting the running value of the equipment to be 1 in the time interval of the total equipment running time interval table, otherwise, setting the running value to be 0;

learning all the equipment according to the mode to finally obtain a total equipment operation period table;

in the learning stage, recording the parameters of the equipment operation, and selecting one or more auxiliary situation parameters related to the equipment parameters;

the use and feedback update phase comprises:

detecting whether a user exists in a family range;

when a user exists in the home range, the equipment is triggered to be turned on and off according to the time schedule of the running of the overall equipment;

matching the detected one or more auxiliary situation parameters related to the equipment or the one or more auxiliary situation parameters related to the equipment acquired by the server with the auxiliary situation parameters recorded in the learning stage, searching whether a history record identical to the current auxiliary situation parameter exists, and if so, setting the parameters of the equipment according to the history record;

if no matched historical record is obtained, distance calculation is carried out on the current one or more auxiliary situation parameters and the auxiliary situation parameters recorded in the learning stage by using a mathematical formula to obtain proper operation parameters of the equipment;

the distance calculation of the parameters comprises discretizing the numerical value of the current auxiliary situation parameter according to a standard, then performing distance calculation with the numerical value of the auxiliary situation parameter in the historical log, selecting the tuple with the minimum distance between the value of the current auxiliary situation parameter and the auxiliary situation parameter in the historical log, and setting the current operation parameter as the operation parameter recorded in the tuple with the minimum distance;

when the history of the auxiliary context parameter values conflicts, the later record has higher priority;

obtaining recommended operational parameter settings from the server according to the current auxiliary context parameters.

Preferably, the operating parameters include: volume, temperature, humidity, channel and brightness; the auxiliary context parameters include: time, weather, ambient noise, user location, and user attention information.

Preferably, the auxiliary context parameter is represented in the form of a discrete value, and if the parameter is a non-discrete value, the auxiliary context parameter is converted into a discrete value representation.

Preferably, the discrete values of the auxiliary context parameters related to the operating equipment and the operating parameters are represented in the form of m + n tuples, wherein m is a parameter name, n is a parameter discrete value, and the discrete values of the auxiliary context parameters related to the operating equipment are uniformly recorded in a history log of the operating equipment.

Preferably, the detecting whether the user exists in the home range includes: whether the user exists in the family range is detected through the intelligent bracelet and the mobile phone.

Preferably, the update cycle is set to 1 day, and when the update cycle arrives, the time interval running average value is calculated again according to the historical data of the new device running two-dimensional table.

Preferably, the behavior and the times of manual adjustment of the equipment by the user are recorded, and the judgment threshold value of the equipment is adjusted according to the behavior and the times and the preset rule;

and updating the total equipment operation time segment table according to the new time segment operation mean value and the adjusted judgment threshold value, and operating the equipment according to the updated total equipment operation time segment table.

The invention has the beneficial effects that:

according to the technical scheme provided by the invention, whether the equipment needs to automatically run according to the habit of the user can be analyzed by recording the use condition of the equipment in each time period and a data statistical method, and the habitual operation of the user can be controlled.

Drawings

Fig. 1 is a flowchart of an automatic operation method of smart home devices according to the present invention.

Detailed Description

The following detailed description of embodiments of the invention refers to the accompanying drawings.

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Embodiment mode 1

As shown in fig. 1, the method is applied to a plurality of devices a1 and a2 … aM which access a home server and allow automatic operation. The method comprises an initial learning phase, a use and feedback updating phase.

An initial learning stage:

dividing each day into N periods, setting an equipment operation two-dimensional table Tai for each access server allowed automatic operation equipment ai (1< = i < = M), recording whether the equipment is in an operation state in each period j (1< = j < = N) of each day in a learning cycle corresponding to the equipment, if so, recording the period operation value of the period as 1, otherwise, recording the period operation value as 0. And finally obtaining a device operation two-dimensional table with the horizontal axis as days and the vertical axis as time periods.

And accumulating the data of each period of the period, and dividing the data by the total days of the period to obtain the average value of the operation of the equipment in the period, wherein the average value is between the intervals [0,1 ].

Setting a threshold value related to the running equipment, and when the section running average value is greater than the preset threshold value, considering that the possibility that the equipment is required to be in a running state by a user in the section is very high, setting the running value of the equipment to be 1 in the section of the overall equipment running section table, and otherwise, setting the running value to be 0.

An example of a hypothetical device is as follows:

in fig. 1, the device of device a1 runs two-dimensional table Ta1, and assuming a learning period of 10 days, the threshold value for this device is 0.6.

Time period	Day 1	Day 2	…	Day 10	Total of	Time interval running average
							1	1	1		1	10	1
2	0	1		0	7	0.7
							3	0	0		0	3	0.3
…	…	…	…	…	…	…
							N	1	1		1	9	0.9

Then it can be seen from the results of the above example table that the device should be turned on for periods 1, 2 and N, while period 3 is not automatically turned on because it is less than the threshold, so the corresponding period in the runtime period table is added to the device ID, setting the value of the device to 1, and otherwise to 0.

And learning all the equipment according to the mode to finally obtain the total equipment operation period table.

Example (c): overall device runtime segment table

Time period	Device a1	Device a2	Device a3
				1	1	0	0
2	1	0	0
				3	0	0	1
…	…
				N	1	1	0

In the learning stage, parameters of the device operation and auxiliary context parameters associated with the device parameters are also recorded, and the operation parameters include but are not limited to: volume, temperature, humidity, channel, brightness, etc.; auxiliary context parameters include, but are not limited to: time, weather, ambient noise, user location, user attention information, etc., which are stored in the form of discrete values. If the initial value is a discrete value, it is directly stored, and if the value is not a discrete value, it needs to be converted.

For example:

the current air temperature is 34 degrees celsius and humidity is 70%, this parameter is matched with the values of the tuples in the history library, finding in the history library the value of < temperature: 27 degrees, wind power: stroke, mode: refrigeration, air temperature: 34 facility degree, humidity: 70% >, then the current operating parameters are set to temperature: 27 degrees, wind power: stroke, mode: and (5) refrigerating.

If no matched record is found, calculation is carried out according to a mathematical formula, for example, 2 parameters are currently available, and the history record with the minimum distance in the two-dimensional coordinate system is calculated and set by taking the 2 parameters as coordinates.

If 2 identical history records are found, the operating parameters are set based on the records of the later date.

And a use and feedback updating stage:

the server detects whether a user exists in a family range or not, and can judge through various modes such as an intelligent bracelet, a mobile phone, sound, an image and the like.

When detecting that there is the user to exist in the home range, according to the total equipment operation time period table, trigger the opening and closing of equipment according to the time period, specifically, when the time period value is 1, open equipment, when the time period value is 0, close equipment, when the time period value jumps from 1 to 0, close equipment, when the time period value jumps from 0 to 1, open equipment, and other circumstances are unchangeable.

And matching or fitting the detected situation parameters or the situation parameters acquired through the server with the situation parameters recorded in the learning stage to obtain the proper operation parameters of the equipment.

Setting an updating period to be 1 day, and calculating the running state mean value again according to the historical data of a new device running two-dimensional table when the updating period comes;

and recording the adjustment action and times of the device manually performed by the user, and adjusting the judgment threshold value of the device according to the action and times and a preset rule.

And updating the running time segment table of the overall equipment according to the new running state mean value and the adjusted judgment threshold value, and running the equipment according to the updated running time segment table of the overall equipment.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.

Claims (7)

1. An automatic operation method of smart home equipment, which is used for a plurality of devices which are accessed to a home server and are allowed to automatically operate, and is characterized by comprising the following steps: an initial learning stage and a use and feedback updating stage;

the initial learning phase includes: dividing each day into N time intervals, wherein N is a positive integer value, setting an equipment operation two-dimensional table Tai for each equipment ai which is allowed to automatically operate and accessed to a server, wherein 1< = i < = M and M, i are positive integer values, recording whether the equipment is in an operation state in each time interval j of each day in a corresponding learning cycle of the equipment, wherein 1< = j < = N and j are positive integer values, if the equipment is in the operation state, recording the operation value of the time interval of the day as 1 in the Tai, and if not, recording the operation value of the time interval of the day as 0; finally obtaining an equipment operation two-dimensional table Tai with the horizontal axis being days and the vertical axis being time periods;

accumulating the data of each time interval of the period and then calculating an average value to obtain a time interval running average value of the equipment running in the time interval, wherein the average value is in an interval [0,1 ];

setting a threshold value related to running equipment, and when the time interval running average value of a certain time interval is greater than a preset threshold value, setting the running value of the equipment to be 1 in the time interval of the total equipment running time interval table, otherwise, setting the running value to be 0;

learning all the equipment according to the mode to finally obtain a total equipment operation period table;

in the learning stage, recording the parameters of the equipment operation, and selecting one or more auxiliary situation parameters related to the equipment parameters;

the use and feedback update phase comprises:

detecting whether a user exists in a family range;

when a user exists in the home range, the equipment is triggered to be turned on and off according to the time schedule of the running of the overall equipment;

matching the detected one or more auxiliary situation parameters related to the equipment or the one or more auxiliary situation parameters related to the equipment acquired by the server with the auxiliary situation parameters recorded in the learning stage, searching whether a history record identical to the current auxiliary situation parameter exists, and if so, setting the parameters of the equipment according to the history record;

if no matched historical record is obtained, distance calculation is carried out on the current one or more auxiliary situation parameters and the auxiliary situation parameters recorded in the learning stage by using a mathematical formula to obtain proper operation parameters of the equipment;

the distance calculation of the parameters comprises discretizing the numerical value of the current auxiliary situation parameter according to a standard, then performing distance calculation with the numerical value of the auxiliary situation parameter in the historical log, selecting the tuple with the minimum distance between the value of the current auxiliary situation parameter and the auxiliary situation parameter in the historical log, and setting the current operation parameter as the operation parameter recorded in the tuple with the minimum distance;

when the history of the auxiliary context parameter values conflicts, the later record has higher priority;

obtaining recommended operational parameter settings from the server according to the current auxiliary context parameters.

2. The method of claim 1, wherein the operating parameters comprise: volume, temperature, humidity, channel and brightness; the auxiliary context parameters include: time, weather, ambient noise, user location, and user attention information.

3. A method as claimed in claim 2, wherein the auxiliary context parameter is represented in discrete value form, and if the parameter is a non-discrete value it is converted to a discrete value form representation.

4. The method of claim 3, wherein the discrete values of the auxiliary context parameters related to the running equipment and the running parameters are represented in m + n tuples, wherein m is a parameter name, and n is a parameter discrete value, and the discrete values of the auxiliary context parameters related to the running equipment are uniformly recorded in a history log of the running equipment.

5. The method of claim 1, wherein said detecting the presence of a user within a home comprises: whether the user exists in the family range is detected through the intelligent bracelet and the mobile phone.

6. The method of claim 1, wherein the update cycle is set to 1 day, and when the update cycle comes, the time-interval running average is recalculated based on the historical data of the new device running two-dimensional table.

7. The method of claim 1, wherein the behavior and the number of times of manual adjustments of the device by the user are recorded, and the decision threshold of the device is adjusted according to the behavior and the number of times and a predetermined rule;

and updating the total equipment operation time segment table according to the new time segment operation mean value and the adjusted judgment threshold value, and operating the equipment according to the updated total equipment operation time segment table.

Images