KR20130055503A - User movement state estimation device and method for user movement state estimation - Google Patents

Abstract

PURPOSE: A movement state estimating device and a movement state estimating method are provided to calculate a movement state of a user with an accelerometer and a digital compass, thereby accurately estimating the movement state. CONSTITUTION: A movement state estimating device(100) comprises a sensor unit(110) and a movement state determining unit(130). The sensor unit includes an accelerometer(111) sensing the acceleration information of a mobile device(1000) and a digital compass(112) sensing the directional angle information of the mobile device. The movement state determining unit determines a movement state of a user as one among a walking state, a moving state using a vehicle, and a stopped state based on the acceleration information sensed by the accelerometer and the direction angle information sensed by the digital compass. [Reference numerals] (100) Movement state estimating device; (1000) Mobile device; (110) Sensor unit; (111) Accelerometer; (112) Digital compass; (120) Threshold setting unit; (130) Movement state determining unit

Description

{MOVEMENT STATE ESTIMATION DEVICE AND METHOD FOR USER MOVEMENT STATE ESTIMATION}

The present invention relates to a movement state prediction apparatus and a movement state prediction method.

With the development of the mobile communication field, mobile devices such as smartphones and tablet PCs have also developed. Mobile devices, such as smartphones and tablet PCs, are equipped with a global positioning system (GPS) for locating mobile device users and for navigating directions.

Mobile devices also include accelerometers and digital compasses for use in many mobile applications, such as games, racing games, educational programs, and pedometers, which are reminiscent of a user's direct steering wheel. Accelerometers and digital compasses can also track the movement of mobile devices.

In this regard, the Korean Laid-open Patent Application (Application No. 2005-0088120) detects the movement of the aiming device by means of a digital compass and an accelerometer, and uses the system according to the intuitive real spatial aiming to intuitively and remotely control the target devices. And its identification method and communication method.

Using GPS to determine location information can be more precise and accurate than location information using only the digital compass and accelerometer. However, since GPS receives signals from satellites, it is not easy to receive in an indoor space, affects battery consumption of a mobile device, and has various problems such as privacy infringement that exposes location information even if a user does not want it.

In addition, the use of GPS is limited depending on the hardware performance of the mobile device, and is inadequate for low-performance miniaturized mobile devices.

Due to the shortcomings of GPS, it is necessary to develop a motion state prediction device and a motion state prediction method that do not degrade GPS performance by using an accelerometer and a digital compass that are basically included in a mobile device without adding GPS.

One embodiment of the present invention has been created to solve the problems described above, the problem to be solved by the present invention is the movement included in the mobile device for determining the movement state of the mobile device user using an accelerometer and a digital compass The present invention relates to a state prediction device and a moving state prediction method.

As a technical means for achieving the above technical problem, the device for predicting the movement state of the mobile device user according to the first aspect of the present application is an accelerometer for detecting the acceleration information of the mobile device and a digital compass for detecting the direction angle information Sensor unit comprising; The moving state determination unit may determine the moving state of the user as one of a walking state, a vehicle moving state, and a fixed state based on the acceleration information detected by the accelerometer and the direction angle information detected by the digital compass. .

According to a second aspect of the present invention, a method of predicting a mobile device user's movement state may include (a) collecting data according to one or more of a walking habit, a sitting habit, and a behavioral habit of the mobile device user, such that the threshold value of the accelerometer and digital Setting a threshold of the compass; calculating acceleration of the mobile device by applying acceleration information sensed by the accelerometer to the set threshold value; (c) calculating the movement of the mobile device by applying the direction angle information detected by the digital compass to the set threshold value; And (d) determining the moving state of the mobile device user as one of a walking state, a vehicle moving state, and a fixed state based on the information calculated through the steps (b) and (c).

According to an embodiment of the present invention, by calculating the user's movement through the accelerometer and the user's movement through the digital compass, it is possible to more accurately predict the movement state.

In addition, by setting the threshold value by collecting data according to the user's habit, it is possible to accurately predict the moving state by reducing the error that can be changed according to the user's habit.

1 is a schematic structural diagram of an apparatus for predicting movement state according to an embodiment of the present invention.
2 is a diagram illustrating a variable in Euclidean semi-norm according to an embodiment of the present invention.
3 is a diagram illustrating determining a moving state using an accelerometer and a digital compass according to an embodiment of the present invention.
4 is a diagram illustrating calculating and determining a moving state by using a variable value according to an embodiment of the present invention.
5 is a flowchart illustrating a moving state prediction method according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily carry out the present invention. It should be understood, however, that the present invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In the drawings, the same reference numbers are used throughout the specification to refer to the same or like parts.

Throughout this specification, when a part is referred to as being "connected" to another part, it is not limited to a case where it is "directly connected" but also includes the case where it is "electrically connected" do.

Throughout this specification, when an element is referred to as "including " an element, it is understood that the element may include other elements as well, without departing from the other elements unless specifically stated otherwise. The terms "about "," substantially ", etc. used to the extent that they are used throughout the specification are intended to be taken to mean the approximation of the manufacturing and material tolerances inherent in the stated sense, Accurate or absolute numbers are used to help prevent unauthorized exploitation by unauthorized intruders of the referenced disclosure. The word " step (or step) "or" step "used to the extent that it is used throughout the specification does not mean" step for.

1 is a schematic structural diagram of an apparatus for predicting movement state according to an embodiment of the present invention.

Referring to FIG. 1, the movement state predicting apparatus 100 included in the mobile apparatus 1000 includes a sensor unit 110, a threshold setting unit 120, and a movement state determination unit 130.

The sensor unit 110 detects acceleration information and direction angle information of the mobile device 1000. It includes an accelerometer 111 for detecting the acceleration information and a digital compass 112 for detecting the direction angle information. For example, the accelerometer 111 senses acceleration changes in the x, y, and z axis directions. In addition, the digital compass 112 detects direction angle information in a direction moving about the x, y, and z axes.

The threshold setting unit 120 sets a threshold of the sensor unit 110 according to a habit of a user who uses the mobile device 1000. For example, the mobile device 1000 collects data according to user habits such as walking habits, sitting habits, or behavioral habits of the user. The threshold of the accelerometer 111 and the threshold of the digital compass 112 are set based on the collected data.

The reason for setting the threshold value based on data according to a user's habit may be that information detected by the accelerometer 111 and the digital compass 112 may change according to the user's habit. Therefore, by setting the threshold value according to the habit of the user of the mobile device 1000, it is effective to increase the accuracy of the position information detected by the accelerometer 111 and the digital compass 112.

The movement state determination unit 130 determines the movement state of the user based on the position information detected by the sensor unit 110 and the threshold value set by the threshold value setting unit 120. The moving state of the user is determined as one of a walking state, a vehicle moving state, and a fixed state based on the acceleration information detected through the accelerometer 111 and the direction angle information detected through the digital compass 112.

For example, the movement state determiner 130 receives the acceleration information moved on the x, y, and z axes sensed by the accelerometer 111. It also receives direction angle information about the x, y, and z axes sensed from the digital compass 112. The movement state of the user is determined based on the information received from the accelerometer 111 and the digital compass 112 and the threshold information of the accelerometer 111 and the digital compass 112 received from the threshold setting unit 120.

When determining the movement state based on the information detected by the accelerometer 111 and the digital compass 112, the detected information is converted to Euclid semi norm, and converted into a variable at Euclidean semi norm Calculate Euclidean semi-norm exponentially multiplies and adds acceleration values for the x, y, and z axes sensed through the accelerometer 111, and uses the power again. In addition, the exponential powers of the x, y, and z axes sensed through the digital compass 112 may be exponentially added to each other and then may be defined using a power of root again.

2 is a diagram illustrating a variable in Euclidean semi-norm according to an embodiment of the present invention.

를 정의할 수 있다.Referring to (1) of FIG. 2, the powers of the acceleration values for the x, y, and z axes are exponentially increased, and the powers are again shown. Variable A by substituting A value obtained through (1) of FIG. 2 into (2) of FIG.

Can be defined.

로 변환하여 변수값으로 사용한다.

값은 모바일 장치(1000)의 움직임의 불규칙성을 나타내는 변수이다.

값이 커질수록 모바일 장치(1000)의 움직임이 많아지는 것을 나타낸다.

값은 가속도값의 변이를 측정할 수 있는 어떤 공식의 변수로도 대체 가능하다.For example, the acceleration information moved to the x, y, and z axes detected from the accelerometer 111 may be

Convert to and use as variable value.

The value is a variable representing the irregularity of the movement of the mobile device 1000.

As the value increases, the movement of the mobile apparatus 1000 increases.

The value can be replaced by any formula variable that can measure the variation in the acceleration value.

를 구할 수 있다.(3) of FIG. 2 shows exponential powers of the directions of the x, y, and z axes, and adds them to each other again. By applying this value to (4) of FIG. 2, the difference according to the direction value which changes in real time can be calculated | required. In addition, the variable value of (5) of FIG. 2 is applied by applying the time change to obtain the value of (4) of FIG.

Can be obtained.

로 변환하여 변수값으로 사용한다.

값은 모바일 장치(1000)의 곡선 움직임의 빈도를 나타내는 변수이다.

값이 커질수록 모바일 장치(1000) 의 움직임이 많아지는 것을 나타낸다.For example, the direction angle information about the x, y, and z axes detected from the digital compass 112 may be

Convert to and use as variable value.

The value is a variable representing the frequency of the curved movement of the mobile device 1000.

As the value increases, the movement of the mobile apparatus 1000 increases.

For example, the movement state determiner 130 applies the acceleration information detected from the accelerometer 111 to the Euclidean semi-norm as a primary variable, calculates the state, and based on the result, the user's state as a walking state or a non-walking state. To judge. Thereafter, the direction angle information detected from the digital compass 112 as a secondary variable is applied to the Euclidean semi-norm, and then calculated, and based on the result, it is determined as a fixed state or a vehicle moving state in a non-walking state.

In addition, the direction angle information detected from the digital compass 112 as a primary variable is applied to the Euclidean semi-norm and calculated, and based on the result, the user's state is determined as a fixed state or a non-fixed state. Thereafter, the acceleration information detected from the accelerometer 111 as a secondary variable is applied to the Euclidean semi-norm, and then calculated, and based on the result, it may be determined as a walking state or a vehicle moving state in a non-fixed state.

3 is a diagram illustrating determining a moving state using an accelerometer and a digital compass according to an embodiment of the present invention.

Referring to FIG. 3, the above-described movement state determination will be described in detail. Accelerometer 111 set by the acceleration information 111 and the threshold value setting unit 120 moved to the x, y, and z axes sensed in real time by the accelerometer 111. Compare the thresholds. The comparison value is converted to Euclidean semi-norm, the analysis of how the compared value changes according to the user's moving state, and the user's moving state is divided into walking or non-walking state.

Here, the non-walking state is not based on the absolute speed of the user. For example, the user may sit still while surfing the web but sit in the vehicle while moving based on the user's body usage.

Since only the acceleration information using the accelerometer 111 does not accurately determine the movement state of the user, the digital compass 112 is used. The digital compass 112 senses the direction angle information of the non-walking user on the x, y, and z axes. The direction value received in real time from the digital compass 112 and the threshold value of the digital compass 112 set by the threshold setting unit 120 is compared to the Euclidean semi-norm. The converted value is obtained from a time point when the threshold value of the digital compass 112 is exceeded, and is divided into a fixed state or a vehicle use state among non-walking states.

In addition, although not shown in the drawing, in addition to determining the movement state by using the acceleration information detected by the aforementioned accelerometer 111 as the primary variable, the direction angle information detected by the digital compass 112 as the primary variable. Can be used to determine the state of movement.

For example, the moving state of the user is fixed or non-fixed by comparing the direction angle information detected in real time through the digital compass 112 and the threshold of the digital compass 112 set by the threshold setting unit 120. To judge.

When the user's movement state is determined to be non-fixed state, the real-time acceleration information detected by the accelerometer 111 is compared with the accelerometer 111 threshold set by the threshold setting unit 120 to determine the walking state or the vehicle movement state. do.

4 is a diagram illustrating calculating and determining a moving state using a variable value according to an embodiment of the present invention.

When calculating a moving state based on the information detected by the accelerometer 111 and the digital compass 112 described above with reference to FIG. 4, the detected information is converted into a variable to be calculated and moved by the moving state determining unit 130. Examine the process of determining the status.

로 변환하여 변수값으로 사용한다. 변수값

가 가속도 임계값보다 클 경우 사용자의 이동 상태를 보행 상태로 판단한다. 변수값

가 가속도 임계값보다 작거나 같으면 비 보행 상태로 판단한다.First, the acceleration information moved to the x, y, and z axes detected from the accelerometer 111 is applied to the Euclidean semi-norm,

Convert to and use as variable value. Variable value

If is greater than the acceleration threshold value is determined as the walking state of the user walking. Variable value

Is less than or equal to the acceleration threshold, it is determined as a non-walking state.

로 변환하여 변수값으로 사용한다. 변수값

가 방향각 임계값보다 클 경우 사용자의 이동 상태를 고정 상태로 판단한다. 변수값

가 방향각 임계값보다 작으면 차량 이동 상태로 판단한다.Next, when it is determined that the non-walking state, the direction angle information about the x, y, and z axes detected from the digital compass 112 is applied to the Euclidean semi-norm,

Convert to and use as variable value. Variable value

If is greater than the direction angle threshold value determines the user's moving state to a fixed state. Variable value

Is smaller than the direction angle threshold, it is determined that the vehicle is in a moving state.

로 변환 하여 고정 상태 또는 비 고정 상태로 판단한다. 다음으로 비 고정 상태시 가속도계(111)로부터 감지된 정보를 유클리드 세미 노름에 적용하고,

로 변환하여 사용자의 이동 상태를 보행 상태 또는 차량 이동 상태로 판단할 수 있다.In addition, although not shown in the drawing, the above-mentioned movement state is converted into a variable to calculate, and the first process of applying the information detected from the digital compass 112 to the Euclidean semi-norm,

Determine the fixed or non-fixed state by converting to. Next, the information detected from the accelerometer 111 in the non-fixed state is applied to the Euclidean semi-norm,

The moving state of the user may be determined as a walking state or a vehicle moving state by converting to.

The movement state prediction apparatus 100 included in the above-described mobile device does not apply real-time information detected by the accelerometer 111 and the digital compass 112 to the movement state prediction apparatus 100 included in the mobile device in real time. Can be stored using simple memory. For example, based on the stored information, it is possible to statistically calculate the walking, vehicle movement, etc. of the entire population.

In addition, by applying the mobile state information of the user of the mobile device 1000 with the application of the mobile device 1000 can be provided to the user of the mobile device 1000 with a suitable application program according to the user's moving state.

For example, if it is determined that the moving state of the user of the mobile device 1000 is a walking state, an application program for reporting weather information of the current and near time may be executed. In addition, if it is determined that the fixed state, run the application to inform the schedule of the current or one day, and if it is determined that the vehicle movement state, by running the application to inform the traffic status information according to the mobile state of the user of the mobile device 1000 You can run applications that provide convenience.

Hereinafter, the moving state prediction method according to an embodiment of the present invention will be described.

For reference, the movement state prediction method according to an embodiment of the present invention relates to a method of predicting a movement state by using the movement state prediction apparatus 100 according to an embodiment of the present invention. Components similar to those described in the moving state predicting apparatus 100 according to the embodiment are denoted by the same reference numerals, and description thereof will be briefly or omitted.

5 is a flowchart illustrating a moving state prediction method according to an embodiment of the present invention.

Referring to FIG. 5, in the moving state prediction method according to an embodiment of the present invention, first, acceleration and direction angle data according to a user's habit are collected through an accelerometer 111 and a digital compass 112 to set a threshold value. (S510).

The mobile device 1000 collects data according to user habits such as walking habits, sitting habits, or behavioral habits of the user. The reason for collecting data according to a user's habit is x, y centering on the mobile device 1000 which is a reference of information detected by the accelerometer 111 and the digital compass 112 according to the user's habit of the mobile device 1000. This is because the, and z axes can be reversed.

값을 변수로 사용하여 계산한다.

값은 모바일 장치(1000) 움직임의 불규칙성을 나타내며, 이 값이 커질수록 모바일 장치(1000)의 움직임이 많아지는 것을 뜻한다.Next, the acceleration of the mobile device 1000 is calculated by applying the acceleration information sensed by the accelerometer 111 to the set threshold (S520). Apply the detected acceleration information to the Euclidean semi-norm,

Calculate using a value as a variable.

The value represents the irregularity of the movement of the mobile device 1000, and as the value increases, the movement of the mobile device 1000 increases.

값을 변수로 사용하여 계산한다.

값은 모바일 장치(1000)의 곡선 움직임의 빈도를 나태내며, 이 값이 커질수록 모바일 장치(1000)의 움직임이 많아지는 것을 뜻한다.Next, the motion of the mobile apparatus 1000 is calculated by applying the direction angle information detected by the digital compass 112 to the set threshold (S530). Apply the detected direction angle information to the Euclidean semi-norm,

Calculate using a value as a variable.

The value indicates the frequency of the curved movement of the mobile device 1000, which means that as the value increases, the movement of the mobile device 1000 increases.

S520 and S530 are performed through the movement state determination unit 130, in addition to executing S530 after S520, S520 may be executed first and then S520 may be executed. For example, after calculating the movement of the mobile device 1000 by applying the direction angle information detected by the digital compass 112 to the set threshold value, the acceleration information detected by the accelerometer 111 is then set to the set threshold value. The motion of the mobile apparatus 1000 may be calculated by applying to.

The movement state determination unit 130 determines the movement state of the user as one of a walking state, a vehicle movement state, and a fixed state based on the information calculated through S520 and S530 (S540).

For example, after applying the acceleration information detected from the accelerometer 111 to the Euclidean semi-norm, it is calculated using the primary variable, and based on the result of the determination of the user's state as a walking state or a non-walking state. Thereafter, the direction angle information sensed by the digital compass 112 is applied to the Euclidean semi-norm, and then used as a secondary variable, and calculated based on the result.

In addition, after applying the direction angle information sensed from the digital compass 112 to the Euclidean semi-norm, it is calculated as a primary variable, and based on the result, the user's state is determined as a fixed state or a non-fixed state. Thereafter, the acceleration information detected from the accelerometer 111 is applied to the Euclidean semi-norm, and then calculated using the secondary variable, and based on the result, it may be determined as a walking state or a vehicle moving state in a non-fixed state.

It will be understood by those of ordinary skill in the art that the foregoing description of the embodiments is for illustrative purposes and that those skilled in the art can easily modify the invention without departing from the spirit or essential characteristics thereof. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive. For example, each component described as a single entity may be distributed and implemented, and components described as being distributed may also be implemented in a combined form.

The scope of the present invention is defined by the appended claims rather than the detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalents should be construed as being included within the scope of the present invention.

100: movement state prediction device 110: sensor unit
111: accelerometer 112: digital compass
120: threshold setting unit 130: moving state determination unit
1000: Mobile device

Claims (11)

A device for predicting a movement state of a mobile device user,
A sensor unit including an accelerometer for sensing acceleration information of the mobile device and a digital compass for detecting direction angle information of the mobile device; And
A movement state including a movement state determination unit that determines the movement state of the user as a walking state, a vehicle movement state, or a fixed state based on the acceleration information detected by the accelerometer and the direction angle information detected by the digital compass Prediction device.
The method of claim 1,
And a threshold setting unit for setting a threshold of the sensor unit according to the habit of the user.
3. The method of claim 2,
And the threshold setting unit collects the acceleration information and the direction angle information that change according to one or more of a walking habit, a sitting habit, and a behavioral habit of the user to set an acceleration threshold and a direction angle threshold.
The method of claim 1,
And the movement state determination unit determines the movement state of the user by converting information sensed by the accelerometer and the digital compass into Euclid semi norm.
The method of claim 4, wherein
The Euclidean semi-norm is the acceleration information detected from the accelerometer

Converts to and uses it as a variable, and uses the direction angle information detected from the digital compass.

Moving state prediction apparatus for determining the moving state of the user by converting to use as a variable.
The method of claim 1,
The movement state determination unit determines the state of the user as a walking state or a non-walking state based on the acceleration information detected by the accelerometer, and based on the direction angle information detected by the digital compass, the state of the user Is determined to be a non-walking state, the movement state predicting apparatus for determining the state of the user as a fixed state or a vehicle movement state.
The method of claim 1,
The moving state determination unit determines the state of the user as a fixed state or a non-fixed state based on the direction angle information detected by the digital compass, and based on the acceleration information detected by the accelerometer, the state of the user Is determined to be in a non-fixed state, the movement state prediction apparatus for determining the state of the user as a walking state or a vehicle movement state.
What is claimed is: 1. A method for predicting a movement state of a mobile device user,
(a) collecting data according to one or more of the walking habits, sitting habits, and behavioral habits of the mobile device user to set an accelerometer threshold and a digital compass threshold;
calculating acceleration of the mobile device by applying acceleration information sensed by the accelerometer to the set threshold value;
(c) calculating the movement of the mobile device by applying the direction angle information detected by the digital compass to the set threshold value; And
(d) a moving state prediction including determining a moving state of the mobile device user as one of a walking state, a vehicle moving state, and a fixed state based on the information calculated through steps (b) and (c). Way.
The method of claim 8,
The step (b) and (c) further comprises the step (d) after the step (c).
The method of claim 8,
The step (d) is a moving state prediction method for determining the moving state of the user as a walking state or a non-walking state, and determines a fixed state or a vehicle moving state in the non-walking state.
The method of claim 8,
In step (d), the moving state predicting method of the user is determined as a fixed state or a non-fixed state, and when the non-fixed state is determined as a walking state or a vehicle moving state.

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