CN114363452A - Smart phone anti-theft and tracking method based on somatosensory interaction - Google Patents
Smart phone anti-theft and tracking method based on somatosensory interaction Download PDFInfo
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Abstract
The invention discloses a method for preventing and tracking a smart phone based on somatosensory interaction, which comprises the following steps: s1, when the mobile phone is in a standing state or a screen locking state, entering a static anti-theft mode; s2, after detecting that the relevant data of the mobile phone gyroscope changes, sending distance confirmation information to the bracelet at intervals of 3 seconds within the next 20 seconds; s3, after the bracelet receives the distance confirmation information from the mobile phone, the bracelet immediately returns the distance measurement information; s4, distance measurement is carried out at the mobile phone end through the iRss value of the Bluetooth; and S5, transmitting the distance value obtained after measurement to an early warning method. The invention provides a method for preventing and tracking a smart phone based on somatosensory interaction, which can reduce the withdrawal of stolen mobile phone users and effectively prevent and track the stolen mobile phone.
Description
Technical Field
The invention relates to the technical field of anti-theft tracking, and particularly discloses a method for carrying out intelligent mobile phone anti-theft tracking by using somatosensory interaction equipment in a Bluetooth communication mode.
Background
Internationally, McAfe publishes the Android platform-based mobile phone security protection software WaveSecure, so that a user can remotely lock a mobile phone, track the position of the mobile phone through an SIM card, remotely perform data backup of the mobile phone, remotely delete data on the mobile phone, restore data backup to a new mobile phone and the like. In the market of China, some security software companies also develop similar security software, such as 360 security guards, QQ mobile phone stewards and the like, which also provide the security protection function of the mobile phone and gain the favorable comment of users.
Somatosensory interaction is changing the understanding of people on the design of traditional products as a novel interaction mode rich in behavior ability, and exploring a novel behavior mode. Somatosensory interaction is an interaction mode which directly utilizes body motion, sound, eyeball rotation and other modes to interact with peripheral devices or environments.
The powerful performance and the integration of mobile chip let the smart mobile phone obtain stronger computing power, but say and promote user interaction experience, rely on ground to be those sensors that the integration carried in the cell-phone, if: acceleration sensors, gyroscopes and gravity sensors. Most models of smart phones on the market today support three sensor services.
The most important thing in the somatosensory interaction is to acquire the displacement, rotation attitude and behavior characteristics of a moving body in a three-dimensional space, and to show the three parts, the data of an acceleration sensor, a gyroscope and a gravity sensor are required to be used.
Three-axis gyroscope (Gyro-sensor): the principle of the gyroscope is based on a rotating gyroscope, and the direction of a rotating shaft of the gyroscope can not be changed under the condition that the rotating shaft is not influenced by external force when the gyroscope rotates at high speed. According to the principle, the gyroscope can return angular acceleration data of three axes of x, y and z, and the three-axis gyroscope can replace three single-axis gyroscopes to simultaneously determine the position, the movement track and the acceleration in 6 directions. Typical applications include photo optical anti-shake, inertial navigation of GPS, and motion sensing control games.
A gravity sensor: the realization principle is a piezoelectric effect, namely, the horizontal direction is judged by detecting the component force in two orthogonal directions of the gravity borne by a heavy object which is integrated with a piezoelectric sheet in the sensor. Many applications such as the step counting function of the sport APP and the self-adaptive rotation function of the smart phone screen are realized by using the sensor.
An acceleration sensor: also known as an accelerometer, it has a wide range of applications, and most commonly belongs to a shaking function in WeChat. The principle of the sensor is also derived from the piezoelectric effect, when the sensor and an external object do accelerated motion together, the mass block moves towards the opposite direction due to the action of inertia force, the spring and the damper influence the displacement of the mass block, and the external acceleration can be measured through the output voltage.
In the prior art, a perfect motion sensing interaction-based smart phone anti-theft and tracking method does not exist, and therefore an anti-theft and tracking method needs to be developed to solve the problems.
Disclosure of Invention
The invention aims to solve the problems, and provides a smart phone anti-theft and tracking method based on somatosensory interaction, which can reduce the ring worry of a stolen mobile phone user and effectively perform anti-theft tracking on the stolen mobile phone.
In order to realize the purpose, the invention adopts the technical scheme that: smart phone theftproof based on body is interactive, it includes the following steps: the static state anti-theft method comprises the following steps:
s1, when the mobile phone is in a standing state or a screen locking state, entering a static anti-theft mode;
s2, after detecting that the relevant data of the mobile phone gyroscope changes, sending distance confirmation information to the bracelet at intervals of 3 seconds within the next 20 seconds;
s3, after the bracelet receives the distance confirmation information from the mobile phone, the bracelet immediately returns the distance measurement information;
s4, distance measurement is carried out at the mobile phone end through the iRss value of the Bluetooth;
and S5, transmitting the distance value obtained after measurement to an early warning method.
Further, the early warning method in the step 5 of the static state anti-theft method comprises the following steps:
s1, setting an electronic fence threshold value according to the actual needs of the user, wherein the value can be changed according to the needs of the user in actual use, and testing the electronic fence threshold value;
s2, standing the mobile phone at any position without electronic interference, and connecting the mobile phone with the bracelet in a Bluetooth link mode;
s3, freely moving in the threshold range of the electronic fence, detecting whether a Bluetooth receiver, namely a bracelet, receives false alarm information from a mobile phone. If not, continuing, otherwise, returning to the step S2;
and S4, freely moving outside the threshold range of the electronic fence, and detecting whether a Bluetooth receiver, namely a bracelet, receives an alarm message from a mobile phone. If not, continuing, otherwise, returning to the step S2;
s5, processing the alarm information through the bracelet, wherein the processing option is affirmation or negation; the alarm state of the mobile phone is released by confirming the alarm message, and the system is indicated to exit until the system is restarted after the screen is locked next time; and starting a tracking mode of the mobile phone through a negative message, and performing related tracking operation according to the user bracelet.
The intelligent mobile phone anti-theft method based on somatosensory interaction is characterized by comprising the following steps of:
(1) the user holds the equipment by hand to perform natural walking movement, and freely moves for about 10 meters in any direction. According to the motion, when the mobile phone is in the swing-arm-like motion, the motion data of the mobile phone is collected to obtain the following two arrays, array T11(Δ T1, Δ T2, Δ T3 …) and array V11(Δ V1, Δ V2, Δ V3 …), and after the two arrays are obtained, the data of the same numerical index is correspondingly calculated to obtain the arrays A1x (a11, a22, a33 …), A1y (a11, a22, a33 …), A1z (a11, a22, a33 …), which respectively represent the acceleration in the front-back direction, the acceleration in the left-right direction and the acceleration in the up-down direction.
(2) The user holds the equipment to perform natural running movement, and freely runs for about 10 meters in any direction. According to the motion, when the mobile phone is in the swing-arm-like motion, motion data of the mobile phone is collected to obtain the following two arrays, namely, array T12(Δ T1, Δ T2, Δ T3 …) and array V12(Δ V1, Δ V2, Δ V3 …), and after the two arrays are obtained, corresponding calculation processing is performed on data of the same numerical subscript to obtain arrays B1x (a11, a22, a33 …), B1y (a11, a22, a33 …), and B1z (a11, a22, a33 …), which respectively represent acceleration in the front-back direction, acceleration in the left-right direction, and acceleration in the up-down direction.
(3) The user holds the equipment by hand to carry out natural jumping movement, and the equipment freely jumps up and down in the vertical direction. According to the action, when the mobile phone is doing similar movement, the movement data of the mobile phone is collected to obtain the following two arrays, array T13(Δ T1, Δ T2, Δ T3 …) and array V13(Δ V1, Δ V2, Δ V3 …), and after the two arrays are obtained, the data of the same numerical subscript is correspondingly calculated to obtain the arrays C1x (a11, a22, a33 …), C1y (a11, a22, a33 …), C1z (a11, a22, a33 …), wherein the arrays respectively represent the acceleration in the front-back direction, the acceleration in the left-right direction and the acceleration in the up-down direction.
(4) Repeating the three actions (1), (2) and (3) for three times to obtain A1N, A2N and A3N, wherein the value of N is 1,2 and 3; the obtained nine sets of arrays are processed, after the average value of each array is taken, the obtained average value is averaged again in a mode of grouping three in a synchronous step, and after that, the obtained average value is set as the initial motion state matching values, namely acceleration values Alpha1, Alpha2 and Alpha3, which respectively represent the acceleration in the front-back direction, the acceleration in the left-right direction and the acceleration in the up-down direction.
(5) The threshold of the degree of matching is set according to the actual needs of the individual users, and the threshold of the degree of matching in step 5 should be set to ninety percent or more.
(6) And (5) respectively testing the motions by the user holding the mobile phone by hands, if the actual test matching value is greater than the preset threshold value, the preset data is successful, if the actual test matching value is less than the preset threshold value, the step (5) is returned, and the matching threshold value is adjusted to ensure the normal operation of the function.
The intelligent mobile phone tracking method based on somatosensory interaction comprises the following steps:
(1) firstly, part of control functions of the mobile phone need to be realized within the controllable range of a user, for example, the mobile phone sends out an instruction through a bracelet, so that the mobile phone sends out sharp and harsh sound to prompt the user about the position of the mobile phone;
(2) secondly, after the mobile phone is separated from the controllable range of the bracelet, the function of acquiring the current condition information of the mobile phone in real time is realized, so that the mobile phone is tracked.
Further, the tracking information acquiring method includes: visual environment tracking information acquisition and localization tracking information acquisition.
Further, the visual environment tracking information acquisition comprises the following steps:
(1) the method comprises the steps that peripheral face information is obtained through a camera, the obtained information is stored in a memory controller, and video information is sent to an image processing unit frame by frame;
(2) and whether the processing result contains address information or not is judged, and the information is sent to the user equipment center.
Further, the positioning tracking information acquisition for acquiring the positioning information by the GPS positioning system includes the following steps:
(1) a built-in GPS module of the mobile phone is adopted to send positioning request information to a GPS system;
(2) adopting a built-in GPS module of the mobile phone to receive GPS position information returned by a GPS system;
(3) and transmitting the acquired GPS position information to another device preset by the user in a file form which can be opened by the current common map.
Further, the acquisition of the localization tracking information is a WLAN method, which includes the following steps:
(1) the mobile phone acquires peripheral available WIFI information through a WLAN + technology and actively sends request information to the available WIFI;
(2) the server receives the WIFI characteristic value sent by the mobile phone and records the WIFI characteristic value into a memory bank; carrying out corresponding statistical analysis on the WIFI characteristic value in a memory library;
(3) calculating the distribution position of the WIFI equipment according to the distribution characteristics;
further, the method for acquiring the positioning tracking information to be based on the WIFI positioning base station network comprises the following steps:
(1) the system collects data of a map environment in advance and summarizes the data into a memory base;
(2) dividing the summarized map environment data into N accurate small blocks;
(3) through daily geographic activities of the user, the signal intensity of each small WIFI of the environment where the user is located and the geomagnetic intensity serving as auxiliary data are obtained, and the average value of the collected data is obtained to obtain more accurate position information.
Further, the specific calculation method for acquiring the localization tracking information includes:
(1) WIFI signal intensity data S obtained through calculation1And signal strength data S in the memory bankn[N]Has a Euclidean distance d betweenn＝|S1-Sn|2And calculating the weight of each WIFI signal intensity:
(2) selecting a plurality of WIFI signal intensity data with the largest weight, and taking the specific position calculated by the WIFI signal intensity data as an initialization position;
(3) obtaining triaxial angle data of the current position of the mobile phone according to the transformation of the collected geomagnetic data; and estimating the current accurate position of the mobile phone according to the initial position and the triaxial angle data.
The invention has the beneficial effects that:
1. the invention provides a method for preventing and tracking a smart phone based on somatosensory interaction, which can reduce the withdrawal of stolen mobile phone users and effectively prevent and track the stolen mobile phone.
2. The method can obtain the specific floor information of the current position of the mobile phone, provides high tracking accuracy, and solves the problem that the specific position of the mobile phone cannot be obtained when the mobile phone enters multiple floors during tracking.
Drawings
Fig. 1 is a flowchart of the entire system for tracking a smart phone according to the present invention.
FIG. 2 is a schematic diagram of tracking information acquisition for a visual environment according to the present invention.
Detailed Description
The following detailed description of the present invention is given for the purpose of better understanding technical solutions of the present invention by those skilled in the art, and the present description is only exemplary and explanatory and should not be construed as limiting the scope of the present invention in any way.
As shown in fig. 1-2, the specific structure of the present invention is: smart phone theftproof based on body is interactive, it includes the following steps: the static state anti-theft method comprises the following steps:
s1, when the mobile phone is in a standing state or a screen locking state, entering a static anti-theft mode;
s2, after detecting that the relevant data of the mobile phone gyroscope changes, sending distance confirmation information to the bracelet at intervals of 3 seconds within the next 20 seconds;
s3, after the bracelet receives the distance confirmation information from the mobile phone, the bracelet immediately returns the distance measurement information;
s4, distance measurement is carried out at the mobile phone end through the iRss value of the Bluetooth;
and S5, transmitting the distance value obtained after measurement to an early warning method.
Further, the early warning method in the step 5 of the static state anti-theft method comprises the following steps: :
s1, setting an electronic fence threshold value according to the actual needs of the user, wherein the value can be changed according to the needs of the user in actual use, and testing the electronic fence threshold value;
s2, standing the mobile phone at any position without electronic interference, and connecting the mobile phone with the bracelet in a Bluetooth link mode;
s3, freely moving in the threshold range of the electronic fence, detecting whether a Bluetooth receiver, namely a bracelet, receives false alarm information from a mobile phone. If not, continuing, otherwise, returning to the step S2;
and S4, freely moving outside the threshold range of the electronic fence, and detecting whether a Bluetooth receiver, namely a bracelet, receives an alarm message from a mobile phone. If not, continuing, otherwise, returning to the step S2;
s5, processing the alarm information through the bracelet, wherein the processing option is affirmation or negation; the alarm state of the mobile phone is released by confirming the alarm message, and the system is indicated to exit until the system is restarted after the screen is locked next time; and starting a tracking mode of the mobile phone through a negative message, and performing related tracking operation according to the user bracelet.
A smart phone anti-theft and dynamic anti-theft method based on somatosensory interaction comprises the following steps:
(1) the user holds the equipment by hand to perform natural walking movement, and freely moves for about 10 meters in any direction. According to the motion, when the mobile phone is in the swing-arm-like motion, the motion data of the mobile phone is collected to obtain the following two arrays, array T11(Δ T1, Δ T2, Δ T3 …) and array V11(Δ V1, Δ V2, Δ V3 …), and after the two arrays are obtained, the data of the same numerical index is correspondingly calculated to obtain the arrays A1x (a11, a22, a33 …), A1y (a11, a22, a33 …), A1z (a11, a22, a33 …), which respectively represent the acceleration in the front-back direction, the acceleration in the left-right direction and the acceleration in the up-down direction.
(2) The user holds the equipment to perform natural running movement, and freely runs for about 10 meters in any direction. According to the motion, when the mobile phone is in the swing-arm-like motion, motion data of the mobile phone is collected to obtain the following two arrays, namely, array T12(Δ T1, Δ T2, Δ T3 …) and array V12(Δ V1, Δ V2, Δ V3 …), and after the two arrays are obtained, corresponding calculation processing is performed on data of the same numerical subscript to obtain arrays B1x (a11, a22, a33 …), B1y (a11, a22, a33 …), and B1z (a11, a22, a33 …), which respectively represent acceleration in the front-back direction, acceleration in the left-right direction, and acceleration in the up-down direction.
(3) The user holds the equipment by hand to carry out natural jumping movement, and the equipment freely jumps up and down in the vertical direction. According to the action, when the mobile phone is doing similar movement, the movement data of the mobile phone is collected to obtain the following two arrays, array T13(Δ T1, Δ T2, Δ T3 …) and array V13(Δ V1, Δ V2, Δ V3 …), and after the two arrays are obtained, the data of the same numerical subscript is correspondingly calculated to obtain the arrays C1x (a11, a22, a33 …), C1y (a11, a22, a33 …), C1z (a11, a22, a33 …), wherein the arrays respectively represent the acceleration in the front-back direction, the acceleration in the left-right direction and the acceleration in the up-down direction.
(4) Repeating the three actions (1), (2) and (3) for three times to obtain A1N, A2N and A3N, wherein the value of N is 1,2 and 3; the obtained nine sets of arrays are processed, after the average value of each array is taken, the obtained average value is averaged again in a mode of grouping three in a synchronous step, and after that, the obtained average value is set as the initial motion state matching values, namely acceleration values Alpha1, Alpha2 and Alpha3, which respectively represent the acceleration in the front-back direction, the acceleration in the left-right direction and the acceleration in the up-down direction.
(5) The threshold of the degree of matching is set according to the actual needs of the individual users, and the threshold of the degree of matching in step 5 should be set to ninety percent or more.
(6) And (5) respectively testing the motions by the user holding the mobile phone by hands, if the actual test matching value is greater than the preset threshold value, the preset data is successful, if the actual test matching value is less than the preset threshold value, the step (5) is returned, and the matching threshold value is adjusted to ensure the normal operation of the function.
The intelligent mobile phone tracking method based on somatosensory interaction comprises the following steps:
(1) firstly, part of control functions of the mobile phone need to be realized within the controllable range of a user, for example, the mobile phone sends out an instruction through a bracelet, so that the mobile phone sends out sharp and harsh sound to prompt the user about the position of the mobile phone;
(2) secondly, after the mobile phone is separated from the controllable range of the bracelet, the function of acquiring the current condition information of the mobile phone in real time is realized, so that the mobile phone is tracked.
Further, the tracking information acquiring method includes: visual environment tracking information acquisition and localization tracking information acquisition.
Further, the visual environment tracking information acquisition comprises the following steps:
(1) the method comprises the steps that peripheral face information is obtained through a camera, the obtained information is stored in a memory controller, and video information is sent to an image processing unit frame by frame;
(2) and whether the processing result contains address information or not is judged, and the information is sent to the user equipment center.
Further, the positioning tracking information acquisition for acquiring the positioning information by the GPS positioning system includes the following steps:
(1) a built-in GPS module of the mobile phone is adopted to send positioning request information to a GPS system;
(2) adopting a built-in GPS module of the mobile phone to receive GPS position information returned by a GPS system;
(3) and transmitting the acquired GPS position information to another device preset by the user in a file form which can be opened by the current common map.
Further, the acquisition of the localization tracking information is a WLAN method, which includes the following steps:
(1) the mobile phone acquires peripheral available WIFI information through a WLAN + technology and actively sends request information to the available WIFI;
(2) the server receives the WIFI characteristic value sent by the mobile phone and records the WIFI characteristic value into a memory bank; carrying out corresponding statistical analysis on the WIFI characteristic value in a memory library;
(3) calculating the distribution position of the WIFI equipment according to the distribution characteristics;
further, the method for acquiring the positioning tracking information to be based on the WIFI positioning base station network comprises the following steps:
(1) the system collects data of a map environment in advance and summarizes the data into a memory base;
(2) dividing the summarized map environment data into N accurate small blocks;
(3) through daily geographic activities of the user, the signal intensity of each small WIFI of the environment where the user is located and the geomagnetic intensity serving as auxiliary data are obtained, and the average value of the collected data is obtained to obtain more accurate position information.
Further, the specific calculation method for acquiring the localization tracking information includes:
(1) WIFI signal intensity data S obtained through calculation1And signal strength data S in the memory bankn[N]Has a Euclidean distance d betweenn＝|S1-Sn|2And calculating the weight of each WIFI signal intensity:
(2) selecting a plurality of WIFI signal intensity data with the largest weight, and taking the specific position calculated by the WIFI signal intensity data as an initialization position;
(3) obtaining triaxial angle data of the current position of the mobile phone according to the transformation of the collected geomagnetic data; and estimating the current accurate position of the mobile phone according to the initial position and the triaxial angle data.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
The principles and embodiments of the present invention are explained herein using specific examples, which are presented only to assist in understanding the method and its core concepts of the present invention. The foregoing is only a preferred embodiment of the present invention, and it should be noted that there are objectively infinite specific structures due to the limited character expressions, and it will be apparent to those skilled in the art that a plurality of modifications, decorations or changes may be made without departing from the principle of the present invention, and the technical features described above may be combined in a suitable manner; such modifications, variations, combinations, or adaptations of the invention using its spirit and scope, as defined by the claims, may be directed to other uses and embodiments.
Claims (10)
1. Smart phone theftproof based on body is interactive, its characterized in that, it includes following step:
the static state anti-theft method comprises the following steps:
s1, when the mobile phone is in a standing state or a screen locking state, entering a static anti-theft mode;
s2, after detecting that the relevant data of the mobile phone gyroscope changes, sending distance confirmation information to the bracelet at intervals of 3 seconds within the next 20 seconds;
s3, after the bracelet receives the distance confirmation information from the mobile phone, the bracelet immediately returns the distance measurement information;
s4, distance measurement is carried out at the mobile phone end through the iRss value of the Bluetooth;
and S5, transmitting the distance value obtained after measurement to an early warning method.
2. The smartphone anti-theft method based on somatosensory interaction according to claim 1, wherein the early warning method in step 5 in the static state anti-theft method comprises the following steps: :
s1, setting an electronic fence threshold value according to the actual needs of the user, wherein the value can be changed according to the needs of the user in actual use, and testing the electronic fence threshold value;
s2, standing the mobile phone at any position without electronic interference, and connecting the mobile phone with the bracelet in a Bluetooth link mode;
s3, freely moving in the threshold range of the electronic fence, detecting whether a Bluetooth receiver, namely a bracelet, receives false alarm information from a mobile phone. If not, continuing, otherwise, returning to the step S2;
and S4, freely moving outside the threshold range of the electronic fence, and detecting whether a Bluetooth receiver, namely a bracelet, receives an alarm message from a mobile phone. If not, continuing, otherwise, returning to the step S2;
s5, processing the alarm information through the bracelet, wherein the processing option is affirmation or negation; the alarm state of the mobile phone is released by confirming the alarm message, and the system is indicated to exit until the system is restarted after the screen is locked next time; and starting a tracking mode of the mobile phone through a negative message, and performing related tracking operation according to the user bracelet.
3. The smartphone antitheft based on somatosensory interaction of claim 1, wherein the dynamic antitheft method comprises the following steps:
the user holds the equipment by hand to perform natural walking movement, and freely moves for about 10 meters in any direction. According to the motion, when the mobile phone is in the swing-arm-like motion, the motion data of the mobile phone is collected to obtain the following two arrays, array T11(Δ T1, Δ T2, Δ T3 …) and array V11(Δ V1, Δ V2, Δ V3 …), and after the two arrays are obtained, the data of the same numerical index is correspondingly calculated to obtain the arrays A1x (a11, a22, a33 …), A1y (a11, a22, a33 …), A1z (a11, a22, a33 …), which respectively represent the acceleration in the front-back direction, the acceleration in the left-right direction and the acceleration in the up-down direction.
(2) The user holds the equipment to perform natural running movement, and freely runs for about 10 meters in any direction. According to the motion, when the mobile phone is in the swing-arm-like motion, motion data of the mobile phone is collected to obtain the following two arrays, namely, array T12(Δ T1, Δ T2, Δ T3 …) and array V12(Δ V1, Δ V2, Δ V3 …), and after the two arrays are obtained, corresponding calculation processing is performed on data of the same numerical subscript to obtain arrays B1x (a11, a22, a33 …), B1y (a11, a22, a33 …), and B1z (a11, a22, a33 …), which respectively represent acceleration in the front-back direction, acceleration in the left-right direction, and acceleration in the up-down direction.
(3) The user holds the equipment by hand to carry out natural jumping movement, and the equipment freely jumps up and down in the vertical direction. According to the action, when the mobile phone is doing similar movement, the movement data of the mobile phone is collected to obtain the following two arrays, array T13(Δ T1, Δ T2, Δ T3 …) and array V13(Δ V1, Δ V2, Δ V3 …), and after the two arrays are obtained, the data of the same numerical subscript is correspondingly calculated to obtain the arrays C1x (a11, a22, a33 …), C1y (a11, a22, a33 …), C1z (a11, a22, a33 …), wherein the arrays respectively represent the acceleration in the front-back direction, the acceleration in the left-right direction and the acceleration in the up-down direction.
(4) Repeating the three actions (1), (2) and (3) for three times to obtain A1N, A2N and A3N, wherein the value of N is 1,2 and 3; the obtained nine sets of arrays are processed, after the average value of each array is taken, the obtained average value is averaged again in a mode of grouping three in a synchronous step, and after that, the obtained average value is set as the initial motion state matching values, namely acceleration values Alpha1, Alpha2 and Alpha3, which respectively represent the acceleration in the front-back direction, the acceleration in the left-right direction and the acceleration in the up-down direction.
(5) The threshold of the degree of matching is set according to the actual needs of the individual users, and the threshold of the degree of matching in step 5 should be set to ninety percent or more.
(6) And (5) respectively testing the motions by the user holding the mobile phone by hands, if the actual test matching value is greater than the preset threshold value, the preset data is successful, if the actual test matching value is less than the preset threshold value, the step (5) is returned, and the matching threshold value is adjusted to ensure the normal operation of the function.
4. Smart phone tracking based on somatosensory interaction is characterized by comprising the following steps:
(1) firstly, part of control functions of the mobile phone need to be realized within the controllable range of a user, for example, the mobile phone sends out an instruction through a bracelet, so that the mobile phone sends out sharp and harsh sound to prompt the user about the position of the mobile phone;
(2) secondly, after the mobile phone is separated from the controllable range of the bracelet, the function of acquiring the current condition information of the mobile phone in real time is realized, so that the mobile phone is tracked.
5. The smartphone tracking based on somatosensory interaction according to claim 4, wherein the tracking information obtaining method comprises: visual environment tracking information acquisition and localization tracking information acquisition.
6. The somatosensory interaction-based smartphone tracking according to claim 4, wherein visual environment tracking information acquisition comprises the steps of:
(1) the method comprises the steps that peripheral face information is obtained through a camera, the obtained information is stored in a memory controller, and video information is sent to an image processing unit frame by frame;
(2) and whether the processing result contains address information or not is judged, and the information is sent to the user equipment center.
7. The motion-sensing interaction based tracking of smart phones of claim 6, wherein the location tracking information acquisition is a GPS location system to acquire location information, comprising the steps of:
(1) a built-in GPS module of the mobile phone is adopted to send positioning request information to a GPS system;
(2) adopting a built-in GPS module of the mobile phone to receive GPS position information returned by a GPS system;
(3) and transmitting the acquired GPS position information to another device preset by the user in a file form which can be opened by the current common map.
8. The motion-sensing interaction based smart phone tracking method according to claim 6, wherein the location tracking information is obtained as a WLAN method, comprising the steps of:
(1) the mobile phone acquires peripheral available WIFI information through a WLAN + technology and actively sends request information to the available WIFI;
(2) the server receives the WIFI characteristic value sent by the mobile phone and records the WIFI characteristic value into a memory bank; carrying out corresponding statistical analysis on the WIFI characteristic value in a memory library;
(3) calculating the distribution position of the WIFI equipment according to the distribution characteristics;
9. the somatosensory interaction-based smartphone tracking according to claim 6, wherein the method for acquiring the positioning tracking information as a WIFI-based positioning base station network comprises the following steps:
(1) the system collects data of a map environment in advance and summarizes the data into a memory base;
(2) dividing the summarized map environment data into N accurate small blocks;
(3) through daily geographic activities of the user, the signal intensity of each small WIFI of the environment where the user is located and the geomagnetic intensity serving as auxiliary data are obtained, and the average value of the collected data is obtained to obtain more accurate position information.
10. The smartphone tracking based on somatosensory interaction according to claim 6, wherein the specific calculation method for acquiring the localization tracking information comprises:
(1) WIFI signal intensity data S obtained through calculation1And signal strength data S in the memory bankn[N]Has a Euclidean distance d betweenn＝|S1-Sn|2And calculating the weight of each WIFI signal intensity:
(2) selecting a plurality of WIFI signal intensity data with the largest weight, and taking the specific position calculated by the WIFI signal intensity data as an initialization position;
(3) obtaining the triaxial angle data of the current position of the mobile phone according to the transformation of the collected geomagnetic data
(4) And estimating the current accurate position of the mobile phone according to the initial position and the triaxial angle data.
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