JP5095809B2 - Portable terminal device and control method thereof - Google Patents

Description

  The present invention relates to a mobile terminal device and a control method thereof, and in particular, walking navigation information according to an object (shoe, clothes, bag, etc.) worn or carried by a user when the user carrying the mobile terminal device walks. It relates to the technique of presenting.

  Conventionally, a car navigation system for displaying and guiding a route in an automobile or the like is often used. In the car navigation system, when a destination is input, a route is searched, and not only the route but also the required time to the destination in consideration of road conditions is notified to the user. Outside the automobile field, there are systems for mobile communication terminals that inform pedestrians of the route to the destination, the current position, and the required time. Further, a technique for acquiring a standard walking speed of a pedestrian and notifying the user of how much it needs to hurry if it is determined that the walking speed is not in time for the desired arrival time (see Patent Documents 1 and 2). Is also disclosed.

Japanese Patent Laid-Open No. 10-293038 JP2003-244767

  The time required to reach a pedestrian's destination varies due to factors that are completely different from those of a car. One of them is footwear worn by pedestrians. Depending on the type and shape of footwear and the frequency of wearing, the ease of walking, and therefore both the standard speed and the maximum speed may vary greatly. In addition to footwear, when carrying a large or heavy bag, kimono and yukata, which are representative of kimonos, greatly affect walking speed and ease of walking. Also, the user's walking speed changes due to weather such as rain and wind, and injuries such as shoe rubbing, and cannot be handled with uniform navigation. Setting a uniform maximum speed without taking into account the above factors may require the user to walk or run at an unreasonable speed, increasing the risk of falling or crashing, or conversely. You will make the wrong decision that you are not in time. Moreover, there are many cases where it is not useful to predict the arrival time without considering such factors that affect the walking speed of the user.

  By the way, in recent years, an RFID tag that enables a product tag to be read without contact has been developed, and the price of the RFID tag is being reduced. The RFID tag is given a unique ID for each product, and it is possible to know what the product is. However, most of them are for merchandise sales / POS or logistics merchandise management, and no technique has been developed to apply this to walking navigation.

In order to solve the above-described problems, the mobile terminal device according to the first invention
Position acquisition means (GPS function etc.) for acquiring (positioning) the current position of the mobile terminal device;
Destination setting means for setting the destination;
Proximity object identification means (RFID reader or the like) for identifying an object in proximity to the mobile terminal device (that is, clothes worn by the user, footwear, bags, etc.)
Calculating means for calculating an expected speed based on the object identified by the proximity object identifying means;
Expected rate based on those currently being identified, before Kigen standing position, and, walking navigation information generated based on prior Symbol their destinations (e.g., predicted arrival time to the destination, anticipated moving speed, the walking speed increases or decreases Notification means (vibrator, display, speaker, etc.) for notifying instructions (display, speaker, etc.);
It is characterized by providing.

As described above, the solution of the present invention has been described as an apparatus. However, the present invention can be realized as a method, a program, and a storage medium storing the program, which are substantially equivalent thereto, and the scope of the present invention. It should be understood that these are also included.
For example, a control method for a mobile terminal device according to the second invention that implements the present invention as a method is as follows:
A position acquisition step of acquiring (positioning) the current position of the mobile terminal device using positioning means (GPS function);
A destination setting step for setting a destination;
A proximity object identifying step for identifying an object in proximity to the mobile terminal device using a proximity object identifying means;
Expected rate based on those currently being identified, before Kigen standing position, and, walking navigation information generated based on prior Symbol their destinations (e.g., predicted arrival time to the destination, anticipated moving speed, the walking speed increases or decreases A notification step of notifying an instruction or a walking route suitable for the user having the identified object (by a display, a speaker, etc.);
It is characterized by including.

  According to the present invention, the user's items (footwear, clothes, bags, etc.) carrying the terminal are automatically identified by the proximity object identifying means, and the walking navigation information considering the influence on the walking by the objects is easy. Can be provided. In the present invention, it is possible to automatically identify and judge an object worn by the user, and provide walking navigation information according to the user's situation at that time. Therefore, the user can obtain walking navigation information according to the individual user's footwear, clothes, and carrying items, which is much more accurate than before, by a simple operation of setting the destination.

It is a block diagram which shows the basic composition of the portable terminal device by this invention. It is a block diagram of the portable terminal (cellular phone terminal) to which the present invention is applied. It is a detailed block diagram of the movement condition setting means 13 shown in FIG. It is a figure which shows an example of the data format of the route information used with this terminal. It is a detailed block diagram of the walking guide means 10 shown in FIG. It is a flowchart explaining an example of the walk navigation (guide) process performed with this terminal. It is a timing chart which shows an example of the walking rhythm which this terminal alert | reports to a user. It is a figure which shows the screen interface which this terminal presents to a user as walking navigation information. FIG. 3 is a detailed block diagram of maximum walking speed estimation means 20 shown in FIG. 2. FIG. 10 is a detailed block diagram of the maximum object walking speed memory estimating means 37 shown in FIG. 9. It is a figure which shows the shape of seven types of shoes. It is a figure which shows the example of a shape of shoes. It is a figure explaining the fixing method of shoes and a leg. It is a figure explaining the fixing method shown in FIG. 13 with the shape of shoes. 3 is a three-dimensional map of a shoe fixing method, a heel height, and a heel thickness. It is a default three-dimensional map of a shoe fixing method, a heel height, and a heel thickness. It is a figure which shows 3 points | pieces for investigating how much it changes with each item, and speed changes 1km / h. It is a figure which shows the method of investigating how much it changes with each item, and speed changes 1km / h. It is a graph showing the magnitude | size of the change of the speed by the change in any of 3 items. FIG. 3 is a detailed block diagram of standard walking speed estimation means 26 shown in FIG. 2. It is an example of distribution of the data of a walk interval. It is a figure showing the example of the actual walking speed in a walking guide, and required walking speed (walking navigation information). It is a figure showing the example of the speed and distance when going to the destination of 6 km in 1 hour. It is a flowchart which shows the flow of the process for correcting the memory | storage of an object and matching estimation with a user. It is a figure showing how update of a record and correction of a default value are performed. It is a figure showing three axes memorized in addition to information on speed and shoes.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.
<Example 1>
FIG. 1 is a block diagram showing a basic configuration of a mobile terminal device according to the present invention. As shown in the figure, the portable terminal device 1 according to the present invention includes a position acquisition means (GPS function) 2, a route determination means 3, a proximity object identification means (RFID reader) 4, a storage means 5, a notification means 6, and a customization. Means 7 are provided. The position acquisition means 2 measures the current position of the mobile terminal device carried by the user and displays the current position on a display (not shown). The user selects a destination on the display, and the route determination means 3 determines an optimal walking route from the current position to the destination, and thereby a required distance to the destination is determined. The proximity object identification means 4 reads the RFID tag attached to the object located in the proximity area AR (that is, the tag readable area) as viewed from the own terminal (that is, the user) in a non-contact / wireless manner. The proximity area AR depends on the performance of the RFID reader or RFID tag (transponder) and its usage standard, but it is possible to use one with a radius of about 1 m from the RFID reader or one with a radius of about 2 m. It is suitable for avoiding misrecognition between the property and the property of others. In this case, a radius 2 m from the terminal device 1 accommodated in the user's breast pocket is the proximity area AR.

  In this embodiment, the RFID tag ID1 of the shoe A as the footwear, the RFID tag ID2 of the jeans B as the clothing, and the RFID tag ID3 of the carry bag C as the carried item are identified as nearby items, that is, the proximity items. In addition to the items worn by the user and items carried by the user, items that are not detected continuously, or those that are detected for a short period of time, for example, are determined to be someone else's items. In other words, only the objects close to the user are identified in advance in a state where there are no objects / persons other than the user in the vicinity, and the operations are limited to those identified at that time.

  The notification means 6 searches the object-specific walking influence table 5A stored in the storage means 5 using the tags ID1, ID2, and ID3 of the identified nearby objects as search keys, and reads the corresponding walking influence information. In this example, it can be seen from the tag ID1 that the object is the shoe A, and the walking influence information indicating that the walking ease (that is, the walking speed) is reduced by 20% when the shoe A is worn is obtained. Similarly, when wearing the jeans B, walking influence information indicating that walking ease (walking speed) is increased by 10% is obtained, and when carrying the carry bag C, walking ease ( Walking influence information indicating that walking speed is reduced by 40% is obtained. The notifying means 6 calculates the expected walking speed, expected arrival time, etc. of the user who uses the identified object, using the following formula and calculating means, and notifies these to the user as walking navigation information. Alternatively, a calculation means for calculating the walking navigation information may be provided separately from the notification means.

Expected walking speed = user standard walking speed × (1− (effect 0.2 of shoe A) + effect 0.1 of blue jeans B− (effect 0.4 of carry bag C))
= User standard walking speed x 0.5
Expected arrival time = current time + expected required time = current time + set route distance / expected walking speed In this way, in the situation of FIG. 1, it is estimated that the walking speed is 50% of the normal walking speed of the user, It is automatically calculated that it takes twice as long as usual, and walking navigation information based on this is provided to the user.

Each RFID tag stores a unique ID (generally a unique product code) for each product. If the unique ID can be read, the RFID tag is constructed in advance in a built-in unique ID database (or in a server on the Internet). By referring to the product code database, it is possible to know almost completely the attributes of the product. For example, when the unique ID accommodated in the RFID tag is a JAN code, a unique ID database as shown in the table below is used. In the case of a JAN code, the code itself stores the code that specifies the country name, manufacturer name, and product name, but adds classification, shape information, weight information, walking influence information, etc., which are attribute information of the object Since the information is information that is not included in the JAN code, it is necessary to include these additional information in the spare field of the RFID tag or to prepare and set a database including the additional information in advance.

  In the present invention, it is not always necessary to know the manufacturer, product name, attribute, and walking influence information of the identified item. Since the terminal according to the present invention has a customization function for learning the influence on walking when the object is held, the object is distinguished from each other, the walking influence information is measured for each object, and those objects are measured. It is possible to construct a walking effect table for each object that is specific to the user who uses, so that even if it does not obtain the attribute of the object (for example, sneaker X of Company A) or the walking effect information, Adapted walking navigation information can be provided.

  As will be described in detail later, for example, the type of footwear, the type of heel, the capacity of the heel, the weight of the carried item, etc. are factors that greatly affect the walking speed. If you can refer to the unique ID database (or the product code database on the Internet) that defines the detailed attributes of the product (or set flags that specify items that affect walking, such as the type, volume, and weight of items) RFID itself may have.) From the read unique ID, it is possible to know the attributes of the item, that is, the type of footwear, the capacity of the heel, and the weight of the carried item. Therefore, without using the customization function, for example, in the case of footwear, a walking influence table for each footwear that takes into account the type and shape of the footwear is constructed in advance, and by referring to this table, It is possible to provide walking navigation information in consideration of footwear.

  Further, various objects affect the walking speed of the user, and the user carrying the terminal usually wears or carries a plurality of objects that affect the walking speed. For example, as shown in FIG. 1, shoes A, jeans B, carry bags C, and the like. In FIG. 1, comprehensive walking influence information is calculated from a plurality of objects with a simple formula, and an estimated walking speed corresponding to the situation is calculated. A walking influence information table in a three-dimensional map format as shown in FIG. It can also be constructed and derived from such a map (which will be described in detail later).

<Example 2>
An embodiment in which the present invention is applied to a most popular mobile phone as a mobile terminal device will be described. FIG. 2 is a block diagram of a mobile terminal (mobile phone terminal) to which the present invention is applied. As shown in the figure, the portable terminal 44 according to the present invention includes a position acquisition unit 15 that acquires the current position, a time acquisition unit 14 that acquires the current time, a destination that the user 16 wants to move, and a route to the destination. , And movement condition setting means 13 for setting movement conditions such as desired arrival time, the current position acquired by the position acquisition means 15, the current time acquired by the time acquisition means 14, and the movement set by the movement condition setting means 13 Based on the conditions, the necessary walking speed determining means 12 for determining an appropriate walking speed for arriving at the destination by the desired arrival time, and the necessary walking speed for the user 16 based on the necessary walking speed determining means 12 are determined. A walking guide means 10 for notifying and a maximum walking speed estimating means 20 for estimating the maximum walking speed of the current user 16 are provided.

  The mobile terminal 44 further determines whether or not the movement condition can be achieved by comparing the maximum walking speed based on the maximum walking speed estimation means 20 and the required walking speed based on the required walking speed determination means 12. An achievement determination means 19, a walking speed acquisition means 28 for acquiring the walking speed of the user 16, a weather information acquisition means 21 for acquiring weather information, and a walking interval acquisition means 24 for acquiring the walking interval of the user 16 are provided.

  The portable terminal 44 is further acquired by the first walking abnormality determination means 23 and the walking speed acquisition means 28 for determining whether or not there is an abnormality in the walking of the user 16 based on the walking interval acquired by the walking interval acquisition means 24. The standard walking speed estimation means 26 for estimating the standard walking speed of the user 16 based on the past walking speed, the current walking speed acquired by the walking speed acquisition means 28, and the standard walking estimated by the standard walking speed estimation means 26 The second gait abnormality determination means 25 that determines whether there is an abnormality in walking of the user 16 by comparing with the speed, and information on shoes, clothes, or carrying items (such as bags) that the user 16 is currently wearing Object information acquisition means (proximity object acquisition means, RFID reader) 27 and communication means 22 for communicating with the outside (server on the Internet).

  The required walking speed determining means 12 is the current position acquired by the position acquiring means 15 and the current time acquired by the time acquiring means 14 according to the moving conditions set by the moving condition setting means 13 until the desired arrival time at the destination. Calculate the speed required to arrive.

  The first gait abnormality determination unit 23 stores the walking interval obtained by the walking interval acquisition unit 24, and statistically calculates a value acquired at a high frequency in the obtained walking interval. When the user is carrying this terminal, he always takes statistics of the walking interval data and stores how the normal data is distributed. As a result of examining the statistics of the data in the walking interval or speed, if the data distribution is clearly different from the normal data distribution, it is determined that the user 16 has an abnormality in walking, and the walking speed estimation means 20 is notified.

  The second walking abnormality determination means 25 compares the standard walking speed obtained by the standard walking speed estimation means 26 with the walking speed obtained by the walking speed acquisition means 28, and the standard value of the walking speed within a certain time is the standard walking speed. If it is lower than a certain level, it is determined that there is an abnormality in the walking of the user 16, and the maximum walking speed estimation means 20 is notified.

<Movement condition setting means>
FIG. 3 is a detailed block diagram of the movement condition setting means 13 shown in FIG. As shown in the figure, the movement condition setting means 13 is obtained by the alarm means 31 that sounds an alarm at the alarm time set by the user 16, the position information obtained by the alarm time and the position acquisition means 15, and the time acquisition means 14. The route estimation means 29 for estimating the destination and the route to be reached and the time at which the destination is desired to be arrived based on the time to be received, and confirming with the user 16 whether the route estimated by the route estimation means 29 is acceptable. When the estimated route is not approved, the route registration means 30 is configured to accept a change operation from the user 16 and determine the route.

  The route estimation means 29 always stores a combination of position information and time. Of the stored location information and time, the current location of the alarm time is used as a departure point, and the alarm time is used as a reference to take out a series of places that frequently walk in the same direction. A place where walking ends, such as a place that does not move for a certain period of time or a transportation stop, is set as a destination, and a series of places from the starting point to the destination is set as a route. Based on the speed and the time required to reach the destination, the distance to the destination at several points in the route is also calculated. If the time passing through each point is close each time, the standard time (estimated time of arrival) at the last place (destination) of the route is also taken out.

  The route registration unit 30 displays the route estimated by the route estimation unit 29 and the time of the destination, and allows the user 16 to confirm and register. Further, the route is displayed to the user 16, and the selected route and the time at the destination are registered.

  FIG. 4 is a diagram illustrating an example of a data format of route information used in the terminal. The route information estimated by the route estimation unit 29 and registered by the route registration unit 30 includes, as shown in the figure, “location information of destination and name (if any)”, Location information, name (if any), desired arrival time, distance from departure location to destination, and location information (latitude and longitude) at several points in the route "Distance to destination" and "Road conditions such as traffic lights and stairs". The above one block of route information is transferred from the movement condition setting means 13 to the necessary walking speed determination means 12 as a movement condition.

<Walking guide means>
FIG. 5 is a detailed block diagram of the walking guide means 10 shown in FIG. As shown in the figure, the walking guide means 10 includes a necessary walking interval calculating means 32 for calculating a walking interval necessary for walking at the required walking speed obtained by the required walking speed determining means 12, and a necessary walking speed for the user 16. Based on the determination result of the notification determination means 34 and the notification determination means 34 for determining the content to be notified and the start and end of the notification, the required walking interval obtained by the required walking interval calculation means 32, or determined not to be in time The notification means 33 is configured to transmit the fact to the user 16 by vibration, sound or display.

  The required walking interval calculation means 32 calculates the current stride based on the current walking interval obtained by the walking interval acquisition means 24 and the walking speed obtained by the walking speed acquisition means 28, and sends it to the necessary walking speed determination means 12. The necessary walking speed obtained in this way is divided by the step length, and the walking interval necessary for walking at the necessary walking speed with the current step length is calculated.

  The notification determination means 34 compares the current walking speed obtained by the walking speed acquisition means 28 with the required walking speed obtained by the required walking speed determination means 12, and when the required walking speed exceeds the current walking speed, the notification means 33 Is instructed to notify the necessary speed. The notification determination unit 34 further includes the standard walking speed obtained by the standard walking speed estimation unit 26 and the necessary walking obtained by the necessary walking speed determination unit 12 in a state where the notification unit 33 reports the necessary walking speed. The speeds are compared, and if the standard walking speed exceeds the required walking speed, the notification means 33 is instructed to stop the notification of the required speed.

  The notification determining means 34 further determines that the user 16 has stopped walking due to the walking speed obtained by the walking speed acquisition means 28, and the standard walking speed obtained by the standard walking speed estimation means 26, The required walking speed obtained by the required walking speed determining means 12 is compared, and when the required walking speed exceeds the standard walking speed, the notification means 33 is instructed to notify the required speed. Further, the notification determination unit 34 instructs the user 16 to notify the notification unit 33 that it has determined that the movement condition cannot be achieved by the movement condition achievement determination unit 19.

  FIG. 6 is a flowchart for explaining an example of walking navigation (guide) processing performed in the terminal. Start walking guide processing one hour before the alarm time. As shown in the figure, when an alarm sounds in the alarm setting (steps s1 and s2), information on the current location is acquired at regular intervals and it is checked whether the departure location has been exited (step s3). If it is known that the vehicle has left the departure place, the RFID information and weather information of the proximity object are acquired (steps s4 and s7). Based on RFID information, the attributes (type, shape, etc.) of the object are specified. For example, if the object is a shoe, the standard walking speed is estimated based on information on the type and shape of the shoe (step s6), and the current position is acquired at regular time intervals (step s8). If the acquired current position is the destination, the walking guide is terminated (steps s9, s10). If it has not arrived at the destination, the current walking speed is obtained, the speed required to arrive at the destination at the desired arrival time is calculated, whether there is an abnormality in walking, and the maximum walking speed is estimated. (Steps s11, s12, s13, s14).

  Compare the current walking speed with the required walking speed and the maximum walking speed. If the current speed is not enough, but if you are in a hurry, that is, if the required speed is slower than the estimated maximum walking speed, it is necessary. The rhythm of the walking interval at a high speed is transmitted to the user 16 (FIGS. 7A and 7B), and the remaining time until the estimated arrival time is displayed on the screen (FIG. 8A, steps s15, s16, and s17). . If it is not in time even in a hurry, a rhythm that cannot adjust the walking interval is transmitted to the user 16 (FIG. 7 (c), steps s16 and s19).

  FIG. 7 is a timing chart illustrating an example of a walking rhythm that the terminal notifies the user. As shown in the figure, FIG. 7 (a) shows a rhythm of vibration or sound when transmitting a walking sensation at a relatively low speed, and FIG. 7 (b) shows a rhythm when transmitting a walking interval at a relatively high speed. FIG. 7 (c) shows an example of a rhythm transmitted when it is determined that it is not in time. A rhythm representing a walking interval (interval of one step) is transmitted to the user 16 by vibration or sound. Represents the time interval (walking interval) obtained by dividing the current required speed by the current stride obtained by the walking speed acquisition means 28, and walking at the required stride while walking the stride as it is can walk at the required speed and arrive It is possible to arrive at the destination at the desired time. Since (a) vibrates at a relatively long interval or makes a sound, it walks at a relatively slow speed when walking according to the vibration and sound of (a) without changing the stride. In addition, the interval of (b) is short, and it becomes faster to walk according to the vibration and sound of (b) without changing the stride. In this way, it is possible to convey the speed more accurately by telling what walking interval should be used while keeping the stride as it is. By enabling walking at an optimal speed without looking at the screen of the mobile terminal, a more optimal walking guide is possible. When it is estimated that even if it runs at the maximum walking speed, it will not be in time for the desired arrival time, it informs the user 16 of a rhythm that cannot be walked together. (c) Tells the user 16 that he / she cannot walk in step by step with the vibration / sound because the vibration / sound for a long time is combined with the sound for a short time. Is possible.

  FIG. 8 is a diagram showing a screen interface that the terminal presents to the user as walking navigation information. As shown in the figure, FIG. 8A is an example of a display screen when the walking guide is in time and the current speed is not in time and a higher speed is transmitted to the user 16. Tamagawa Station is the destination, 7:20 is set as the desired arrival time, and the remaining time and urgent need to be displayed. FIG. 8B is an example of a display screen when it is determined that it is not in time for the desired arrival time (moving conditions cannot be achieved), and displays that it is not in time. The user 16 can know the speed necessary to make it in time and the fact that it is not in time by vibrations and sounds without looking at the display screen, but cannot know the time. Time information such as the remaining time until the desired arrival time can be confirmed by displaying it on the screen.

<Maximum walking speed estimation means>
FIG. 9 is a detailed block diagram of the maximum walking speed estimation means 20 shown in FIG. As shown in the figure, the maximum walking speed estimation means 20 includes a weather influence speed estimation means 36 that estimates the maximum walking speed in consideration of the influence of the weather based on weather information obtained from the outside by communication means, and object information Based on (for example, shoes), the maximum object walking speed memory estimation means 37 for estimating the maximum walking speed in consideration of the influence of the object on walking, the weather influence speed obtained by the weather influence speed estimation means 36, and the object maximum It is composed of total maximum walking speed estimation means 35 that estimates the maximum walking speed based on the maximum object walking speed obtained by the walking speed memory estimation means 37.

  The weather influence speed estimation means 36 stores the combination of the weather information and the walking speed, and estimates the weather influence speed based on the storage and the weather information at the time of estimation. In the weather information, the three items of “rainfall, wind speed, and temperature” are each divided by a certain value, and the average of the maximum walking speed at that value is calculated. Multiply the value in the difference between the average maximum walking speed and the highest average maximum walking speed in the current weather information range to obtain the speed that affects the estimated maximum walking speed due to the weather.

  The overall maximum walking speed estimation means 35 is obtained by multiplying the weather influence speed obtained by the weather influence speed estimation means 36 by a certain number and subtracting it from the maximum walking speed of the object (shoes) obtained by the object maximum walking speed memory estimation means 37. Is the maximum walking speed. Further, when the first walking abnormality determining means 23 or the second walking abnormality determining means 25 determines that there is an abnormality in the walking of the user 16, the estimated maximum walking speed is decreased by a predetermined ratio. .

<Maximum walking speed memory estimation means>
FIG. 10 is a detailed block diagram of the object maximum walking speed memory estimating means 37 shown in FIG. As shown in the figure, the object maximum walking speed memory estimating means 37 is worn by the user 16 and the object maximum walking speed memory means 39 for storing the ID, type, shape and maximum walking speed of the object (typically shoes). A maximum object walking speed estimating means 38 for estimating the maximum walking speed of the object being carried, and a maximum object walking speed memory correcting means 40 for correcting the memory content of the object maximum walking speed storage means 39 to suit the user 16; Consists of

  The maximum walking speed of the user 16 and the ID, type, shape, and the like of an object (typically shoes) being worn and carried are stored in the maximum object walking speed storage means 39. Based on the previous stored contents of the maximum object walking speed storage means 39, the maximum walking speed of the object currently worn and carried by the user 16 is estimated. For previously worn / carrying items, such as shoes, the previously stored maximum walking speed is used.

  Hereinafter, in the present specification, the present invention will be described by exemplifying shoes (footwear) as one of representatives of “things” that affect walking (especially walking speed). In the case of a shoe worn for the first time, the maximum walking speed is estimated based on the memory contents of other shoes worn before. In the initial state, even if there is no memory of the shoe information and the maximum walking speed, the default value is the general relationship between the type of shoe, shape and speed in order to estimate the maximum walking speed of the first shoe to wear. It is put in the maximum walking speed storage means 39 (FIG. 16). Since the default value differs from the relationship between the user's 16 individual shoe information and the maximum walking speed, the default value is changed by the customization function based on the error between the estimated maximum walking speed and the actual maximum walking speed ( Customized) to make it possible to estimate the maximum walking speed of the object (shoes) that suits the user 16 more.

  The article maximum walking speed storage means 39 stores the shoe ID, type, shape, and maximum walking speed. The type and shape of the shoe are stored as the type of shoe (any one of FIGS. 11 (a) to (g)), the height of the heel (FIG. 12 (a)), the thickness of the heel (FIG. 12). (b) There are four fixing methods (Figs. 13 and 14.) The types of shoes are classified into seven types (Fig. 11): sneakers, sandals, mules, pumps, boots, petan shoes, and kettles. For example, 1 is the most difficult to walk and 7 is the most comfortable to walk, the heel height is 0cm to 10cm, and the heel thickness is 1cm to 5cm. There are six methods for fixing the toe and foot: "Is there a heel?", "If there is no heel, is there a belt behind?" And "Is there something that fixes the instep?" 14), the general order of ease of walking is set, for example, 1 is the most difficult to walk and 6 is the easiest to walk.

  The shoe type and shape are replaced with the numerical values in the four items as described above, and stored in combination with the shoe ID and the maximum walking speed for each shoe of the actual user 16 obtained by the walking speed acquisition means 28. The above storage contents are stored separately for each type of shoe. If the acquired maximum walking speed changes, the stored content is updated. However, when the first walking abnormality determining means 23 or the second walking abnormality determining means 25 determines that the walking of the user 16 is abnormal, it is not updated to the acquired maximum walking speed. Also, even if the shoe shape and type are the same, if the ID is different, it is not updated and stored separately. Since there is no actual stored numerical value in the initial state, the relationship between the general shoe type and shape and the maximum walking speed is stored as a default value. The ID is the default value. The default value is to change each item at a constant interval and make it uniformly exist in the entire range (FIG. 16).

  The maximum object walking speed estimation means 38 estimates the speed of the shoe based on the storage of the type and shape of the shoe and the ID. The information on the type, shape and ID of the shoe is extracted from the RFID information of the shoe. In the previous memory stored by the maximum object walking speed storage means 39, it is checked whether there is information on shoes with the same ID, and if present, the previous maximum walking speed of the shoes with the same ID is estimated. The maximum walking speed of shoes. Also, if there is no memory of the same ID and memory of the same shape and type, the maximum walking speed of the estimated shoe is reduced by reducing the maximum walking speed of the same shape and type of shoes at a certain rate. Speed. If there is no memory of the same ID and the same shape and type in the previous memory, 8 memories are taken as samples from the memory contents of other shoes and the memory contents that are included by default, and inferred based on the 8 samples I do.

The memory used for estimation as the sample is a memory of the same shoe type, and in three items of heel height, heel thickness, and fixing method,
・ All three items are the closest in the memory that is easier to walk than the guessed shoe ・ All three items are the closest in the memory that is harder to walk than the guessed shoe ・ Only the heel height of the three items is walking The closest one of the difficult memories ・ Of the three items, the closest one of the memories that only the thickness of the heel is difficult to walk ・ Of the three items, the closest one of the memories that are difficult to walk only the fixing method ・ The three items Of the three items, only the heel height and the heel thickness are the closest to the memory that is difficult to walk.Of the three items, the heel thickness and the fixing method are the closest to the memory that is difficult to walk. Eight of the closest memories that are difficult to walk with only the heel height (Fig. 15).

In order to examine the closeness of the shoes that estimate the maximum walking speed (the shoes to be estimated) and the eight samples above, the maximum change in the three items of heel height, heel thickness, and fixing method Normalize the walking speed by 1km / h and calculate the distance between the two points. The calculation of the maximum walking speed of the shoes to be estimated is divided by dividing the maximum walking speed of the sample by the distance between the sample and the shoes to be estimated, respectively, and totaling them. Multiply the total number by the sample distance, divide by the total sample distance, and use the calculation result as the maximum walking speed of the guessed shoe.
Distance to sample 1 object: l1 Speed: v1
Distance to sample 2 target: l2 Speed: v2
Distance to sample 3 target: l3 Speed: v3
Distance to sample 4 target: l4 Speed: v4
Distance to sample 5 target: l5 Speed: v5
Distance to sample 6 object: l6 Speed: v6
Distance to sample 7 target: l7 Speed: v7
Distance to sample 8 target: l8 Speed: v8

  The maximum object walking speed memory correction means 40 reflects the error in the default value when the estimated maximum walking speed and the actual maximum walking speed are different. The absolute value of the error multiplied by a certain value is added to the default maximum walking speed if the actual maximum walking speed is higher than the estimated maximum walking speed, and the maximum walking speed estimated by the actual maximum walking speed is added. If lower, subtract from the maximum walking speed of the default memory content. In addition, every time one of the highest walking speed memories is added by the highest walking speed storage means 39, it is within a certain range (the default value interval is one side and the cube is centered on the added actual data. ) Delete the default value in

  Also, in each of the three items of heel height, heel thickness, and fixing method, examine how much the maximum walking speed changes by 1 km / h. Two shoes (A, B) of the same type with the same two items (referred to as a, b) but different from one item (referred to as c), and the maximum walking speed of the two shoes are taken as samples (Fig. 17). 1 item (a) is the same as the two shoes (A, B), and two items (b, c) are the same type of shoes (C) different from either of the two shoes, the maximum walking speed, Estimation is made based on the difference between the maximum walking speed of the two shoes (A, B) and the item c (FIG. 18). The difference between the estimated maximum walking speed and the actual maximum walking speed of shoe C is stored as a change in the maximum walking speed due to the difference in item b. Using the stored content of the change in the maximum walking speed due to the difference in the items, a graph (FIG. 19) of the relationship between the change in each item and the change in the maximum walking speed is created, and how fast the maximum walking speed is from the worst case It expresses by becoming. How much a certain value of an item changes is 1 km / h faster is calculated by dividing 1 km / h by the slope at a certain value.

  FIG. 11 is a diagram showing the shapes of seven types of shoes (footwear). As shown in the figure, (a) sneakers, (b) sandals, (c) mules, (d) pumps, (e) boots, (f) petan shoes, (g) bald It is. The maximum walking speed storage means 39 and the standard walking speed storage means 42 store the shoe type together with the shoe ID and heel height, heel thickness, fixing method, maximum walking speed or standard walking speed. .

  FIG. 12 is a diagram illustrating a shape example of a shoe. As shown in the figure, (a) is a photograph of the side of the shoe, and the white arrow indicates the height of the heel. (b) is the heel part on the back of the shoe, and the white arrow is the thickness of the heel. The height of the heel and the thickness of the heel are stored as a shoe shape together with the shoe ID and type, the maximum walking speed, or the standard walking speed in the shoe speed storage means. As the type and shape of the shoe, the type of shoe (any one of FIGS. 11 (a) to (g), the height of the heel (FIG. 12 (a)), the thickness of the heel (FIG. 12 (b)), fixed Four methods (FIGS. 13 and 14) are stored.

  FIG. 13 is a diagram illustrating a method for fixing shoes and feet. As shown in the figure, if you have a heel, if there is no belt, if there is no belt, if there is something that fixes the upper, and if there is something (Fig. 14) It is classified into 6). Numbers representing ease of walking are assigned to the six fixing methods, and the numbers are stored together with the type of shoes, heel height, heel thickness, speed, and ID.

  FIG. 14 is a diagram for explaining the fixing method shown in FIG. 13 in the shape of a shoe. As shown in the figure, (a) and (b) are with and without heel, (c) and (d) are with and without a belt behind, (e) and (f) are It is an example of shoes with and without a thing to fix. According to the three cases, the shoe fixing method is classified into six, and a numerical value representing ease of walking is assigned. The numerical value is stored together with the type of shoe, the height of the heel, the thickness of the heel, the speed, and the ID.

FIG. 15 is a three-dimensional map of a shoe fixing method, heel height, and heel thickness. As shown in the figure, the three axes are the height of the heel, the thickness of the heel, and the fixing method, and the black dots are the memories of the relationship between the values of the three items of the shoes and the speed. White dots are shoes for estimating the speed, and the speed is estimated based on the memory of the sample shoes numbered 1 to 8. Eight memories used for estimation as samples are memories of the same shoe type, in three items of heel height, heel thickness, fixing method,
・ All three items are the closest memories that are easier to walk than the guessed shoes (point 1 in FIG. 15)
・ All three items are the closest memories that are harder to walk than the guessed shoes (point 2 in FIG. 15)
・ Of the three items, only the heel height is the closest to the memory that is difficult to walk (point 3 in FIG. 15)
・ Of the three items, only the thickness of the heel is the closest to the memory that is difficult to walk (point 4 in FIG. 154)
-Of the three items, the closest one of the memories that only the fixing method is difficult to walk (point 5 in Fig. 15)
・ Of the three items, only the height of the heel and the thickness of the heel are the closest in memory that is difficult to walk (point 6 in FIG. 15)
・ Of the three items, only the thickness of the heel and the fixing method are the closest in memory that is difficult to walk (point 7 in FIG. 15)
・ Of the three items, only the fixing method and the height of the heel are the closest ones that are difficult to walk (point 8 in FIG. 15).
It is. The arrows represent the vector from each sample to the shoe that estimates the speed. The vector is used in the calculation to estimate the speed of the white spot shoe as the distance between the shoe and the sample that estimates the speed of the white spot. That is, this three-dimensional map is used as an object-specific walking influence table in the case of shoes.

  FIG. 16 is a default three-dimensional map of a shoe fixing method, a heel height, and a heel thickness. As shown in the figure, three points of fixing method, heel height, and heel thickness are used as axes, and each point stores the speed of a shoe having the shape of each value of three items. In the initial state, the speed of a general shoe is stored as a default value, and the default value is uniformly present in the entire range by changing the value of each item at a constant interval. When the user 16 activates the customization function when walking, the memory of the shoe information and the speed accumulates, and the speed of the shoe is estimated based on the customized memory. However, since the memory does not exist in the initial state, and there are cases where the number of memories is insufficient to guess by the shoes to be worn, the default value is used to supplement the memory of the actual walking of the user 16. Used to guess.

  FIG. 17 is a diagram showing three points for examining how much each item changes to change the speed by 1 km / h. As shown in the figure, the three axes a, b, and c are either the heel height, the heel thickness, or the fixing method, and points A, B, and C indicate the relationship between the values of each of the three items and the speed. It is a memory for each shoe. In order to examine how much the speed changes by 1 km / h depending on the heel height, heel thickness, and fixing method, two items (referred to as a and b) are the same as the sample. Take two shoes (A, B) of the same type with different (c) and the speeds of two shoes (standard walking speed or maximum walking speed). The speed of the shoe (C) is estimated based on the difference between the speed of the two shoes (A, B) and the item c (FIG. 18), and the difference between the estimated speed and the actual speed of the shoe C is It is memorized as a change in speed due to the difference. Using the stored contents of the change in speed due to the difference in items, a graph (FIG. 19) of the relationship between the change in each item and the change in speed is created and expressed as how fast the speed becomes from the worst case. How much a certain value of an item changes is 1 km / h faster is calculated by dividing 1 km / h by the slope at a certain value.

  FIG. 18 is a diagram showing a method for examining how much the speed changes by 1 km / h for each item. As shown in the figure, an item b (any of heel height, heel thickness, and fixing method) and a walking speed are used as axes, and a speed due to a change in the item b is represented. The black dots of A, B, and C are records for each shoe, and the white circle is the estimated speed of shoe C estimated based on points A and B. In order to investigate how much the speed changes by 1 km / h with each item of heel height, heel thickness, and fixing method, the two items (referred to as a and b) are the same and one item (c and The two types of shoes (A, B) of the same type differing) and the speed (standard walking speed or maximum walking speed) of the two shoes are taken as samples (FIG. 17), and one item (a) is the two shoes. Same as (A, B), two items (b, c) are different from both of the two shoes, the speed of the same type of shoes (C), the speed of the two shoes (A, B) and item c Guess based on the difference. The difference between the estimated speed and the actual speed of shoe C is stored as a change in speed due to the difference in item b. Using the stored contents of the change in speed due to the difference in items, a graph (FIG. 19) of the relationship between the change in each item and the change in speed is created and expressed as how fast the speed becomes from the worst case. How much a certain value of a certain item changes is 1 km / h faster by dividing 1 km / h by the slope at a certain value, when calculating the distance between the shoe and the memory of the speed and the estimated shoe use.

  FIG. 19 is a graph showing the magnitude of the change in speed due to the change in any of the three items. As shown in the figure, item b (heal height, heel thickness, fixing method) and how fast the heel is faster than the maximum, the minimum speed due to the change in item b It represents how fast it will be. Using the stored contents of the change in speed due to the difference in each item of the height of the heel, the thickness of the heel, and the fixing method, a graph of the relationship between the change in each item and the change in speed is created. The speed is expressed as how fast it is from the worst case. In the graph of FIG. 19, the slope is small when the value of item b is close to 0 and close to the maximum value, and the change in speed due to the change of item b is also small. Further, since the slope is large when the item b is about two-thirds of the maximum value, the change in speed due to the change in the item b is also large. The speed of 1 km / h when a certain value of a certain item is changed is calculated by dividing 1 km / h by the slope at a certain value, and used to calculate the distance between the estimated shoe and the memory of the sample. To do. By including how much a certain value of an item changes in the distance calculation, the change in which item of the heel height, heel thickness, and fixing method for the user 16 is large in speed. It is possible to reflect in the estimation of speed whether it affects.

  FIG. 20 is a detailed block diagram of the standard walking speed estimation means 26 shown in FIG. As shown in the figure, the standard walking speed estimation means 26 includes an article standard walking speed storage means 42 that stores the ID, type, shape, and standard walking speed of shoes (things), and shoes (things) worn by the user 16. The standard walking speed estimation means 41 for estimating the standard walking speed in the above-mentioned standard and the standard walking speed memory correction means 43 for correcting the stored contents of the standard walking speed storage means 42 so as to suit the user 16. . The standard walking speed of the user 16 and the ID, type, and shape of the shoes being worn are stored in the standard walking speed storage means 42.

  Based on the previous stored contents of the physical standard walking speed storage means 42, the standard walking speed of the shoes currently worn by the user 16 is estimated. If the shoe has been worn before, the previously stored standard walking speed is used. In the case of a shoe worn for the first time, the standard walking speed is estimated based on the memory contents of other shoes worn before. Even if there is no memory of shoe information and standard walking speed in the initial state, the default value is the general relationship between the type and shape of the shoes and the standard walking speed in order to estimate the standard walking speed of the first shoe to wear. It is put in the physical standard walking speed storage means 42 (FIG. 16). Since the default value is different from the relationship between the information on the shoes of the individual 16 users and the standard walking speed, the default value is changed based on the error between the estimated standard walking speed and the actual standard walking speed. This makes it possible to estimate the standard walking speed of the object (shoes) that matches. The article standard walking speed storage means 42 stores the shoe ID, type, shape, standard walking speed, and the like.

  If the acquired standard walking speed changes, the memory is updated. However, when the first walking abnormality determining means 23 or the second walking abnormality determining means 25 determines that the walking of the user 16 is abnormal, it is not updated to the acquired standard walking speed. Also, even if the shoe shape and type are the same, if the ID is different, it is not updated and stored separately. Since there is no actual memory in the initial state, the relationship between the type and shape of general shoes and the standard walking speed is stored as a default value. The ID is the default value. The default value is to change each item at a constant interval and make it uniformly exist in the entire range (FIG. 16).

  The object standard walking speed estimation means 41 estimates the standard walking speed of a shoe based on the storage of the type, shape, and ID of the shoe. The information on the type, shape and ID of the shoe is extracted from the RFID information of the shoe. In the previous memory stored by the object standard walking speed storage means 42, it is checked whether there is information on the shoe with the same ID, and if there is, the previous standard walking speed of the shoe with the same ID is determined. Use standard walking speed. Also, if there is no memory of the same ID and the same shape and type of shoes, the standard walking speed of the estimated shoes is reduced by a certain rate by reducing the standard walking speed of the same shape and type of shoes. Speed. If there is no memory of the same ID and the same shape and type in the previous memory, 8 memories are taken as samples from the memory contents of other shoes and the memory contents that are included by default, and inferred based on the 8 samples I do.

  The memory used for estimation as the sample is the same as the method related to the maximum walking speed. In addition, in order to examine the proximity of each of the eight samples to estimate the standard walking speed (the shoes to be estimated) and the sample, how much changes in the three items of heel height, heel thickness, and fixing method The standard walking speed changes by 1 km / h, and the distance between the two points is calculated. The calculation of the standard walking speed of the estimation target shoe is performed by dividing the standard walking speed of the sample by the distance between the sample and the estimation target shoe, respectively, and adding them up. The total number is multiplied by the sample distance and divided by the total sample distance, and the calculation result is used as the standard walking speed of the shoe to be estimated. This is also the same as the maximum walking speed related technique.

  The object standard walking speed memory correcting means 43 reflects the error in the default value when the estimated standard walking speed and the actual standard walking speed are different. The absolute value of the error multiplied by a certain value is added to the default standard walking speed if the actual standard walking speed is higher than the estimated standard walking speed, and the standard walking speed estimated by the actual standard walking speed is added. If it is lower, it is subtracted from the standard walking speed of the default stored contents. Also, every time one standard walking speed memory is added by the standard walking speed memory means 42, a cube within a certain range (with the default value interval as one side and the actual data added as the center) Delete the default value in ().

  Also, in each of the three items of heel height, heel thickness, and fixing method, examine how much the standard walking speed changes by 1 km / h. Two shoes (A, B) of the same type with the same two items (referred to as a, b) but different from one item (referred to as c), and the standard walking speed of the two shoes are sampled (FIG. 17). 1 item (a) is the same as the two shoes (A, B), and 2 items (b, c) are the standard walking speeds of the same type of shoes (C) different from both of the two shoes, The estimation is based on the difference between the standard walking speed of the two shoes (A, B) and the item c (FIG. 18). The difference between the estimated standard walking speed and the actual standard walking speed of shoe C is stored as a change in the standard walking speed due to the difference in item b. Using the stored contents of changes in standard walking speed due to differences in the items, a graph (FIG. 19) of the relationship between changes in each item and changes in standard walking speed is created. How fast is the standard walking speed from the worst case? It expresses by becoming. How much a certain value of an item changes is 1 km / h faster is calculated by dividing 1 km / h by the slope at a certain value.

  FIG. 21 is an example of distribution of walking interval data. As shown in the figure, the horizontal axis represents the stride walking interval, and the vertical axis represents the number of data, and represents how much data of each value of the walking interval was present. In FIG. 21 (a), there is one mountain, and values acquired with high frequency are gathered into one. Assuming that the distribution of (a) is a normal data distribution, it is determined that walking is performed in a normal state when speed or stride is distributed in the same form as (a), and FIG. If there are two mountains and the values acquired with high frequency are divided into two, it is judged as walking in an abnormal state. When there is an abnormality such as shoe rubbing and normal walking is not possible, the walking interval often differs between the left and right feet, and by detecting the distribution of the walking interval, the user's 16 walking abnormality is detected and considered Walking guide is possible.

  FIG. 22 is a diagram illustrating an example of an actual walking speed and a required walking speed (walking navigation information) in the walking guide. In FIG. 22 (a), the horizontal axis is time, the vertical axis is speed, and the solid line is the actual speed when you depart 10 minutes before going to your destination 1km ahead, the required walking speed that the thin broken line is transmitted, A thick broken line represents a necessary walking speed that is not transmitted. In the graph of FIG. 22B, the horizontal axis represents time, the vertical axis represents distance, and the distance from the departure point when walking at each speed is shown. The solid line is the actual speed, the required walking speed at which the thin broken line is transmitted, and the thick broken line is the standard walking speed. The standard walking speed is 6 km / h. The timing for checking whether the current speed is in time is 1.25 minutes. Initially (when time is 0 minutes), the maximum walking speed and the standard walking speed are estimated based on the type, shape, and ID of the shoes worn by the highest object walking speed memory estimating means 37 and the standard walking speed estimating means 26. While walking at the required walking speed of 6 km / h, nothing is transmitted to the user 16.

  If it falls to 3km / h on the way, it will be judged that it will not be in time from 3.75 minutes, and a speed of about 6.6km / h will be reported to be in time. If you walk at the speed of 6.6km / h, you can get to your destination on time. If you walk at 3km / h without increasing the speed, the necessary walking speed will be recalculated 1.25 minutes later (5 minutes) and you will be told to walk at 7.5km / h. Also, if you start from 5 minutes to 12km / h, after 1.25 minutes (6.25 minutes), you will reach the position of walking at normal walking speed. When reaching, the transmission of the speed to the user 16 ends. Even if the vehicle continues to run at a speed of 12 km / h, nothing is transmitted to the user 16. In this way, what is to be rushed and how fast to walk are reported, and when walking at the reported speed, it is possible to arrive at the destination at the desired arrival time.

  FIG. 23 is a diagram showing an example of the speed and distance when going to a destination 6 km away in one hour. This figure shows the relationship between the actual speed, the required walking speed, and the distance when starting and walking one hour ahead toward the destination 6 km away. FIG. (B) shows the case of heel. In the upper two graphs, the horizontal axis represents time, and the vertical axis represents speed. The bottom two graphs show how far you have traveled from your starting point, with time on the horizontal axis and distance on the vertical axis. The solid line is the actual speed, the broken line is the required walking speed, and ○ is the point that it should be given up. First, the maximum walking speed is estimated based on the type, shape, and ID of the shoes worn by the maximum object walking speed memory estimating means 37. The estimated maximum walking speed is 12 km / h for sneakers and 9 km / h for heels. Since walking 6km in 1 hour, the required walking speed is calculated as 6km / h. Nothing is transmitted while walking at 6km / h for the first time.

  When the speed drops to 3 km / h after 30 minutes, the required walking speed is transmitted to the user 16. If you keep walking at 3km / h as it is, Sneaker has a maximum walking speed of 12km / h, 50 minutes later, and heel has a maximum walking speed of 9km / h, 45 minutes later, 3km / h or less as it is If the user keeps walking, the user 16 will not be in time, and the user 16 will be notified that it will not be in time. In this way, it is determined whether it is enough to walk (run) at the maximum walking speed according to the shoes, and it is not necessary to walk (run) at an unreasonable speed, thus reducing the risk of falling. It becomes possible. In addition, the possibility of not being in time even though there is a possibility of being in time is reduced, and more appropriate guidance is possible.

  FIG. 24 is a flowchart showing a flow of a process for correcting the storage of an object and adjusting the estimation to the user. A case where this processing is applied to shoes will be described. As shown in the figure, when walking normally (step s31), the standard walking speed and the maximum walking speed of the shoes are estimated (steps s32 and s33). The actual standard walking speed is calculated based on the memory of the actual walking speed (step s34). The standard shoe speed memory is corrected based on the difference between the standard walking speed and the estimated speed (step s36). Also, if there is no actual record of the maximum walking speed, the maximum shoe speed memory is corrected. If a speed exceeding the maximum walking speed estimated during normal walking is measured, the memory is rewritten to the exceeding speed (step s35). During the walking guide process (step s41), the maximum walking speed of the shoes being worn is estimated (step s42). When a speed exceeding the estimated speed is measured during walking, the memory is rewritten to the above speed at any time during the walking guide process. Also, instruct the driver to run at the estimated maximum walking speed, and if the estimated speed is not reached even if the speed increases and there is no actual memory, the highest speed among the actual speeds during the walking guide process The memory is rewritten to the value of (steps s43, s44). With the above processing, it is possible to estimate an appropriate speed even in the case of shoes worn for the first time after buying or shoes walking fast for the first time.

  FIG. 25 is a diagram illustrating how the record update and the default value correction are performed. As shown in the figure, the horizontal axis is time, the vertical axis is distance, and the lines in the graph show examples of the distance traveled at each speed. FIG. 25 (a) is a case of normal walking, FIG. 25 (b) is during a walking guide, and FIG. 25 (c) is a case where it is requested to walk at the maximum walking speed estimated during the walking guide. It is. At the time of walking, first, the maximum walking speed and the standard walking speed of the shoes being worn are estimated based on the memory of the type, shape and speed of the shoes. (a) In the case of normal walking, if the standard walking speed of the actual walking is different from the estimated standard walking speed, the memory of the standard walking speed is updated to the value of the actual speed, and the standard walking speed is entered. Modify the default values. Also, the default value of the maximum walking speed is corrected by multiplying the value (0 to 1.0) in the correction of the standard walking speed. In the case of the walking guide (b), correction and updating are not performed due to the difference between the actual standard walking speed and the estimated standard walking speed. In the example of FIG. 24 (b), since walking is actually performed at a speed higher than the estimated maximum walking speed during walking, the memory update of the maximum walking speed and the default value correction are performed. Multiply the value for the maximum walking speed correction (0 to 1.0) to correct the default value for the standard walking speed. Similarly, if a speed exceeding the estimated maximum walking speed appears even during normal walking, the memory is updated and the default is corrected. When (c) requires walking at the maximum walking speed estimated during the walking guide, the requested maximum walking speed is not output. In this way, when the maximum walking speed is requested and the estimated maximum walking speed is not reached, but walking at a certain rate or more, the memory of the maximum walking speed is updated and the default value is corrected. The standard walking speed is also corrected to the default value.

  Even if the shoes are worn for the first time during the walking guide, if there has been walking before, the standard walking speed has a memory, and the maximum walking speed is also estimated based on the corrected default value (FIG. 25 (a)). If you walk more than your estimated maximum walking speed, your previous memory exists. In addition, even for shoes that have not been walked before, the default value for other shoes is modified from the general default value to the default value more suitable for user 16, and the default value for user 16 is corrected. The speed is estimated based on Even during the walking guide, the memory of the maximum walking speed is updated, the default value is corrected, the standard walking speed is corrected, and even if the initially estimated speed does not match the shoes, the shoes that are worn more in the middle A matching guide is given. In this way, more appropriate guides can be provided even for shoes worn for the first time by updating memory during normal walking guides and correcting default values.

  According to the present invention, it is determined whether or not it is in time for shoes that are worn in consideration of the characteristics of the user's walking shoes, and appropriate determination is made as to whether or not it is in time without making the user walk unreasonably. Walking guide is possible. It is possible to provide a walking guide that takes into account not only the type and shape of the shoes, but also the time when the shoes were previously worn, walking abnormalities such as shoe rubbing, and the weather. In addition, it is possible to provide an easy-to-use walking guide that conveys the necessary speed to the user accurately by vibration or sound without looking at the screen, in a more urgent situation.

As described above, the invention has been described for shoes as close objects, but the present invention can provide walking navigation information in which the influence on the walking speed of clothes, bags, and the like is also calculated as close objects. FIG. 26 is a diagram showing three axes stored in addition to speed and shoe information in the standard walking speed estimation means and the maximum walking speed estimation means. Standard walking speed estimation means, maximum walking speed estimation means, standard walking speed or maximum walking speed, shoe ID, shoe type, shoe heel height, shoe heel thickness, shoe fixing method, etc. In addition, the following three items are added and stored.
・ Type of heel you have ・ (Standard) volume of heel you have (the larger the volume, the more difficult it is to walk and the lower the walking speed)
・ Types of clothes you are wearing

The type of bag is acquired from the tag information itself or from a product information database based on the tag information and stored,
-Rucksacks, backpacks, etc. Classify and memorize them by dragging or pushing to carry them. The standard volume of the bag is obtained from the tag information itself or a product information database based on the tag information. Also, the type of clothes is acquired from the tag information itself or the product information database based on the tag information, and is divided into four types: pants (including overalls and culottes), skirts (including one-piece), skirts, kimonos, and yukatas. Classify. However, in the skirt,
Hem width length x size (hip) x constant α-length (from waist to hem)
Is calculated and classified into a plurality of values with a predetermined numerical range.

  As described above, in addition to shoe information, three items of information are stored and handled in the same way as the three items of shoes. Add the three items of heels and clothes to the three items of shoes and calculate in the same way to estimate the maximum walking speed and standard walking speed. The correction of the distance within each item is also made in 6 items, including 3 items of heel type, heel volume, and clothing type, as in the case of 3 items of shoes. In addition, when there are a plurality of kites, the slowest value among the estimated speeds is used. By adding the above, it is possible to provide a walking guide that takes into account not only shoes, but also a decrease in speed due to heels and clothes.

  Although the present invention has been described based on the drawings and examples, it should be noted that those skilled in the art can easily make various modifications and corrections based on the present disclosure. Therefore, it should be noted that these variations and modifications are included in the scope of the present invention. In addition, the functions included in each member, each means, each step, etc. can be rearranged so as not to be logically contradictory, and a plurality of means, steps, etc. can be combined into one or divided. Is possible. For example, the object-specific walking effect table and the three-dimensional walking effect map shown in FIGS. 1 and 26 are merely examples, and not only in various formats, for example, not only tables and maps but also arithmetic expressions according to objects. It should be noted that the present invention can be implemented.

1 Mobile terminal device
2 Position acquisition means
3 Route determination means
4 Proximity identification method
5 Storage means
5A walking effect table
6 Notification means
7 Customization methods
AR proximity area
10 Walking guide means
12 Required walking speed determination means
13 Movement condition setting method
14 Time acquisition means
15 Position acquisition means
16 users
19 Movement condition achievement judgment means
20 Maximum walking speed estimation means
21 Weather information acquisition means
22 Communication means
23 Gait abnormality judgment means
24 Walking interval acquisition means
25 Walking abnormality judgment means
26 Standard walking speed estimation means
27 Object information acquisition means (RFID reader)
28 Walking speed acquisition means
29 Route estimation means
30 Route registration means
31 Alarm means
32 Required walking interval calculation means
33 Notification means
34 Notification judgment means
35 Overall maximum walking speed estimation means
36 Means for estimating weather influence speed
37 Means for estimating the maximum walking speed memory
38 Means for estimating maximum walking speed
39 Maximum walking speed memory
40 object maximum walking speed memory correction means
41 Standard object walking speed estimation means
42 Standard walking speed memory means
43 Standard walking speed memory correction means
44 Mobile devices

Claims (2)

A portable terminal device,
Position acquisition means for acquiring a current position of the mobile terminal device;
Destination setting means for setting the destination;
Proximity object identification means for identifying an object in proximity to the mobile terminal device;
Calculating means for calculating an expected speed based on the object identified by the proximity object identifying means;
Expected rate based on those currently being identified, before Kigen standing position, and a notification means for notifying a walking navigation information generated based on prior Symbol their destinations,
A portable terminal device comprising: A method for controlling a portable terminal device, comprising:
A position acquisition step of acquiring a current position of the mobile terminal device using positioning means;
A destination setting step for setting a destination;
A proximity object identifying step for identifying an object in proximity to the mobile terminal device using a proximity object identifying means;
Expected rate based on those currently being identified, before Kigen standing position, and a notification step of notifying the walking navigation information generated based on prior Symbol their destinations,
A control method for a mobile terminal device, comprising:

Images