WO2020020535A1 - Procédé de configuration d'une pluralité de coordonnées de position destiné à un positionnement en intérieur - Google Patents

Procédé de configuration d'une pluralité de coordonnées de position destiné à un positionnement en intérieur Download PDF

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Publication number
WO2020020535A1
WO2020020535A1 PCT/EP2019/065737 EP2019065737W WO2020020535A1 WO 2020020535 A1 WO2020020535 A1 WO 2020020535A1 EP 2019065737 W EP2019065737 W EP 2019065737W WO 2020020535 A1 WO2020020535 A1 WO 2020020535A1
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level
locations
level sub
location
sub
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Inventor
Abhik Banerjee
Gopalan Venkoparao VIJENDRAN
Prabhakar Ragavendra
Himadri Sikhar KHARGHARIA
Amit Parasmal BORUNDIYA
Sheelvant Mahalingeshwara HEMANTH
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Robert Bosch GmbH
Bosch Global Software Technologies Pvt Ltd
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Robert Bosch GmbH
Robert Bosch Engineering and Business Solutions Pvt Ltd
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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0252—Radio frequency fingerprinting
    • G01S5/02521—Radio frequency fingerprinting using a radio-map
    • G01S5/02524—Creating or updating the radio-map
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0252—Radio frequency fingerprinting
    • G01S5/02521—Radio frequency fingerprinting using a radio-map

Definitions

  • This invention is related to a method of configuring a plurality of position co- ordinates for indoor positioning.
  • Indoor location detection is used in many applications such as in shopping malls, tourist locations, hospitals and warehouses for locating or providing directions to users.
  • all existing techniques involve a pre-configuration or training phase, as part of which a map of individual locations with observations recorded using one or more technologies is constructed. Subsequent indoor positioning takes place by comparing online measurements with the pre-constructed map.
  • the map creation procedure is tedious and needs to be updated regularly, involving significant overhead, and can act as a barrier to adopting indoor positioning technologies.
  • an indoor positioning system and method of localizing a person/object in an indoor environment by identifying the orientation and direction of a person/object to provide a true location of the person/object without navigation errors comprises magnets disposed on a doorway to create a unique magnetic field, a wireless communication unit comprising a magnetometer sensor to sense perturbations in each of the unique magnetic fields in the event that the person/object with the wireless communication unit passes through the doorway, and generate corresponding signals, a processor receiving the signals and extracting data from the same, and a backend server wirelessly communicating with the wireless communication unit, the backend server processing the data sample received from the wireless communication unit to identify the opening and the wireless communication unit to localize the person/object.
  • Figure 1 is a flowchart illustrating a method of configuring a plurality of position co-ordinates for indoor positioning, in accordance with one embodiment of this disclosure
  • Figure 2 is a flowchart illustrating a method of configuring a plurality of position co-ordinates for indoor positioning, in accordance with one embodiment of this disclosure.
  • Figure 3 is an exemplary illustration of a method of configuring a plurality of position co-ordinates for indoor positioning, in accordance with one embodiment of this disclosure.
  • the present disclosure discloses a method of configuring a plurality of position co-ordinates for indoor positioning in accordance with one embodiment.
  • the method includes retrieving a reference map of an indoor location, the reference map comprising fingerprint data of at least one labelled location with reference to at least one access point, establishing a first level relationship between a plurality of first-level sub-locations with respect to the at least one labelled location, the first level relationship is established by relating signal-strength value associated with each of the plurality of first-level sub-locations with a signal-strength value associated with the fingerprint data of the at least one labelled location, establishing a second level relationship between a plurality of second level sub-locations within each of the plurality of first level sub-locations by grouping the plurality of second level sub locations into at least one cluster, determining at least one position co-ordinate based on the grouping and storing the at least one position co-ordinate in the reference map for enabling the indoor positioning.
  • the present disclosure discloses a method of configuring a plurality of position co-ordinates for indoor positioning in accordance with one embodiment.
  • the method includes monitoring time stamps associated with a user device in relation to a plurality of signal strength values that correspond to the user device with reference to at least one access point, grouping of the time stamps into at least one first level cluster based on the received signal strength values, establishing a first level relationship between one or more first-level sub-locations, within the first level cluster, with each other with reference to the at least one access point, establishing a second level relationship between one or more second-level sub-locations within each of the one or more first- level sub-location by grouping the one or more second-level sub-locations into at least one second level cluster, determining the position of the user device based on the at least one second level cluster and storing the determined position in a map to for configuring the plurality of position co-ordinates for the indoor positioning.
  • Figure 1 is a flowchart illustrating a method of configuring a plurality of position co-ordinates for indoor positioning, in accordance with one embodiment of this disclosure
  • the method is performed by a processor present in a server.
  • the server may be located in the cloud or physically be present in an indoor space where the position co-ordinates are to be configured.
  • the processor performs the method in steps 105 through 125 depicted in the flowchart of Figure 1.
  • a reference map of an indoor location is retrieved by the processor.
  • Such a reference may be stored in a memory unit that is accessed by the processor.
  • the reference map includes fingerprint data of at least one labelled location with reference to at least one access point. Examples of the access point include, but are not limited to, WIFI access point, Bluetooth access point and the like.
  • the Fingerprint data refers to a signal strength value of a signal emitted from a user device which is received by the access point. The signal strength value indicates distance of the user device with reference to the access point. Greater the signal strength value, closer is the user device to the access point.
  • the labelled location indicates one location which has a label tagged to it.
  • the label can be name of the building, for example, if it is a shopping mall then it can be“Shopping mall- A”.
  • the label can also be name of specific locations in a floor, for example,“lobby area”,“Entry” and“Exit”.
  • the reference map in other words is a floor map including one or a limited number of labelled locations in the indoor space.
  • the fingerprint data includes the label, signal strength value associated with each label with reference to the access point and the position co-ordinate for each label.
  • Such a reference map is used for determining other position co-ordinates in the indoor space which will be explained in detail in the following paragraphs.
  • the processor establishes a first level relationship between a numerous first-level sub-locations with respect to the labelled location.
  • the first-level sub-locations include locations that form a subset of the labelled location.
  • the first level relationship indicates that the first-level sub-locations form such a subset of the labelled location.
  • the first level relationship corresponds to peer-to- peer relationship among the plurality of first-level sub-locations associated with the at least one labelled location. It should be noted that these first-level sub-locations do not have any labels associated with them. This is explained with an example for clear understanding in conjunction with Figure 3. Consider the indoor space as a shopping mall having 7 floors.
  • the labelled location is“Shopping mall-A” and the first-level sub-locations include“l-floor, 2-floor, 3-floor, 4-floor, 5-floor, 6-floor and 7-floor”.
  • the first level relationship is the relationship that exists between the labelled location which is“Shopping mall-A” and all the floors that fall under the labelled location“Shopping mall-A”. This is illustrated in Figure 3 as 305.
  • the processor establishes the first level relationship by determining relationship between the signal strength value of one first-level sub-location and the signal strength value of the labelled location (fingerprint data) which is already known and is stored in the reference map. For example, if the signal strength value of the labelled location is“X” then the first level relationship for one first-level sub-location may be“0.25X”. Similarly, the first level relationship for another first-level sub location may be“0.4X”. The first level relationship is established by relating signal- strength value associated with each of the plurality of first-level sub-locations with a signal-strength value associated with the fingerprint data of the at least one labelled location.
  • the processor stores the determined signal strength values of each of the first-level sub location in the reference map. It should be noted that, even at this point, only the signal strength values associated with numerous first-level sub-locations are known. However, the labels associated with each of the first-level sub-locations are still not known and also the position co-ordinates of these numerous first-level sub-locations are not known at this point.
  • the processor establishes a second level relationship between a plurality of second level sub-locations within each of the first level sub-locations.
  • the second level relationship is a relationship existing between one first level sub-location and numerous second level sub-locations that form a subset of that first level sub-location. This is explained considering the previous example. It is considered that the indoor space is the same shopping mall having 7 floors.
  • the labelled location is“Shopping mall- A” and the first-level sub-locations include“1- floor (3 l0a), 2-floor (310b), 3-floor (3 l0c), 4-floor (3 l0d), 5-floor (3 l0e), 6-floor (31 Of) and 7-floor (3 l0g)” as shown in Figure 3.
  • the second level sub-locations include locations within each first level sub-locations.
  • the first level sub location“l-floor” may include“second level sub-location- 1” (3 l5a),“second level sub-location-2 (315b)” and“second level sub-location-3 (315c)”.
  • The“second level sub-location- 1” (315a),“second level sub-location-2 (315b)” and“second level sub location-3 (3 l5c)” are three different locations within the first level sub-location“1- floor (3 l0a)”.
  • each first level sub-location may include one or many second level sub-locations within it.
  • the second level relationship is established by determining a relation between the signal strength value of one first-level sub-location that was determined in step 110 and the signal strength value of the signal obtained from a user device when the user device is positioned at one of the second level sub-location with reference to the access point.
  • the second level sub-locations whose signal strength value is in relation with the signal strength value of one first-level sub-location are grouped into at least one cluster. Therefore, all the second level sub-locations grouped into one cluster are identified to be associated to one specific first-level sub-location. I should be noted that each first-level sub-location may include one or more such clusters.
  • the second level relationship corresponds to hierarchical relationship between a plurality of second-level sub-locations and each first-level sub-location of the numerous first-level sub-locations described in step 110.
  • the second-level sub locations are depicted in Figure 3 as (315a, 315b, 315c) under the first-level sub location (3 l0a). Therefore, at the end of step 115, the processor determines signal strength values associated with numerous second-level sub-locations that correspond to each first-level sub-location. Further, the processor stores each of these values in the reference map. It should be noted that, at the end of step 115, only the signal strength values associated with numerous second-level sub-locations that correspond to each first-level sub-location is known. However, the position co-ordinate and the labels associated with each second-level sub-locations are yet to be determined by the processor.
  • the processor determines a plurality of position co-ordinates based on the grouping.
  • the position co-ordinates are determined based on the signal strength values of each of the first-level sub-locations and the signal strength values associated with numerous second-level sub-locations stored in the reference map.
  • the position co-ordinates are determined with reference to the fingerprint data stored in the reference map.
  • the position co-ordinates which is a part of the fingerprint data are subjected to interpolation technique or extrapolation technique for determining the position co-ordinates associated with the first-level sub-locations and the second-level sub-locations.
  • the processor stores the position co-ordinates determined in step 120 in the reference map.
  • the reference map thus includes position co-ordinates of numerous first-level sub-locations and the second level sub-locations.
  • the reference map includes signal strength values along with position co-ordinates of numerous first-level sub-locations and the signal strength values along with position co-ordinates of numerous second-level sub-locations. Therefore, as the user device hovers around the indoor space, based on the signal strength value determined by the processor, the associated position co-ordinate is retrieved from the created reference map.
  • the processor repeats step 105 through step 125 iteratively for populating the reference map so that position co-ordinates can be determined for many other location within the indoor space.
  • each of the position co-ordinates determined in the step 125 can be tagged with a label. Tagging can be done by manually entering the data or in another case, the user can tag the label for the position co-ordinates determined in the step 125.
  • the method of tagging a label can be explained with reference to the previous example.
  • the first-level sub- location“l-floor (3 l0a)” may be tagged as“Clothing”.
  • the first-level sub location“2-floor (310b)” may be tagged as“Footwear”.
  • the first-level sub location“3-floor (3 lOc)” may be tagged as“Cinema” and the like.
  • the second- level sub-location which is“second level sub-location- 1” may be tagged as“entrance”.
  • the“second level sub-location-2” may be tagged as“exit”
  • the“second level sub-location-3” may be tagged as“Payment”
  • the method in the present disclosure enables configuring position co-ordinates for an indoor space automatically without using training data.
  • the position co-ordinates are determined in real-time which eliminate tedious process of pre-calibrating the training data.
  • the disclosure also enables updating the reference map dynamically so that the position co-ordinates of all the locations can be configured in real-time.
  • the method does not limit to first and second level relationships alone. There may further levels of granularity involved depending on indoor space.
  • FIG. 2 is a flowchart illustrating a method of configuring a plurality of position co-ordinates for indoor positioning, in accordance with one embodiment of this disclosure.
  • the method is performed by the processor from step 205 through 225.
  • the processor monitors the time stamps associated with a user device in relation to a plurality of signal strength values received from the user device with reference to at least one access point.
  • the processor receives the signal from the user device and the signal strength values determined by the processor with reference to one or more access points.
  • the processor upon determining the signal strength values, appends a time stamp to each signal strength value.
  • Such the time stamps are monitored to identify location of a user in the indoor space for a specific time interval. By determining the location of the user for the specific time interval, an interest of the user can be identified.
  • the processor performs grouping of the time stamps into at least one first level cluster based on said received signal strength values. Grouping includes combining time stamps that are close to each other into a first level cluster. It should be noted that there may be one first level cluster or many first level clusters. Such clustering of the time stamps is performed to identify various first-level sub-locations associated to the one or more first level clusters.
  • the processor establishes a first level relationship between one or more first-level sub-locations associated to the first level cluster, with each other with reference to the access point.
  • the first level relationship is established by associating each first level cluster to first-level sub-location.
  • many such first level clusters are associated to a corresponding first-level sub-location.
  • the signal strength values in each first level cluster are almost similar to each other.
  • each first-level sub-location will correspond to an average signal strength value obtained based on the numerous signal strength values associated with each first level cluster. Therefore each first-level sub-locations will be associated with a corresponding average signal strength value.
  • the first level relationship between one or more first-level sub-locations with each other is established by determining a relation between the average signal strength value that correspond to each first-level sub-locations with each other.
  • the relation between the average signal strength value is such that it indicates that there exists a peer-to-peer relationship between the first-level sub-locations with each other. Therefore, by clustering numerous time stamps into one or more first level clusters, a first level relationship can be established between numerous first-level sub-locations with reference to one or more access points which is/are fixed in the indoor space.
  • the processor establishes a second level relationship between one or more second-level sub-locations within each of the one or more first-level sub location by grouping the one or more second-level sub-locations into at least one second level cluster. Grouping of the one or more second-level sub-locations into at least one second level cluster is obtained by aggregating a set of time stamps that are close to each other into one second level cluster. It should be noted that there may be one or more than one second level clusters within each first-level sub-location. Similarly, each first-level sub-location may be associated with one or more such second level clusters. Therefore, the second level clusters form a hierarchical relationship between a specific first-level sub-location and the second-level sub locations within that first-level sub-location.
  • the second level relationship is a relation between the signal strength value associated with the set of time stamps in the second level cluster and the average signal strength value associated with a specific first-level sub-location. Therefore, each first- level sub-location will be associated with a fixed factor that establishes a relation with its second-level sub-locations.
  • the processor determines the position of the of the user device based on the second level cluster. The position is determined by assigning position co- ordinates to each second-level sub-location that corresponds to second level cluster. The position co-ordinates are assigned based signal strength value associated with the each second-level sub-location.
  • the processor stores the position determined in step 230 in a reference map thereby enabling configuration of a plurality of position co-ordinates for indoor positioning.
  • the reference map includes a corresponding signal strength value, a time stamp and a position co-ordinate associated with every second- level sub-location and every first-level sub-location. Therefore as the user device hovers around the indoor space, based on the signal strength value determined by the processor, the associated position co-ordinate is retrieved from the created reference map in real-time.
  • the method in the present disclosure enables configuring position co-ordinates for an indoor space automatically without using training data.
  • the position co-ordinates are determined in real-time which eliminate tedious process of pre-calibrating the training data by using time stamp values.
  • the disclosure also enables updating the reference map dynamically so that the position co-ordinates of all the locations can be configured in real-time.
  • FIG. 2 The method disclosed in Figure 2 is explained with an example for clear understanding of the disclosure. It is considered that the user device enters a mall named“Shopping Mall X”. The user device hovers around the“Shopping Mall X”. As the user device hovers around the“Shopping Mall X”, numerous time stamps associated with the user device is monitored and captured by the processor. Also, signal strength associated with the time stamps are also captured with reference to one access point present in the“Shopping Mall X”.
  • Each of these time stamps are associated with a specific signal strength value reference to the access point. It is considered that the time stamps 5 PM, 5.01 PM, 5.03 PM, 5.05 PM, 5.07 PM, 5.10 PM, 5.12 PM, 5.15 PM, 5.17 PM, 5.19 PM, 5.20 PM, 5.21 PM, 5.23 PM, 5.25 PM are associated with almost similar signal strength values. Further, the time stamps 5. 40 PM, 5.42 PM, 5.43 PM, 5.45 PM, 5.47 PM, 5.49 PM, 5.50 PM, 5. 53 PM, 5.55 PM, 5.57 PM, 6.00 PM, 6.01 PM, 6.03 PM, 6.05 PM are associated with almost similar signal strength value different from similar signal strength values associated with the previous set of time stamps.
  • the first set of time stamps (5 PM, 5.01 PM, 5.03 PM, 5.05 PM, 5.07
  • 5.25 PM are grouped into one first level cluster and the second set of time stamps (5. 40 PM, 5.42 PM, 5.43 PM, 5.45 PM, 5.47 PM, 5.49 PM, 5.50 PM, 5. 53 PM, 5.55 PM, 5.57 PM, 6.00 PM, 6.01 PM, 6.03 PM, 6.05 PM) are grouped into another first level cluster.
  • the processor now considers the one first level cluster into one first- level sub-locations and the another first level cluster to another first-level sub locations. Therefore, the processor establishes a first level relationship between the two first-level sub-locations.
  • the two first-level sub-locations [0039] Further, the first set of time stamps (5 PM, 5.01 PM, 5.03 PM, 5.05 PM, 5.07 PM, 5.10 PM, 5.12 PM, 5.15 PM, 5.17 PM, 5.19 PM, 5.20 PM, 5.21 PM, 5.23 PM, 5.25 PM) are further grouped into 3 second level clusters.
  • the second level cluster- 1 includes 5 PM, 5.01 PM, 5.03 PM, 5.05 PM, 5.07 PM, 5.10 PM.
  • the second level cluster-2 includes 5.12 PM, 5.15 PM, 5.17 PM and the second level cluster-3 includes 5.19 PM, 5.20 PM, 5.21 PM, 5.23 PM, 5.25 PM.
  • the processor determines position for each of the second level clusters by associating a position co-ordinate to each of the 3 second level clusters. The determined position co-ordinates are stored in the reference map. Further these 3 second level clusters can be tagged by one or more users as“Diary products”,“Vegetables” and“payment” within the first-level sub location tagged“1 -floor”. The tagging of the -level sub-location can also be done by one or more users.
  • the second set of time stamps (5. 40 PM, 5.42 PM, 5.43 PM, 5.45 PM, 5.47 PM, 5.49 PM, 5.50 PM, 5. 53 PM, 5.55 PM, 5.57 PM, 6.00 PM, 6.01 PM, 6.03 PM, 6.05 PM) are further grouped into 3 second level clusters.
  • the second level cluster- 1 includes 5. 40 PM, 5.42 PM, 5.43 PM, 5.45 PM, 5.47 PM, 5.49 PM.
  • the second level cluster-2 includes 5.50 PM, 5. 53 PM, 5.55 PM, 5.57 and the second level cluster-3 includes 6.00 PM, 6.01 PM, 6.03 PM, 6.05 PM.
  • the processor determines position for each of the second level clusters by associating a position co ordinate to each of the 3 second level clusters. The determined position co-ordinates are stored in the reference map. Further these 3 second level clusters can be tagged by one or more users as“Entry”,“Stationary products” and“payment” within the second- level sub-location tagged“2-floor”.
  • the method presented in the flowchart of Figure 2 enables automatic configuration of position co-ordinates when the user enters an indoor space.
  • the position co-ordinates are determined based on the time stamps or time intervals where the user has moved around in the indoor space.
  • no trained data is being used which eliminates need for tedious training required for determining the floor map of the indoor space.
  • the interest of the user can be determined.
  • the method does not limit to first and second level relationships alone. There may further levels of granularity involved depending on indoor space.
  • ‘Adapted’ or‘arranged’ in the context of the instant disclosure, refers to the technical capability or the technical capacity of a component, in relation to which the term‘adapted’ or‘arranged’ is used, to carry out or executed a specified action or actions, upon the requirement of the specified action or actions to be carried out or executed.
  • the usage of the term‘adapted’ or‘arranged’ here is in reference with the normal technical capability or technical capacity of the component, imparted by the design or the structure or the composition of the component, and not in reference with any special or extraneous capability or capacity, beyond the scope of the normal technical capability or technical capacity. Therefore, there is a need to address this problem.

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

La présente invention concerne un procédé de configuration d'une pluralité de coordonnées de position destiné à un positionnement en intérieur. Le procédé consiste à récupérer une carte de référence d'un emplacement intérieur, à établir une relation de premier niveau entre une pluralité de sous-emplacements de premier niveau par rapport à l'emplacement marqué, à établir une relation de second niveau entre une pluralité de sous-emplacements de second niveau à l'intérieur de chaque sous-emplacement de la pluralité de sous-emplacements de premier niveau par le groupement de la pluralité de sous-emplacements de second niveau en au moins un groupe, à déterminer au moins une coordonnée de position en fonction du groupement et à mémoriser lesdites coordonnées de position dans la carte de référence afin de permettre le positionnement en intérieur. Ainsi, les coordonnées de position sont configurées automatiquement en temps réel sans avoir besoin d'un processus fastidieux d'obtention des données d'apprentissage.
PCT/EP2019/065737 2018-07-25 2019-06-14 Procédé de configuration d'une pluralité de coordonnées de position destiné à un positionnement en intérieur Ceased WO2020020535A1 (fr)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113784280A (zh) * 2021-07-28 2021-12-10 中国矿业大学 一种基于WiFi指纹的消防员室内定位方法
CN113784280B (zh) * 2021-07-28 2022-06-14 中国矿业大学 一种基于WiFi指纹的消防员室内定位方法

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