FR3086832A1 - METHOD FOR GEORGING WITH AUTOMATIC ADAPTATION OF DETECTION RANGE, COMPUTER PROGRAM, GEORGING MODULE AND RESIDENTIAL GATEWAY THEREFOR. - Google Patents

Abstract

The invention relates to a geolocation method, comprising triggering at least one action on detection of a crossing of a limit of a detection zone by mobile equipment (21). According to the invention, such a geotagging method is remarkable in that it comprises an adaptation (12) of a position of said limit of said detection zone (ZD) as a function of at least one contextual information. Thus, such a geo-tracking method is based on an automatic adaptation of the size of the detection zone according to a context, which makes it possible to improve its reliability and reactivity.

Description

Method of geo-location with automatic adaptation of detection range, computer program, geo-location module and associated residential gateway.

1. Field of the invention

The field of the invention is that of geo-location, also called in English "geofencing". More specifically, the invention relates to a geo-tracking technique which can find applications in fields as diverse as geomarketing, connected house, fleet management, etc.

2. Prior art and its drawbacks

Also called virtual guarding, geo-monitoring is a feature of a software program or an application allowing to define virtual geographic barriers. The software administrator can manually set these limits. When the device on which the software runs (generally a smart phone, in English "smartphone") crosses virtual barriers, by entering or leaving the detection zone delimited by these barriers, an alert is issued, or an action is triggered.

Geolocation is based on a geolocation system of mobile equipment, which most often relies on a satellite positioning system (in English GPS for "Global Positioning System", in French "system for global positioning"), or on a presence detection using radio frequency identification (RFID) tags. Geolocation can also define a geographic barrier from a satellite view; some geo-location applications therefore embed the Google Earth® application developed by Google® for this purpose. Some applications also define the virtual limits of the detection area based on longitude or latitude or from maps available on the global Internet.

Geolocation is used in many sectors. It finds, for example, applications in the field of vehicle fleet management, by allowing a fleet manager to receive an alert if a vehicle deviates from its route. In the area of human resource management, this technology can be used to ensure that an employee does not attempt to enter an unauthorized area.

Companies that lend mobile devices such as smartphones or tablets can also use geo-location to receive an alert if a loaned device leaves the predefined loan area and then lock its use remotely. The same principle applies to prisoners wearing electronic surveillance bracelets, which we can verify that they do not leave the perimeter in which they are authorized to operate.

Georeferencing also finds many applications in the field of home automation, also called in English "Smart Home": it is for example possible to detect the arrival of a user at his home to automatically activate the lighting of the house, or change the set temperature of smart thermostats. It is also possible to issue an alert when a child leaves the perimeter of the house.

Finally, in the field of marketing, geo-location is also increasingly used and bears the specific name of geomarketing. For example, it is possible to define a virtual barrier around a store. Thus, when a potential customer crosses the barrier, it is possible to send him a promotional offer or a mobile advertisement on his smartphone to encourage him to make a purchase.

These geo-location applications open up a vast horizon of new services to the user.

However, these applications suffer from a lack of reliability of the geolocation systems on which they are based.

Thus, the reliability of the GPS positioning of smartphones is relatively erratic, depending on the type of phone, the operating system it embeds, the GPS used, its geographic position, and various disturbances affecting the measurement of this positioning. . It therefore happens sporadically that the positioning measurement is vitiated by an error of several hundred meters over a short period.

This positioning error is likely to mislead geo-location applications, by causing false detections of virtual barrier crossings, which have the effect of causing unwanted actions to be triggered by these applications, and therefore of inducing discomfort. potential on the services offered to the user who owns the smartphone. For example, in the context of home automation applications, these false detections of crossing virtual barriers during the night period can trigger untimely sequences of successive actuations and extinctions of the lights in the house, including in the middle of the night, which can disturb the sleep of its inhabitants.

There is therefore a need for a geotagging technique having increased reliability compared to the techniques of the prior art, and which is less dependent on the vagaries of geolocation of mobile equipment. There is also a need for such a technique making it possible to offer a better quality of service to the user.

3. Statement of the invention

The invention responds to this need by proposing a geotagging method, comprising triggering at least one action on detection of a crossing of a limit of a detection zone by mobile equipment. According to the invention, such a geotagging method comprises an adaptation of a position of said limit of said detection zone as a function of at least one contextual information.

Thus, the invention is based on a completely new and inventive approach to the geo-location technique, which is based on an automatic adaptation of the size of the detection area according to a predefined context.

Indeed, to date, known geo-location applications use a fixed detection area. In other words, the virtual geographic barriers whose crossing is detected are positioned once and for all. Thus, by way of example, the application programming interfaces (or APIs for English “Application Programming Interface”) georeferencing proposed by Google® invite the user to indicate the size (called radius) of the detection area a only once during the initial configuration of the application. To assist the user, a size is recommended for the targeted application (for example 100m for a connected house application), but it is frozen once and for all for the user.

These prior art techniques therefore do not make it possible to adapt the size of the detection zone to a current context, and deprive themselves of a possibility of improving the reliability or the reactivity of the geo-location, depending on one or more several contextual information, which the present invention advantageously proposes to use.

Thus, such a geo-tracking method can analyze the current contextual information, and reduce a size of said detection zone, so as to increase a reactivity of said triggering of action, when it is determined that the context is favorable to a reduction of that size. Likewise, it can increase a size of said detection zone, so as to increase a reliability of said triggering of action, when it is determined that the context is favorable to an increase of this size.

This current context can be determined in several ways.

According to a first embodiment, the contextual information is hourly information. Thus, the time of day, or the day of the week, are taken into account to adapt the size of the detection zone, and thus to reinforce the reliability of the geo-tracking process. The context change rules (for example changes in time periods) can be predefined by the geo-location application or fixed by the user during a prior configuration phase.

According to another embodiment, such a geotagging method comprises a collection of data relating to said actions triggered in association with a location of said mobile equipment with respect to said detection zone, and a determination of said contextual information from said collected data.

Thus, the contextual information can be deduced by automatic learning (“machine learning” in English), as a function of the data previously collected during the operation of the georeferencing application, and in particular the knowledge of the user's habits, or the detection of erroneous crossings of the limit of the detection zone that triggered inaccurate and untimely actions. Taking this into account improves the reliability of the geo-location.

According to yet another aspect, such a geotagging method comprises receiving said contextual information from at least one external source. This external source can be the user himself, who can enter this contextual information through the interface of his mobile equipment; it can also be another communication or computer system, capable of transmitting contextual information complementary to the geo-location process (for example, a system of home automation motion sensors, which can inform of the probable presence of the user in the house: the geo-location process can then advantageously increase the size of the detection zone, to avoid false untimely detections from leaving the zone).

According to yet another aspect, such a geotagging method comprises a calculation of an error rate for triggering said actions and a determination of said contextual information as a function of said calculated error rate. Thus, the contextual information is determined continuously, according to the error rate observed by the geo-location process, which makes it possible for example to avoid the inconveniences linked to problems of oscillation of the positioning of the mobile equipment on the one hand and on the other side of the detection zone limit, by filtering.

According to yet another aspect, said contextual information comprises a plurality of contextual components to each of which is associated a weighting coefficient. Thus, contextual information can be obtained by combining the different approaches presented above (time rules, learning, external source, continuous consideration of the error rate), with or without prioritization, through the use of weighting coefficients.

The invention also relates to a computer program product comprising program code instructions for implementing a method as described above, when executed by a processor.

The invention also relates to a recording medium readable by a computer on which a computer program is recorded comprising program code instructions for the execution of the steps of the geo-tracking method according to the invention as described above. .

Such a recording medium can be any entity or device capable of storing the program. For example, the support may include a storage means, such as a ROM, for example a CD ROM or a microelectronic circuit ROM, or else a magnetic recording means, for example a USB key or a hard disk.

On the other hand, such a recording medium can be a transmissible medium such as an electrical or optical signal, which can be routed via an electrical or optical cable, by radio or by other means, so that the program of computer it contains is executable remotely. The program according to the invention can in particular be downloaded from a network, for example the Internet.

Alternatively, the recording medium can be an integrated circuit in which the program is incorporated, the circuit being adapted to execute or to be used in the execution of the aforementioned display control method.

The invention also relates to a geolocation module comprising:

means for detecting a crossing of a limit of a detection zone by mobile equipment;

means for triggering at least one action on detection of said crossing.

Such a geo-tracking module comprises a unit for adapting a position of said limit of said detection zone as a function of at least one contextual information. It can advantageously be embedded in domestic equipment, such as for example a residential gateway of a domestic communication network to which is able to connect at least one mobile equipment, and which controls a set of services of “smart home” type in the House.

The geolocation module, the residential gateway which integrates it and the aforementioned corresponding computer program have at least the same advantages as those conferred by the geolocation method according to the present invention. They combine the aforementioned technical characteristics presented in relation to the geo-location process in its various embodiments and aspects.

4. List of figures

Other objects, characteristics and advantages of the invention will appear more clearly on reading the following description, given by way of simple illustrative example, and not limiting, in relation to the figures, among which:

FIG. 1 illustrates in the form of a flowchart the main steps of the geo-location method according to an embodiment of the invention;

FIG. 2 presents a first exemplary embodiment of the geotagging method of FIG. 1, in which the adaptation of the size of the detection zone takes account of contextual hourly information;

FIG. 3 illustrates a second exemplary embodiment of the geolocation method of FIG. 1, in which the adaptation of the size of the detection zone takes account of contextual information deduced from learning data collected previously;

FIG. 4 presents in the form of a block diagram the hardware structure of a geo-location module according to an embodiment of the invention.

5. Detailed description of embodiments of the invention

The general principle of the invention is based on the dynamic adaptation of the size of the detection area of a geo-location application, as a function of one or more contextual information, so as to improve the reliability and the reactivity of this application. compared to the techniques of the prior art, in which the size of the detection zone is fixed.

We now present, in relation to the figures, embodiments of such a dynamic adaptation of the detection range of geo-location applications as a function of one or more context information.

In the following, we set out to describe examples of application of the invention in the context of a connected house, in which the geo-location process is implemented in a home automation environment. The invention is of course not limited to this type of application and can advantageously be used in any other geo-location context, such as geomarketing, vehicle fleet management, human resource management, etc.

As illustrated in FIG. 1, such a geolocation method comprises three main main steps:

a first step referenced 10, during which the scope of the detection zone Z _D of the geotagging process is initialized. This initialization can be carried out by manual entry by the user, or by predetermined configuration of the geo-location application, for example depending on the type of application targeted (ie 100m for a home automation application);

during a second step referenced 11, contextual information INFOctxt is determined, representative of a context of use of the geo-location application. This context of use can be determined in several ways:

o it can be predefined by the application, which indicates rules for changing context (for example, changes in time periods);

o it can be learned by the system on the basis of data previously collected during the operation of the application;

o it can be indicated by an external source, such as another computer system or the user himself;

o it can be determined continuously according to the error rate observed by the system;

o it can be determined by combining the previous approaches, with or without prioritization.

Finally, during a step referenced 12, the scope of the detection zone Z _D is adapted as a function of the contextual information determined during the previous step.

FIG. 2 illustrates a first example of a case of such adaptation of the range of the detection zone Z _D as a function of contextual information.

We consider an example of application in which it is necessary to determine whether or not the user is present at his home 20. The service concerned is for example a service for optimizing the energy consumption of housing 20, based on a reduction the set temperature of smart home thermostats, when it is determined that the user is absent. It is assumed that this determination of the presence of the user at his home 20 is made by GPS geolocation of his smart phone, or smartphone 21.

As illustrated by the crosses referenced 22i to 22 ₃ , the positioning of the smartphone 21, as determined by GPS measurement, can be flawed, and produce different measurement results, even if the smartphone 21 is not moved within the home 20. Thus, the positioning 22i obtained for the smartphone 21 confirms the presence of the user at his home 20. On the other hand, the positions 22 ₂ and 22 ₃ are both located outside the perimeter of the area of Z _D detection associated with the home 20.

These successive measurements 22i to 22 ₃ can result in the issuance of successive commands for increasing and reducing the set temperature of the smart thermostats, although the user has never left his home 20, which can s '' prove to be energy consuming, and not very comfortable for the user.

However, it can be considered that during the night period, the user is generally present at his home 20. It may therefore prove advantageous, during this night period of presence of the user (and therefore of his smart phone 21) to his home 20, to increase the range, or the radius, of the detection zone Z _D , during step 12 ADAPT. Z _D. This advantageously avoids the risks of location error of the smartphone 21 outside the detection zone Z _D , and therefore the false detections of crossing by the user of the limits of this detection zone Z _D. This minimizes untimely triggering of successive commands to increase or reduce the set temperature for heating the home 20. In fact, as illustrated in FIG. 2 in its right part, all the position measurements 22i to 22 ₃ of the smart phone 21 now indicate a presence within the perimeter of the detection zone Z _D , after adaptation of the limits of the latter.

This is made possible, thanks to an embodiment of the invention, by taking into account contextual information validating the presence of the user at his home 20.

This contextual information relating to the nightly presence of the user at his home 20 can be determined in multiple ways:

it can be established according to a time range configured by the user. For example, the user configures the parameters of the geo-location application to indicate that he is always present at his home 20 between midnight and six in the morning. In this time range, the scope of the detection zone Z _D is therefore widened, to avoid false detections when leaving the home;

it can be learned by the geo-location application, by analysis of the user's travel habits, and therefore by automatic learning;

it can be provided by the user via any means of communication, or by inputting on his smart phone 21. Thus, the user signals his presence at his home 20, which increases the radius of the area of Z _D detection;

it can be provided by another computer system in the house, for example a system of movement sensors which detected the presence of the user at his home and indicated it to the geo-location application, or even the residential gateway the home communication network which detected that the smartphone 21 was connected to it via Wi-Fi®;

it can also be inferred by the application of georeferencing, according to an evaluated error rate, or the detection of strange and unlikely behavior, such as rapid and successive entries and exits from the detection zone, according to an oscillation movement not very representative of potential human behavior, and more likely associated with a repeated measurement error.

The increase in the range of the detection zone Z _D , in this context of the nocturnal presence of the user at his home 20, advantageously makes it possible to improve the reliability of the geo-location application, by reducing the number of detections of false crossings of the zone limit Z _D , and therefore the number of untimely triggering of associated actions.

We now present, in relation to FIG. 3, another example of geotagging home automation application which can advantageously benefit from the principle of dynamic adaptation of the range of the detection zone Z _D as a function of contextual information.

We now consider the case where one wishes to reliably and reactively detect the arrival of a user at his home 20, to activate the lighting of all or part of the house.

The particular context is that of a movement of the user, by car, as symbolized by the two horizontal arrows from right to left. It is assumed that this movement corresponds to traffic in the user's car on the street bordering his home 20.

In the case of the left part of FIG. 3, the detection zone Z _D has a radius large enough for the smartphone 21 to be detected as having crossed the limit of the detection zone Z _D when the user is traveling in car on his street. This false detection can lead to untimely actuation of the home switches, when the user is not actually present at his home 20.

In this particular example, learning the habits of the user can make it possible to determine that he is driving every evening in front of his home, for example to go and buy bread, in the half hour preceding his return home. During a step referenced 12 for adapting the position of the limits of the detection zone Z _D , the radius or range of this zone Z _D is then reduced, in order to avoid turning on the lights of the home when the user is content to drive in front of his home 20. This increases the responsiveness of the geo-location process according to this embodiment of the invention. In fact, as illustrated in the right-hand part of the figure, the smartphone 21 no longer crosses the limits of the detection zone Z _D when the user's vehicle passes on its street.

Note that the mobile equipment used for geo-monitoring is not limited to a smart phone or smartphone: it can also be a tablet, a connected watch, or more generally any type of connected object able to be geolocated and to move.

We now present, in relation to FIG. 4, the hardware structure of a geo-tracking module according to an embodiment of the invention, for example embedded in mobile equipment of the smartphone type, or remote in the residential gateway of a home network. Such a geo-tracking module notably comprises a unit for adapting a position of the limit of the detection zone as a function of at least one contextual information item.

The term unit can correspond as well to a software component as to a hardware component or a set of hardware and software components, a software component corresponding itself to one or more computer programs or subroutines or more generally to any element of a program capable of implementing a function or a set of functions.

The geolocation module 40 of FIG. 4 comprises a processor 41, an adaptation unit 42, an input device 43, an output device 44 and an interface unit 45, which are connected to each other by a bus 46. Of course, the constituent elements of the geo-location module 40 can be connected to each other by any other type of connection, in place of the bus 46. Such a geo-location module 40 is for example embedded in a residential gateway , a computer, or equipment for managing a fleet of vehicles.

The processor 41 controls the operation of the geo-tracking module 40. The adaptation unit 42 stores at least one computer program, intended to be executed by the processor 41, and various data, including the contextual information used for the adaptation of the size of the detection zone, as well as various parameters necessary for the operations performed by the processor 41. The adaptation unit 42 may in particular contain a memory, intended to store the data collected during the operation of the geo-tracking module 40, the context change rules, the initial or current size of the detection zone, as well as possible weighting coefficients to be assigned to the different components of the contextual information.

The processor 41 can be produced in hardware, software, or in the form of a hardware and software combination. For example, the processor 41 may be designed in the form of a dedicated hardware component, such as an integrated circuit, or of a programmable processing unit of the CPU type ("Central Processing Unit" for central processing unit) which runs a computer program stored in memory.

The adaptation unit 42 can take any form suitable for storing a program or computer-readable data, for example a computer-readable storage means such as a semiconductor memory, or a recording means. magnetic, optical or magneto-optical loaded in a read / write accessible unit.

The program causes the processor 41 to perform various actions, including:

the determination of at least one contextual information INFO _CT xt · This determination may in particular involve the calculation of a rate of operating errors, or the consultation of a table for memorizing contextual reference rules;

adapting the size of the detection zone Z _D as a function of the contextual information INFO _CT xt;

the triggering of one or more actions, as a function of the detection of crossing of the limits of the detection zone Z _D by mobile equipment of the user. Such a triggering can take the form of an emission of commands to one or more pieces of equipment connected to the tracking module 40 by means of the interface unit 45.

The input device 43 can take the form of a keyboard, a mouse, or any other form allowing a user to enter contextual information. The output device 44 can take the form of a screen for monitoring the contextual information entered by the user or a screen for viewing the position of a mobile device of use with respect to the limits of the area of detection.

The interface unit 45 provides an interface between the geolocation module 40 and an external device, such as the residential gateway, or a set of connected objects loT of the house (intelligent thermostats, switches, etc.) for example. The interface unit 45 can be wired or wirelessly connected to the external device (for example, in Wi-Fi® connection with the HGW residential gateway, but in electrical cable connection with an intelligent thermostat or a switch) .

Although a single processor 41 has been shown in FIG. 4, this processor can comprise different modules and units, implementing the functions of the geo-tracking module 40, according to the embodiments of the present patent application, such as:

A unit for detecting the crossing of a limit of a detection zone by mobile equipment, cooperating with a module for geolocation of mobile equipment;

A unit for triggering at least one action on detection of said crossing comprising, for example, a module for transmitting commands to remote equipment;

a unit for adapting a position of said limit of said detection zone as a function of at least one contextual item of information.

These different modules and units can also be embedded in several processors 41 communicating and cooperating with each other.

FIG. 4 illustrates only one particular way, among several possible, of producing the geo-location module 40, so that it performs the steps of the method detailed above, in relation to FIG. 1. In fact, these steps can be carried out indifferently on a reprogrammable computing machine (a PC computer, a DSP processor or a microcontroller) executing a program comprising a sequence of instructions, or on a dedicated computing machine (for example a set of logic gates such as an FPGA or an ASIC , or any other hardware module).

In the case where the geolocation module 40 is produced with a reprogrammable calculation machine, the corresponding program (that is to say the sequence of instructions) may be stored in a removable storage medium (such as for example a diskette, CDROM or DVD-ROM) or not, this storage medium being partially or totally readable by a computer or a processor.

Claims (11)

1. A geo-tracking method, comprising triggering at least one action on detection of a crossing of a limit of a detection zone (Z _D ) by mobile equipment (21), characterized in that it comprises an adaptation (12) of a position of said limit of said detection zone as a function of at least one contextual information (INFO _CT xt) · 2. Georeferencing method according to claim 1, characterized in that said adaptation is capable of reducing a size of said detection zone, so as to increase a reactivity of said triggering of action. 3. Georeferencing method according to any one of claims 1 and 2, characterized in that said adaptation is capable of increasing the size of said detection zone, so as to increase the reliability of said triggering of action. 4. Georeferencing method according to any one of claims 1 to 3, characterized in that said contextual information is time information. 5. Georeferencing method according to any one of claims 1 to 4, characterized in that it comprises a collection of data relating to said actions triggered in association with a location of said mobile equipment with respect to said detection zone, and a determination said contextual information from said collected data. 6. Georeferencing method according to any one of claims 1 to 5, characterized in that it comprises a reception of said contextual information coming from at least one external source. 7. Georeferencing method according to any one of claims 1 to 6, characterized in that it comprises a calculation of an error rate of triggering of said actions and a determination of said contextual information as a function of said error rate calculated. 8. Georeferencing method according to any one of claims 1 to 7, characterized in that said contextual information comprises a plurality of contextual components to each of which is associated a weighting coefficient. 9. A computer program product comprising program code instructions for implementing a method according to any one of claims 1 to 8, when executed by a processor. 10. Geolocation module comprising: means for detecting the crossing of a limit of a detection zone by mobile equipment; means for triggering at least one action on detection of said crossing; characterized in that said geo-tracking module comprises a unit for adapting a position of said limit of said detection zone as a function of at least one contextual information. 11. Residential gateway of a home communication network to which it is able to connect at least one mobile device, characterized in that it comprises a geo-tracking module according to claim 10.