Method for locating indoors

Abstract

The invention relates to a method for locating a terminal moving in an interior space, comprising at least first and second rooms, characterised in that it implements what follows in an indoor locating module (MLI): - receiving E201 first, respectively second, data from a first, respectively second, sensor located in the first, respectively second, room, said first and second sensors being non-dedicated to location and capturing the same type of data, - receiving E202 data from the terminal, said data being of the same type as the first and second data, - comparing E203 the data from the terminal to said first and second, - depending on the result of the comparison, determining E204 the room, among the first and second rooms, in which the terminal is located.

Description

Indoor localization process Field of invention

[0001] This invention relates generally to the field of location technologies.

[0002] More specifically, the invention relates to indoor localization of a terminal by receiving data from sensors associated with rooms and data from the terminal to be located. Prior art

[0003] People tracking is a necessity for many services and has been the subject of numerous innovations to improve its quality. In this area, a distinction must be made between outdoor and indoor tracking, which present different challenges.

[0004] Outdoor geolocation is made widely accessible due to the GPS Global Positioning System).

[0005] Indoor geolocation cannot use GPS, which is inoperative inside buildings, thus requiring the development of different strategies to enable sufficiently precise location on the scale of the dimensions of the buildings (to the nearest meter or room by room), but also at the level of the possible floors of these buildings.

[0006] The first strategy is the use of Wi-Fi (Wireless Fidelity), which is widely available in an indoor infrastructure. However, the link between Wi-Fi and localization requires a preliminary learning phase, which consists of creating a correspondence between the Wi-Fi RSSI (Received Signal Strength Indication) level and the position at which this RSSI is evaluated. The main drawback of this technique is that it requires a large number of recordings in a large indoor environment, and the calibration of an indoor Wi-Fi localization service can be considered excessively long (the desired localization accuracy depends in particular on the number and mesh density of the recordings).

[0007] In the literature, other indoor location systems are based on technologies such as Bluetooth or UWB (ultra wideband), where beacons are positioned at strategic locations in the environment and allow, when the smartphone passes nearby, to quickly deduce the location. The disadvantage of this type of approach is the purchase of a dedicated location infrastructure (Bluetooth / UWB beacons).

[0008] Another solution is to use security devices such as presence detectors or surveillance cameras. However, these solutions have drawbacks. Presence detectors are certainly capable of identifying the presence of an individual in a room. However, they are not capable of identifying the identity of the individual in question. On the other hand, advanced surveillance systems such as cameras associated with facial recognition applications or other biometric data are capable of identifying individuals and locating them (by associating data relating to the identified person and the position of the camera that filmed them) but only by using sensitive personal information. Indeed, this type of device requires the prior creation of, as well as access to, personal databases (face, biometric data, etc.).

[0009] Subject matter and summary of the invention

[0010] One of the aims of the invention is to remedy at least one of the drawbacks highlighted by the aforementioned state of the art by proposing a method for locating indoors a mobile terminal in accordance with the invention which will be described below.

[0011] To this end, the present invention relates to a method for locating a terminal moving in an indoor space comprising at least first and second rooms, characterized in that it implements the following at the level of an indoor location module: - receiving first, respectively second, data from a first, respectively second, sensor located in the first, respectively second, room, said first and second sensors being not dedicated to location and capturing the same type of data, - receiving data from the terminal, said data being of the same type as the first and second data, - comparing the data from the terminal with said first and second, - depending on the result of the comparison, determining the room, among the first and second rooms, in which the terminal is located.

[0012] The term "type" refers to the subject / parameter quantified or qualified by the data, for example, it could be data relating to temperature, noise level, sound capture, movement, etc.

[0013] According to the invention, the first and second data, as well as the data from the terminal, are not limited to the same type and can be of several same types. Thus, the indoor location module can receive: - several same types of first, respectively second data at a time (for example first and second temperature and brightness data, first and second temperature, brightness and CO2 data, etc.), - and several same types of data from the terminal (for example temperature and brightness, temperature, brightness and CO2 level, etc.).

[0014] The invention offers the advantage of not requiring a dedicated indoor location installation but extrapolates the location from data generated by pre-existing installations (sensors and / or combinations of sensors). In doing so, the invention makes it possible to locate a terminal on a room scale and between different floors where appropriate.

[0015] The invention offers the advantage of allowing individualized localization of the terminal, unlike security devices using movement or presence detectors which only generate information relating to the presence of an unidentified person in a room.

[0016] Because it requires the reception of data from the terminal to be located, the process can easily be made conditional on the agreement of the user of said terminal (via opt-in authorization for example), which limits the risks of location without the knowledge of the user of the terminal.

[0017] According to a particular embodiment of the indoor location method, the comparison of said data from the terminal with said first and second data includes an identification of discriminating data for location.

[0018] Here, by "identification of discriminatory data" we mean an analysis of the data received from the sensors and the terminal using methods such as, for example, the following types: - clustering, - Boolean analysis, - polynomial reduction, - least squares, - nearest neighbors, - based on the use of neural networks, or any other method known to those skilled in the art.

[0019] This embodiment offers the advantage of making the most of all the sensors pre-existing the implementation of the location method and of increasing the level of confidence in the location of the terminal.

[0020] These methods can be used, in particular, to distinguish between relevant data types and those that do not provide usable information for indoor location.

[0021] For example: - similar temperature data in all rooms cannot be used to locate the mobile terminal, - conversely, the Boolean analysis of a set of equal data types in pairs of rooms (equal temperature in two rooms (A, B), equal brightness in two rooms (B, C), equal decibel measurement in two rooms (C, A) will make it possible to identify a single room corresponding to the combination of data received by the terminal.

[0022] According to one embodiment of the indoor location method, said data from the terminal, as well as the first and second data, are environmental data.

[0023] “Environmental data” means all data relating to the biophysical and human environment such as, but not limited to, those relating to: air (in particular greenhouse gases), water, soil, land, flora and fauna, habitat, energy, noise, waste, contaminants, pollutant emissions, brightness / sunshine, etc.

[0024] This embodiment offers the advantage of allowing the location of a terminal without resorting to sensitive personal data such as biometric data (voice or face) as may be the case with existing surveillance and recognition devices: the environmental data relates to the space where the terminal / user to be located is located and not to the terminal / user itself.

[0025] This embodiment makes it possible to take advantage of pre-existing installations: environmental data is generally monitored by home automation installations.

[0026] According to another embodiment of the indoor localization method, the comparison of said data from the terminal to said first and second includes any of the following processing: - Video recognition of data specific to the first or second room, - Audio recognition of data specific to the first or second room.

[0027] Here, the term "specific data" refers to non-measurable / quantifiable visual or audio elements / artifacts (e.g., a wallpaper pattern, a pattern on the floor, the sound of a clock, or any other image or sonogram, etc.).

[0028] This embodiment has the advantage of multiplying the number of sensors that can be used for localization, in particular sensors such as cameras and microphones already present in the rooms where localization takes place.

[0029] Such a video or audio recognition operation in the step of comparing data from the terminal and the sensors offers the advantage of locating the terminal based in particular on similarities of specific data that cannot be measured / quantified and are captured both by certain sensors placed in the rooms and by the terminal to be located (for example: a wallpaper pattern, a pattern on the floor, the sound of a clock, etc.), which results in increasing the robustness and the confidence rate in the indoor location process.

[0030] The various embodiments or features mentioned above may be added independently or in combination with each other to the indoor location method as defined above.

[0031] The invention also relates to a device for indoor localization of a terminal moving in an interior space comprising at least first and second rooms, characterized in that it is configured to: - receive first, respectively second, data from a first, respectively second, sensor located in the first, respectively second, room, said first and second sensors being not dedicated to localization and capturing the same type of data, - receive data from the terminal, said data being of the same type as the first and second data, - compare the data from the terminal to said first and second, - depending on the result of the comparison, determine the room, among the first and second rooms, in which the terminal is located.

[0032] Such an indoor location device is in particular capable of implementing the aforementioned indoor location method.

[0033] The invention also relates to a computer program comprising instructions for implementing the indoor location method according to the invention, according to any one of the particular embodiments described above, when said program is executed by a processor.

[0034] Such instructions may be stored permanently in a non-transitory memory medium of the indoor location device implementing the indoor location method according to the invention.

[0035] This program may use any programming language, and may be in the form of source code, object code, or code intermediate between source code and object code, such as in a partially compiled form, or in any other desirable form.

[0036] The invention also relates to a recording medium or information medium readable by a computer, and comprising instructions of a computer program as mentioned above.

[0037] The recording medium may be any entity or device capable of storing the program. For example, the medium may include a storage medium, such as a ROM, for example a CD-ROM or a microelectronic circuit ROM, or a magnetic recording medium, for example a mobile medium, a hard disk, a USB key or an SSD.

[0038] On the other hand, the recording medium may be a transmissible medium such as an electrical or optical signal, which may be conveyed via an electrical or optical cable, by radio or by other means, so that the computer program contained therein is remotely executable. The program according to the invention may in particular be downloaded over a network, for example an Internet-type network.

[0039] Alternatively, the recording medium may be an integrated circuit in which the program is incorporated, the circuit being adapted to perform or to be used in performing the aforementioned indoor location method.

[0040] According to an exemplary embodiment, the present technique is implemented by means of software and / or hardware components. In this regard, the term “device” or “module” may correspond in this document to a software component, a hardware component or a set of hardware and software components.

[0041] Other characteristics and advantages will appear on reading particular embodiments of the invention, given as illustrative and non-limiting examples, and the appended drawings, among which:

[0042] It represents an example of architecture in which the indoor localization method is implemented,

[0043] Describes an embodiment of the indoor localization method,

[0044] Describes an example of comparing data received from sensors and the terminal,

[0045] Describes another example of comparing data received from sensors and the terminal,

[0046] Describes an embodiment of the indoor localization method in which the comparison of the data includes a video or audio recognition step,

[0047] Describes an example indoor location device in one embodiment of the invention. Detailed description

[0048] Description of an example architecture in which the indoor localization method is implemented

[0049] With reference to the is described an example of architecture in which the indoor localization method is implemented. This architecture comprises:- an interior space of at least two rooms respectively P1 and P2,- at least two sensors C p 1 and C p 2placed respectively in rooms P1 and P2,- a terminal T equipped with at least one sensor C T1, for example a smartphone, a tablet or a dedicated terminal, - an indoor location module MLI, which, depending on the embodiments, can be integrated into the terminal T, into a sensor management unit (not shown) or constitute an independent third-party terminal.

[0050] The respective positions of the C sensors p1 etc p2 within the P rooms 1et P2sont connues du module de localisation en intérieur. Selon les modes de réalisation, ces positions peuvent être transmises par un module de gestion des capteurs (non représenté), par les capteurs ou indiquées préalablement au module de localisation en intérieur.

[0051] C sensors p1 etc p2 etc T 1 are connected so that they can send data D C P 1, D C P 2nd and D CT 1 to the MLI module. Depending on the embodiments, this connection can be based on a wired or wireless connection (for example, Wi-Fi, Bluetooth, etc.). The types of connections can be heterogeneous and vary depending on the sensors.

[0052] Data D C P 1, D C P 2nd and D CT1 are of the same type: depending on the embodiments, it can be a question of measuring brightness, CO2, sound capture, etc.

[0053] According to the embodiments, when there is more than one type of sensor, the number and types of sensors present in the rooms may vary from one room to another. However, each of the types of sensors must be present in the terminal T.

[0054] Examples: - in a particular architecture, the method is implemented in a space composed of two rooms, each being equipped with a sensor of the same type, for example a thermometer, so as to locate a dedicated terminal, itself equipped with a thermometer, - in another particular architecture, the method is implemented in a space composed of three rooms A, B, C, respectively equipped with the following sensors: -- room A: a thermometer, a CO2 detector, a sound level meter, -- room B: a thermometer, a lux meter, -- room C: a lux meter, a CO2 detector, a sound level meter, so as to locate a smartphone equipped with a thermometer, a CO2 detector, a sound level meter and a lux meter.

[0055] Description of the main actions implemented in the indoor localization process

[0056] La represents the steps implemented by the indoor localization method, in a particular embodiment of the invention taking place within an architecture similar to that described in.

[0057] The process starts at E201 when the indoor location module MLI receives data D C P 1, D C P 2 of the same type coming respectively from at least two sensors C P 1, C P 2.

[0058] According to other embodiments, the indoor location module MLI receives data D C n dektypes, coming from sensors placed in a number of rooms, where n, k and p are greater than 1.

[0059] According to other embodiments, the indoor location module MLI receives data from the sensors at a predetermined fixed frequency or when the latter detect a change in the value of the captured data greater than a predefined threshold (for example, in the case of a variation in brightness of more than 20 Lux or in temperature of more than 2 degrees Celsius, etc.).

[0060] In E202, the indoor location module receives Dc data T 1 from terminal T and of the same type as data D C T 1, D C T 2.

[0061] According to other embodiments, the indoor location module MLI receives data D CT n from the terminal and generated by sensors associated with said terminal and whose types cover those of the sensors placed in the rooms of the space where the indoor location process is implemented.

[0062] In E203, all data received by the indoor location module are compared type by type.

[0063] Depending on the embodiments, the data can be filtered in order to identify significant / discriminating data presenting different values ​​or interpretations between them.

[0064] For example: - if all the temperature data received by the MLI module are similar or sufficiently close according to predefined sensitivity criteria (for example + / - 1 or + / -2 degrees Celsius), then the data are not retained for the rest of the comparison; - conversely, if the data from sensors placed in different rooms present significant differences, then the data are retained for the rest of the comparison.

[0065] The methods of comparison between each data vary according to the implementation methods. Examples include, but are not limited to, the following methods: - clustering, - least squares, - nearest neighbors, - based on the use of neural networks, -…

[0066] After comparing the data, the indoor location module determines in E204 the location of terminal T in one of the rooms.

[0067] If, after comparing the data, the indoor location module cannot determine the location of terminal T in one of the rooms, the process is not successful, otherwise the location of terminal T is determined.

[0068] According to other embodiments, if, at the end of the comparison of the data, the indoor location module does not make it possible to determine the location of the terminal T to the nearest room, the indoor location module determines an approximate location, for example by excluding the rooms for which the data received from their respective sensors do not correspond to those received from the terminal, or by restricting the location of the terminal to the rooms for which the data received from their sensors correspond to those received from the terminal.

[0069] According to other embodiments, the location of the terminal T can be sent to other modules, such as a sensor management module (not shown in the figure) or any other module or terminal. The data relating to this indoor location can also be associated with a confidence coefficient in this data.

[0070] Here, "data relating to this location or location data" means indoor location information. Depending on the embodiments, this may be the name / code of the part P1 and / or P2 or a particular reference specific to a home automation system not shown in the figure.

[0071] For example: - a confidence coefficient of 1 corresponds to total certainty of the localization process in the terminal's localization data, - a confidence coefficient of 0.5 means that the process estimates that the localization is 50% sure (the terminal is in the room) and 50% false (the terminal is in another room).

[0072] According to the possible embodiments, a confidence coefficient lower than a predefined threshold leads to the indoor localization method not being successful.

[0073] Two examples of implementations of methods for processing data received from sensors and the terminal are illustrated in enet.

[0074] Example of comparison of data received from sensors and the terminal.

[0075] Describes an example of a method for processing and comparing data received from the sensors and the terminal, in the case of an architecture similar to that defined in where:- the space is composed of 3 rooms: P1, P2, P3,-- each room is equipped with a thermometer C1 and a luxmeter C2 measuring respectively the temperature and the brightness at three different times, noted instants t = {1,2,3},- the terminal T to be located indoors is equipped with a thermometer and a luxmeter measuring the temperature and the brightness at a time corresponding to the time when the terminal is located,- during reception steps similar respectively to E201 and E202 as described in, the indoor location module MLI receives respectively pairs of data:-- D t=1 {C1 P1 , C2 P1}, D t=2 {C1 P1 , C2 P1} and D t=3 {C1 P1 , C2 P1} C1 sensors P1 (thermometer) and C2 P1(luxmeter) of room P1,-- D t=1 {C1 P2 , C2 P2}, D t=2 {C1 P2 , C2 P2} and D t=3 {C1 P2 , C2 P2} C1 sensors P2 (thermometer) and C2 P2 (luxmeter) of room P2,-- D t=1 {C1 P3 , C2 P3}, D t=2 {C1 P3 , C2 P3} and D t=3 {C1 P3 , C2 P3} C1 sensors P3 (thermometer) and C2 P3 (luxmeter) of part P3,-- D t=x {C1 T , C2 T} C1 sensors T (thermometer) and C2 T (luxmeter) of terminal T.

[0076] Analyzing data pairs within a two-dimensional space allows us to calculate 3 clusters where each cluster corresponds to a part. This analysis allows us to obtain a mathematical "boundary" between the different parts, in the vector space of the sensor measurements associated with each part.

[0077] The analysis of the data from the mobile terminal then makes it possible to determine which of the 3 clusters contains this data, here the cluster corresponding to the room P3, and to subsequently, during a step of determining the location of the terminal, similar to the step E204 described in, locate the terminal T in the room P3.

[0078] The quality of localization increases with the number of sensors of different types within the rooms: the more varied the types of measurements (brightness, temperature, humidity, CO2, etc.), the more the positioning of the mobile terminal can be distinguished with a high confidence rate.

[0079] Another example of comparing data received from sensors and the terminal.

[0080] This presents another example of data comparison implemented in a similar architecture to that described in but where the data value and the result of the comparison are different.

[0081] In this example, the analysis of data received from sensors placed in the rooms allows the creation of 3 clusters similar to the.

[0082] However, in this example, the analysis of the data from the mobile terminal does not allow the said data from the terminal to belong with sufficient confidence to one of the clusters in particular and the localization process is not successful.

[0083] According to other conceivable embodiments, the terminal T is located by default in the room P3 because the data cluster associated with the room P3 is the one which has the closest proximity to the data received from the terminal. According to the embodiments, the level of confidence in the terminal location is associated with the indoor location data.

[0084] Description of an embodiment of the indoor localization method in which the comparison of the data includes a video or audio recognition step

[0085] Describes an embodiment implemented in an architecture similar to that described in where the sensors C P1 , C P2 etc T are video cameras or microphones.

[0086] Steps E401 and E402 are similar to steps E201 and E202 of the. However, here the data received by the indoor location module cannot be considered as measurements (sound, brightness, humidity, etc.) but as audio and / or video recordings.

[0087] Example 1: The data received by the indoor location module is video content captured / captured by surveillance cameras C P1 , C P2 and by camera C T from terminal T.

[0088] Example 2: The data received by the indoor location module is audio content captured by connected assistants C P1 , C P2 equipped with microphones and by microphone C T from terminal T.

[0089] The indoor location module compares in E403 the data from the sensors placed in the rooms and from the terminal T by including video or audio processing aimed at extracting information from the audio and / or video recordings received during steps E401 and E402.

[0090] The extracted information may vary depending on the embodiments and the data received from the sensors. This may involve, for example:- pattern recognition (e.g. wallpaper patterns, floor patterns, etc.)- recognition of specific objects (e.g. paintings, sculptures, etc.)- recognition of audio content (e.g. a noise, specific music, etc.),- any other types of data from audio / video processing known to those skilled in the art.

[0091] Example 1: The indoor localization module performs in E403 a shape / pattern analysis and identifies patterns (e.g. patterns of wallpaper, tiles, etc.) among the received video content.

[0092] Example 2: The indoor localization module performs a sound analysis in E403 and identifies a regular noise / sound (e.g.: noise of an aquarium pump, noise of a clock, etc.) among the audio content received.

[0093] The indoor localization module continues the comparison step E403 by matching the information relating to the presence or absence of the recognized video or audio elements within the different recordings received.

[0094] In the case of example 1 above, the indoor location module compares the patterns identified in the video content received from rooms P1, P2 and from terminal T and detects the presence of similar patterns only in the video content received from a camera located in one of rooms P1, P2 and in the video content received from terminal T.

[0095] In the case of example 2 above, the indoor location module compares the noises / sounds identified in the audio content received from rooms P1, P2 and from terminal T and detects the presence of similar noises / sounds both in the audio content received from a microphone associated with one of rooms P1, P2 and in the audio content received from terminal T.

[0096] The indoor location module determines in E404 the location of the terminal T in a similar manner to step E204 described in.

[0097] Description of an indoor location device in one embodiment of the invention

[0098] This presents the simplified structure of an indoor MLI location device or module corresponding to a particular embodiment of the invention implemented in an architecture as illustrated in.

[0099] Such a device comprises, according to the invention, an E / R communication module adapted to receive and transmit information from or to the terminal T or the sensors placed in the at least two rooms P1 and P2.

[0100] According to a particular embodiment of the invention, the actions executed by the MLI device, within the framework of the implementation of the indoor localization method of the present invention, are implemented by instructions of a computer program PG. For this, the MLI module has the conventional architecture of a computer and notably comprises a memory MEM, a processing unit UTR, equipped for example with a processor PROC, and controlled by the computer program PG stored in memory MEM.The computer program PG comprises instructions for implementing the steps of the indoor location method, in particular the aforementioned actions: - receiving first, respectively second, data from a first, respectively second, sensor located in the first, respectively second, room, said first and second sensors being not dedicated to location and capturing the same type of data, - receiving data from the terminal, said data being of the same type as the first and second data, - comparing the data from the terminal with said first and second, - depending on the result of the comparison, determining the room, among the first and second rooms, in which the terminal is located.

Claims

Method for locating a terminal moving in an indoor space comprising at least first and second rooms, characterized in that it implements the following at the level of an indoor location module (ILM): - receiving (E201) first, respectively second, data from a first, respectively second, sensor located in the first, respectively second, room, said first and second sensors being not dedicated to location and capturing the same type of data, - receiving (E202) data from the terminal, said data being of the same type as the first and second data, - comparing (E203) the data from the terminal with said first and second, - depending on the result of the comparison, determining (E204) the room, among the first and second rooms, in which the terminal is located. An indoor localization method according to claim 1, wherein said comparison of said data from the terminal to said first and second data includes an identification of discriminatory data for localization. Indoor localization method according to claim 1 or 2, wherein said data from the terminal, as well as the first and second data, are environmental data. An indoor location method according to claim 1 or 2, wherein the comparison of said data from the terminal to said first and second includes any of the following processing: Video recognition of data specific to the first or second room, Audio recognition of data specific to the first or second room. Device (MLI) for indoor location of a terminal moving in an interior space comprising at least first and second rooms, characterized in that it is configured to:- receive first, respectively second, data from a first, respectively second, sensor located in the first, respectively second, room, said first and second sensors being not dedicated to location and capturing the same type of data,- receive data from the terminal, said data being of the same type as the first and second data,- compare the data from the terminal to said first and second,- depending on the result of the comparison, determine the room, among the first and second rooms, in which the terminal is located. A computer program comprising program code instructions for implementing the indoor location method according to any one of claims 1 to 4, when executed on a computer. Computer-readable information medium comprising instructions of a computer program for implementing the indoor location method according to any one of claims 1 to 4.

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