Claims:1. A system (10) to determine a real time position of an entity (20) in an indoor facility comprising:
a tracking device (30) coupled to the entity (20) and configured to generate a received signal strength indicator (RSSI) data;
a plurality of sensors (40) located in the indoor facility and configured to sense the received signal strength indicator (RSSI) data received from the tracking device;
a processor (50) operatively coupled to the plurality of sensors (40) and configured to:
collect the received signal strength indicator (RSSI) data corresponding to each of the plurality of sensors to compose a data frame;
filter noise from the data frame using a filtering technique;
identify a plurality of collisions of the received signal strength indicator (RSSI) data corresponding to each of the plurality of sensors (40);
resolve the plurality of collisions based on a resolving technique selected from a set of techniques;
calculate a resulting distance using a filtered data frame;
determine a positional logic based on the resulting distance; and
calculate the real time position of the entity based on a determined positional logic.
2. The system (10) as claimed in claim 1, wherein the entity (20) comprises an individual or an object.
3. The system (10) as claimed in claim 1, wherein the tracking device (30) comprises a Bluetooth low energy (BLE) beacon transmitter.
4. The system (10) as claimed in claim 1, wherein the plurality of sensors (40) comprises a Bluetooth low energy (BLE) reader.
5. The system (10) as claimed in claim 1, wherein the plurality of sensors (40) comprises one or more standalone sensors and one or more clustered sensors.
6. The system (10) as claimed in claim 1, wherein the processor (50) is located on a cloud-based server platform.
7. The system (10) as claimed in claim 1, wherein the processor (50) is located on an on premise local server.
8. The system (10) as claimed in claim 1, wherein the positional logic comprises a logic to select a trilateration technique or a presence detection technique.
9. A method (200) to determine a real time position of an entity in an indoor facility comprising:
generating, by a tracking device, a received signal strength indicator (RSSI) data; (210)
collecting, by a processor, the received signal strength indicator (RSSI) data corresponding to each of a plurality of sensors to compose a data frame; (220)
filtering, by the processor, noise from the data frame using a filtering technique; (230)
identifying, by the processor, a plurality of collisions of the received signal strength indicator (RSSI) data corresponding to each of the plurality of sensors; (240)
resolving, by the processor, the plurality of collisions based on a resolving technique selected from a set of techniques; (250)
calculating, by the processor, a resulting distance using a filtered data frame; (260)
determining, by the processor, a positional logic based on the resulting distance; (270) and
calculating, by the processor, the real time position of the entity based on a determined positional logic. (280)
10. The method (200) as claimed in claim 9, wherein generating, by the tracking device, the received signal strength indicator (RSSI) data comprises generating the received signal strength indicator (RSSI) data at a predefined frequency.
11. The method (200) as claimed in claim 9, wherein calculating, by the processor, the resulting distance using the filtered data frame comprises calculating the resulting distance by collecting a plurality of samples of the filtered data frame.
12. The method (200) as claimed in claim 9, wherein calculating, by the processor, the resulting distance using the filtered data frame comprises calculating the resulting distance by inverting the filtered data frame.
13. The method (200) as claimed in claim 9, wherein determining, by the processor, a positional logic based on the resulting distance comprises determining a logic to select a trilateration technique or a presence detection technique based on the resulting distance.
, Description:FIELD OF INVENTION
[0001] Embodiments of a present disclosure relate to locating users or terminals and more particularly to a system and a method for determining an indoor position of an entity.
BACKGROUND
[0002] Indoor positioning offers the possibility of locating an individual or an asset inside of a facility such as a building or a place. The indoor positioning may be used for various facility applications such as a security system, a way finding, and/or occupancy detection. Indoor location may be of particular use in a facility where global positioning systems (GPS) are denied or unavailable due to restriction on use of mobile devices, or a facility having multiple floors, where GPS signals overlap. With the advancement of technology, various methods and systems have been utilized for determining an indoor position of the individual or the asset.
[0003] Present approaches may use Radio-frequency identification (RFID), Beacons and Ultra-wide band (UWB) to determine indoor position of the individual or the asset. However, RFID has a passive less range, cause health hazards as well and the beacons provide inaccuracy at higher range of frequency due to noise, motion, and fading. Whereas, the UWB are expensive.
[0004] Such technologies utilize a proximity detection (standalone) technique or a trilateration (clustered) technique to determine the position of the individual or the asset in the indoor facility. However, such methods provide inaccurate positioning or cause error in measurement due to physical obstructions when only either of the methods is used for indoor positioning.
[0005] Hence, there is a need for an improved system and method for indoor positioning to address the aforementioned issues.

BRIEF DESCRIPTION
[0006] In accordance with an embodiment of the present disclosure, a system to determine a real time position of an entity in an indoor facility is provided. The system includes a tracking device coupled to the entity. The tracking device is configured to generate a received signal strength indicator (RSSI) data. The system also includes a plurality of sensors located in the indoor facility. The plurality of sensors is configured to sense the received signal strength indicator (RSSI) data received from the tracking device. The system also includes a processor operatively coupled to the plurality of sensors. The processor is configured to collect the received signal strength indicator (RSSI) data corresponding to each of the plurality of sensors to compose a data frame. The processor is also configured to filter noise from the data frame using a filtering technique. The processor is further configured to identify a plurality of collisions of the received signal strength indicator (RSSI) data corresponding to each of the plurality of sensors. The processor is further configured to resolve the plurality of collisions based on a resolving technique selected from a set of techniques. The processor is further configured to calculate a resulting distance using a filtered data. The processor is further configured to determine a positional logic based on the resulting distance. The processor is further configured to calculate the real time position of the entity based on a determined positional logic.
[0007] In accordance with another embodiment of the present disclosure, a method to determine a real time position of an entity in an indoor facility is provided. The method includes generating, by a tracking device, a received signal strength indicator (RSSI) data. The method also includes collecting, by a processor, the received signal strength indicator (RSSI) data corresponding to each of a plurality of sensors to compose a data frame. The method further includes filtering, by the processor, noise from the data frame using a filtering technique. The method further includes identifying, by the processor, a plurality of collisions of the received signal strength indicator (RSSI) data corresponding to each of the plurality of sensors. The method further includes resolving, by the processor, the plurality of collisions based on a resolving technique selected from a set of techniques. The method further includes calculating, by the processor, a resulting distance using a filtered data frame. The method further includes determining, by the processor, a positional logic based on the resulting distance. The method further includes calculating, by the processor, the real time position of the entity based on a determined positional logic.
[0008] To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures.
BRIEF DESCRIPTION OF THE DRAWINGS
The disclosure will be described and explained with additional specificity and detail with the accompanying figures in which:
[0009] FIG. 1 is a block diagram of a system for determining an indoor position of an entity in accordance with an embodiment of the present disclosure;
[0010] FIG. 2 is a schematic representation of an embodiment of the system for determining the indoor position of the entity using presence detection technique in accordance with an embodiment of the present disclosure;
[0011] FIG. 3 is a schematic representation of an embodiment of the system for determining the indoor position of the entity using trilateration technique in accordance with an embodiment of the present disclosure;
[0012] FIG. 4 is a schematic representation of an exemplary system for determining the indoor position of the entity in accordance with an embodiment of the present disclosure; and
[0013] FIG. 5 is a flow chart representing the steps involved in a method for determining an indoor position of an entity in accordance with an embodiment of the present disclosure.
[0014] Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.
DETAILED DESCRIPTION
[0015] For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiment illustrated in the figures and specific language will be used to describe them. It will nevertheless be understood that no limitation of the scope of the disclosure is thereby intended. Such alterations and further modifications in the illustrated system, and such further applications of the principles of the disclosure as would normally occur to those skilled in the art are to be construed as being within the scope of the present disclosure.
[0016] The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such a process or method. Similarly, one or more devices or sub-systems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices, sub-systems, elements, structures, components, additional devices, additional sub-systems, additional elements, additional structures or additional components. Appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.
[0017] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.
[0018] In the following specification and the claims, reference will be made to a number of terms, which shall be defined to have the following meanings. The singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.
[0019] Embodiments of the present disclosure relate to a system to determine a real time position of an entity in an indoor facility. The system includes a tracking device coupled to the entity. The tracking device is configured to generate a received signal strength indicator (RSSI) data. The system also includes a plurality of sensors located in the indoor facility. The plurality of sensors is configured to sense the received signal strength indicator (RSSI) data received from the tracking device. The system also includes a processor operatively coupled to the plurality of sensors. The processor is configured to collect the received signal strength indicator (RSSI) data corresponding to each of the plurality of sensors to compose a data frame. The processor is also configured to filter noise from the data frame using a filtering technique. The processor is further configured to identify a plurality of collisions of the received signal strength indicator (RSSI) data corresponding to each of the plurality of sensors. The processor is further configured to resolve the plurality of collisions based on a resolving technique selected from a set of techniques. The processor is further configured to calculate a resulting distance using a filtered data. The processor is further configured to determine a positional logic based on the resulting distance. The processor is further configured to calculate the real time position of the entity based on a determined positional logic.
[0020] FIG. 1 is a block diagram of a system (10) for determining an indoor position of an entity (20) in accordance with an embodiment of the present disclosure. The system (10) includes a tracking device (30) coupled to the entity (20). In one embodiment, the entity (20) may include an individual or an object. The tracking device (30) is configured to generate a received signal strength indicator (RSSI) data. As used herein, the ‘RSSI’ is an indication of the power level being received by the receive radio after the antenna and possible cable loss. Therefore, the higher the RSSI number, the stronger the signal. In some embodiments, the tracking device (30) may include a Bluetooth low energy (BLE) beacon transmitter. In some embodiment, the tracking device (30) may be configured to generate the received signal strength indicator (RSSI) data at a predefined frequency.
[0021] The system (10) further includes a plurality of sensors (40) located in the indoor facility. As used herein, the ‘facility’ is defined as a place, amenity or building provided for a particular purpose. In one embodiment, a facility may include one or more portions of a building, a business, a home, a shopping mall, a plant, a hospital, a refinery, a school or a campus. The plurality of sensors (40) is configured to sense the received signal strength indicator (RSSI) data received from the tracking device (30). In a specific embodiment, the plurality of sensors (40) may include a Bluetooth low energy (BLE) reader.
[0022] The BLE readers are devices each positioned at a respective fixed location in the facility. The BLE readers may be a device capable of wireless communication with the tracking device (30). In such embodiment, the plurality of sensors (40) may be calibrated to acquire a measure of the distance variation with power. In one embodiment, the plurality of sensors (40) may include one or more standalone sensors and one or more clustered sensors. As used herein, the one or more standalone sensors are the sensors which are able to operate independently. Further, the one or more clustered sensors are grouping of sensor nodes into clusters and electing cluster heads for all the clusters. The cluster heads collect the data from corresponding cluster nodes and forward an aggregated data to a base station.
[0023] Furthermore, the system (10) includes a processor (50) operatively coupled to the plurality of sensors (40). In some embodiments, the processor (50) may be located on a cloud-based server platform. In another embodiment, the processor (50) may be located on an on premise local server. The processor (50) is configured to collect the received signal strength indicator (RSSI) data corresponding to each of the plurality of sensors to compose a data frame. The processor (50) is also configured to filter noise from the data frame using a filtering technique. The processor (50) is further configured to identify a plurality of collisions of the received signal strength indicator (RSSI) data corresponding to each of the plurality of sensors (40).
[0024] The RSSI data from the tracking device (30) may be picked up by the plurality of sensors (40) such as the one or more standalone sensors and the one or more clustered sensors at a same time which result in collision of RSSI signals. The processor (50) is also configured to resolve the plurality of collisions based on a resolving technique selected from a set of techniques. The processor (50) selects the resolving technique from the set of techniques to resolve the plurality of collisions of RSSI data among the one or more clustered sensors and the one or more standalone sensors.
[0025] Moreover, the processor (50) is further configured to calculate a resulting distance using a filtered data frame. In a specific embodiment, the processor (50) may calculate the resulting distance by collecting a plurality of samples of the filtered data frame. In another embodiment, the processor (50) may calculate the resulting distance by inverting the filtered data frame using the calibration performed during setup of the plurality of sensors.
[0026] The processor (50) is further configured to determine a positional logic based on the resulting distance. In one embodiment, the positional logic may include a logic to select a trilateration technique or a presence detection technique. The presence detection technique is used to determine the position of the entity in the indoor facility based on calculation of distance of the proximity of the plurality of sensors. The trilateration technique is used to calculate the position of the entity in the indoor facility based on RSSI data from 2-3 sensors. The processor (50) is further configured to calculate the real time position of the entity based on a determined positional logic. In one embodiment, the processor (50) may calculate the position of the entity based on the presence detection technique. The position of the entity in the indoor facility may be calculated based on the distance of the tracking device (30) from the plurality of sensors (40). The presence detection technique requires a single reference node to create a geofence and estimate the proximity of the tacking device (30) to the sensor node (60) using the path loss estimated distance from the reference node (65) as shown in FIG. 2.
[0027] In another embodiment, the processor (50) may calculate the position of the entity based on the trilateration technique. The position of the entity in the indoor facility may be calculated based on the distance of the tracking device (30) from two or three sensors of the plurality of sensors (40). The trilateration technique uses three fixed non-collinear reference nodes (70, 80, 90) to calculate the physical position of the entity node (100). Based on the coordinates of three reference nodes (70, 80, 90) such as A (x1, y1), B (x2, y2), and C (x3, y3), and the corresponding distances from each of the three fixed non-collinear nodes (70, 80, 90) to the entity node (100) such as R1, R2, and R3, the position of the entity may be calculated as:
(x1-x)2 + (y1-y)2 = R21
(x2-x)2 + (y2-y)2=R22
(x3-x)2 + (y3-y)2=R23
[0028] where (x, y) denotes the coordinates of the entity node O (x, y) as shown in FIG. 3.
[0029] FIG. 4 is a schematic representation of an exemplary system (10) for determining an indoor position of an entity (20) in accordance with an embodiment of the present disclosure. Indoor positioning involves coupling a tracking device (30) to the entity (20) to generate an RSSI data and locating a plurality of sensors (40) in an indoor facility to receive the RSSI data generated by the tracking device (30). Here in this example, the indoor facility may be a factory wherein the plurality of sensors (40) is installed on the walls of the factory and every entity carries the tracking device (30) that may send RSSI data to the plurality of sensors (40) on the walls. Such signals may be used to compute position of the asset. The tracking device (30) is capable of wireless communication with the plurality of sensors (40).
[0030] There are at least two type of sensor installation method is present. One is proximity detection which is performed by the help of standalone sensors arrangement and the second is, trilateration which is performed by the help of clustered sensor arrangement. For examples, the standalone sensor arrangement is done for one or more cabins (110) in the factory while the clustered sensors arrangement is set in the factory area (120). Based on the survey of the facility, this should be determined that which location require standalone sensor, and which require clustered sensors. Each of the plurality of sensors (40) in the factory are calibrated to get a baseline measure of the distance variation with power. The RSSI data obtained from the tracking device (30) is received by the plurality of sensors (40). The plurality of sensors (40) transmits the RSSI data to a processor (50) via a communication network (130). In one embodiment, the communication network (130) may include a wired network such as local area network (LAN). In another embodiment, the communication network (130) may include a wireless network such as 2G, 3G, 4G, LTE, HSDPA, WiFi, Bluetooth, Zigbee, Low Power WAN or the like.
[0031] In some embodiments, the processor (50) may be located on a cloud-based server platform. In another embodiment, the processor (50) may be located on an on premise local server. The processor (50) composes a data frame based on a collected received signal strength indicator (RSSI) data corresponding to each of the plurality of sensors (40). The processor (50) receives the RSSI data at a predefined frequency. For example, the data frame is composed with a data from past 5 seconds which is received from the plurality of sensors (40). Such data frame is then filtered by the processor (50) to remove the noise using a filtering technique. The filtered data is inverted by the processor (50) to calculate a resulting distance using a calibration data of the plurality of sensors (40).
[0032] Further, if the processor (50) identifies a plurality of collisions of RSSI data at some point of time, then the processor (50) resolves the plurality of collisions based on a resolving technique selected from a set of techniques. For example, the sensors are receiving the signal strength from 5 persons present in the factory, then the processor (50) resolves such situation based on a resolving technique and pick the correct RSSI data. After resolution of collisions, the processor (50) determines a positional logic based on the resulting distance. The positional logic is a logic to determine whether to perform a trilateration technique or a presence detection technique. If the correctly picked RSSI data belongs to the factory area (120), then the processor (50) selects the trilateration technique. In case the correctly picked RSSI data belongs to at least one of the one or more cabins (110) in the factory then the processor (50) selects the presence detection technique.
[0033] The processor (50) further calculates a real time location of the entity in the factory based on the selected positional logic. For example, if the RSSI values is picked from a tracking device (30) located in the factory area (120) then the processor (50) selects the trilateration technique to calculate the real time position of the entity (20) in the factory.
[0034] FIG. 5 is a flow chart representing the steps involved in a method (200) for determining an indoor position of an entity in accordance with an embodiment of the present disclosure. The method (200) includes generating, by a tracking device, a received signal strength indicator (RSSI) data in step 210. In one embodiment, generating, by the tracking device, the received signal strength indicator (RSSI) data comprises generating the received signal strength indicator (RSSI) data at a predefined frequency. The method (200) also includes collecting, by a processor, the received signal strength indicator (RSSI) data corresponding to each of a plurality of sensors to compose a data frame in step 220. The method (200) further includes filtering, by the processor, noise from the data frame using a filtering technique in step 230. The method (200) further includes identifying, by the processor, a plurality of collisions of the received signal strength indicator (RSSI) data corresponding to each of the plurality of sensors in step 240.
[0035] The method (200) further includes resolving, by the processor, the plurality of collisions based on a resolving technique selected from a set of techniques in step 250. The method (200) further includes calculating, by the processor, a resulting distance using a filtered data frame in step 260. In some embodiments, calculating, by the processor, the resulting distance using the filtered data frame comprises calculating the resulting distance by inverting the filtered data frame. In such embodiment, calculating, by the processor, the resulting distance using the filtered data frame comprises calculating the resulting distance by inverting the filtered data frame. The method (200) further includes determining, by the processor, a positional logic based on the resulting distance in step 270. In a specific embodiment, determining, by the processor, a positional logic based on the resulting distance comprises determining a logic to select a trilateration technique or a presence detection technique based on the resulting distance. The method (200) further includes calculate the real time position of the entity based on a determined positional logic in step 280.
[0036] Various embodiments of the system and the method for determining an indoor position of an entity described above enable an accurate positioning of the entity in the indoor facility. The system has ability to combine standalone and clustered sensors to optimize hardware cost. The system also provides collision resolution to provide better protection.
[0037] In addition, the system has the ability to determine a position logic to identify a correct method to determine the position of the entity in the indoor facility.
[0038] It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the disclosure and are not intended to be restrictive thereof.
[0039] While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person skilled in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein.
[0040] The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, order of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts need to be necessarily performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples.