Data communications network and method for determining the location of a data communications device

Abstract

The present invention provides a data communications network and a method of operating same to determine the location of a data communications device operably connected to the data communications network. The method includes receiving a request for positional location determination of a data communications device which is configured to operably connect with one or more low orbit satellite(s); one or more Wi-Fi and / or Bluetooth network(s), and / or one or more cell tower(s), and retrieving data from such data sources regarding the positional location of the data communications device. The retrieved data is merged to form a composite dataset, and the composite dataset is normalized and anomalies are removed to generate a processed dataset which is subsequently analysed to generate a positional location estimation of the data communications device.

Description

DATA COMMUNICATIONS NETWORK AND METHOD FOR DETERMINING THE LOCATION OF A DATA COMMUNICATIONS DEVICEFIELD OF THE INVENTION

[0001] The present invention relates to a data communications network and a method of operating same to determine the location of a data communications device operably connected to the data communications network. The present invention finds particular use in circumstances in which a sufficient level of positional accuracy of a connected communications device is required to perform various tasks.BACKGROUND OF THE INVENTION

[0002] Most devices which utilise existing technologies such as GPS (Global Positioning Satellite) to determine the location of the device, such as smartphones with GPS facilities installed, are typically accurate to within approximately 5-10 metres under normal conditions. Such devices also tend to be slow and ineffective in indoor environments or during periods of adverse atmospheric conditions. Whilst GPS-enabled location can be effective in a broad sense, there are a number of circumstances in which a 5-10 metre location accuracy is insufficient and a more accurate positional location determination is required.

[0003] For example, there may be circumstances in which a user seeks to use the GPS receiver of their device to facilitate the location of an exit door relative to their device in a very crowded venue. In this scenario a floorplan of the venue and a position of the exit door will be known, hence if the GPS coordinates of the device can be accurately monitored, the user can be guided to the exit door. However, whilst GPS receivers can provide location coordinates outdoors with reasonable accuracy, the accuracy is generally reduced in an indoor environment and it will be appreciated that reduced accuracy is likely to be insufficient to assist a user (or a software application operating on the user device) to guide the user to a specific point of interest such as an internal exit door.

[0004] In another example, a user (eg. an individual awaiting a delivery) may be driving a vehicle to a destination location where the user is scheduled to meet with another user (eg. a delivery driver). The user may be running late and hence prefers that the delivery driver meet at an updated location (eg. at the user’s vehicle that may be located a street away from the destination location). This scenario requires the device location facilities associated with each of the user’s smartphones to be more positionally accurate than presently achievable, which is difficult to achieve using existing technologies such as GPS receivers.

[0005] The above problems are exacerbated in view of the presently poor interoperability between different data communications devices and the number of different options available to users to connect to a data communications network (eg. Apple, Android, etc). For example, Apple devices will use Apple’s proprietary operating system (iOS) to combine GPS, WiFi, and cell phone tower communications functions to perform triangulation to determine the device’s positional location. Whilst Android and Google devices rely upon a similar hybrid positional location determination technique, these techniques generally comprise Google’s Location Services API which utilizes different hardware and software optimizations as compared with other devices.

[0006] Accordingly, there is a need to improve existing means of determining the positional location of a data communications device connected to a data communications network to advise outcomes such as those described above. Since location data is utilised for various purposes in a significant number of software applications operating on such devices, including for the purposes of guiding the device to another location or seeking to locate a device according to the above examples, it will be appreciated that by improving the accuracy of retrieved location data, the use of software applications and hence user experiences will be enhanced and in some instances, will enable functionality that is currently not available or achievable.

[0007] The present invention seeks to provide a solution to the problems associated with existing networks, methods and / or systems used to determine the positional location of a data communications device operating within a data communications network, or at least seeks to provide an alternative to currently implemented techniques.

[0008] The reference to any prior art in this specification is not, and should not be taken as, an acknowledgement or any suggestion, that the prior art forms part of the common general knowledge at the priority date of the present disclosure.SUMMARY OF THE INVENTION

[0009] In one aspect, the present invention provides a data communications network including connected data communications devices and a method of operating same to determine the positional location of a data communications device operably connected to the network, the method including, receiving, by the one or more processors, a request for positional location determination of a data communications device, the data communications device configured to operably connect with, one or more low orbit satellite(s), one or more Wi-Fi and / or Bluetooth network(s), and / or one or more cell tower(s), retrieving, by one or more processors, data regarding the positional location of the data communications device from the one or more low orbit satellite(s), the one or more Wi-Fi and / or Bluetooth network(s), and / or the one or more cell tower(s), merging, by one or more processors, the retrieved data to form a composite dataset, normalizing, by one or more processors, the composite dataset and removing anomalies to generate a processed dataset, and analysing, by one or more processors, the processed dataset to generate a positional location estimation of the data communications device.

[0010] In an embodiment, the method further includes providing, by the one or more processors, in response to the request, the location estimation regarding the location of the data communications device.

[0011] In an embodiment, the estimation regarding the location of the data communications device includes geographic location co-ordinates.

[0012] In an embodiment, the anomalies are removed using an anomaly detection technique that dynamically identifies and removes anomalies in the positional location data.

[0013] In an embodiment, the anomaly detection technique includes training one or more machine learning models using historical data such that irregular patterns caused by environmental factors are recognised, the environmental factors including one or more of, signal interference, weather conditions, terrain, obstacles, or device malfunctions.

[0014] In an embodiment, when the data communications device operably connects with data sources including the one or more low orbit satellites, one or more Wi-Fi and / or Bluetooth network(s), and / or one or more cell tower(s), the quality of incoming signalsfrom each data source is continuously monitored and assessed such that the data source(s) that provide the most reliable input data under current conditions are selected and / or prioritized.

[0015] In an embodiment, the method further includes adjusting the precision of the positional location estimation and / or a frequency of generating the estimation according to one or more of, the device hardware, the operating system of the device, or the remaining available battery power of the device.

[0016] In an embodiment, the device hardware is any one of, a smartphone, a laptop, a wearable device, a workstation, or a desktop computer.

[0017] In an embodiment, the operating system of the data communications device is any one of, iOS, Android, macOS, or Windows.

[0018] In an embodiment, the data retrieved and used to generate the positional location estimation further includes data from any one or more of, sensors associated with the data communications device, including from one or more of, an accelerometer, a gyroscope, a magnetometer, or any other device within a predefined geographical area of the data communications device.

[0019] In an embodiment, the request for determination regarding the location of a first data communications device is a request received from the first data communications device regarding its location, or a request received from a second data communications device regarding the location of the first data communications device.

[0020] In an embodiment, the request for determination regarding the location of a data communications device includes a request to determine whether the data communications device has entered, or is present within, one or more predefined zones (eg. to enable a first user having a first communications device to determine whether a second user having a second communications device has entered into a particular zone in which the users are scheduled to meet).

[0021] In an embodiment, the method further includes determining, by one or more processors, whether the data communications device is located within location coordinates defining the one or more predefined zones (eg. using one or more analytical methods such as point-in-polygon algorithms).

[0022] In an embodiment, the one or more predefined zones represent geographical areas and the method further includes, causing, based on detection of the data communications device within one of the predefined zones, one or more additional actions including notifying a user regarding the location of the data communications device within the one or more predefined zones.

[0023] In an embodiment, notifying the user includes providing the user with information regarding the location of the data communications device.

[0024] In an embodiment, the method further includes prompting, by one or more processors, a user associated with the data communications device to provide substantially real-time feedback regarding the accuracy of the generated location estimation.

[0025] In an embodiment, the method further includes utilizing, by one or more processors, one or more artificial intelligence techniques to improve subsequent location estimations.

[0026] In another aspect, the present invention provides a computer-implemented system for determining the positional location of a data communications device, the system including one or more processors operable to, receive a request for positional location determination of a data communications device, the data communications device configured to operably connect and communicate with, one or more low orbit satellite(s), one or more Wi-Fi and / or Bluetooth network(s), and / or one or more cell tower(s), retrieve data regarding the positional location of the data communications device from the one or more low orbit satellite(s), the one or more Wi-Fi and / or Bluetooth network(s), and / or the one or more cell tower(s), merge the retrieved data to form a composite dataset, normalize the composite dataset and filtering anomalies to generate a processed dataset; and analyse the processed dataset to generate a positional location estimation of the data communications device.

[0027] In a further aspect, the present invention provides a non-transitory computer- readable medium including computer instruction code stored therein, that when executed on one or more processors of a data communications network cause the network to perform the steps of, receiving, by the one or more processors, a request for positional location determination of a data communications device, the data communications deviceconfigured to connect and communicate with, one or more low orbit satellite(s), one or more Wi-Fi and / or Bluetooth network(s), and / or one or more cell tower(s), retrieving, by the one or more processors, data regarding the positional location of the data communications device from the one or more low orbit satellite(s), the one or more Wi-Fi and / or Bluetooth network(s), and / or the one or more cell tower(s), merging, by the one or more processors, the retrieved data to form a composite dataset, normalizing, by the one or more processors, the composite dataset and filtering anomalies to generate a processed dataset, and analysing, by one or more processors, the processed dataset to generate a positional location estimation of the data communications device.BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Embodiments of the invention will now be described in further detail with reference to the accompanying Figures in which:

[0029] Figure 1 provides an overview of data communications network according to an embodiment of the present invention showing, in particular, the interaction of various network components;

[0030] Figure 2 provides a diagrammatic representation of an exemplary server component of the network illustrated in Figure 1 ;

[0031] Figure 3 illustrates an exemplary flow diagram of a process that enables users to download and install a software application, and subsequently access, or register to use, the software application for interaction with the network illustrated in Figure 1 , including to establish a user account and to request determination of a positional location associated with another data communications device;

[0032] Figure 4 illustrates exemplary interfaces of the software application including a first interface that provides a display of the positional location estimation generated, and a second interface displaying predefined zones and specifying the zone to which the location estimation corresponds;

[0033] Figure 5 illustrates an exemplary flow diagram of a process that enables users to connect and communicate via the software application, including between a first user who has sought a determination of the positional location of a data communications device, and a second user being the owner of the other data communications device for which the positional location has been determined; and

[0034] Figure 6 illustrates further exemplary interfaces of the software application for providing alerts / notifications and a search facility.DETAILED DESCRIPTION OF EMBODIMENT(S) OF THE INVENTION

[0035] For simplicity and illustrative purposes, the present disclosure is described by referring to embodiment(s) thereof. In the following description, numerous specific details are described to provide a better understanding of the present disclosure. However, it will be readily apparent that the invention may be practiced without limitation to these specific details. In other instances, some features have not been described in detail to avoid obscuring the present disclosure.

[0036] According to an embodiment, the present invention provides a computer- implemented data communications network and a method of operating the network including data communications devices operably connected with the network to generate an estimation (85) of the positional location (80) of a data communications device (55) for which location determination is required. In particular, the network and method provide a platform that hosts a computer-executable software application (40), wherein the application (40) is accessible by a plurality of registered users (30) seeking to have their own devices (50) utilise enhanced location determination functionality (location services) and / or seeking to locate a data communications device associated with another user. In particular, the network utilizes a central server (20) in communication with data communication devices (50) associated with users (30).

[0037] The central server (20) maintains one or more processors and / or databases for performing functions, including receiving a request for positional location determination of a data communications device (55) for which such location determination is required or sought, wherein the data communications device (55) is configured to operably connect with one or more low orbit satellites (60), one or more Wi-Fi (75) and / or Bluetooth (70) networks, and / or one or more cell towers (65), and retrieve data regarding the positional location (80) of the data communications device (55) requiring location determination from the satellite(s) (60), Wi-Fi (75) and / or Bluetooth (70) networks, and cell tower(s) (65). The retrieved data is subsequently merged to form a composite data set and normalized by removal of anomalies to generate a processed data set. The processed data set may then be analyzed to generate a positional location estimation (85) associated with the data communication device (55) which is more accurate than traditional methods of location such as GPS.

[0038] As mentioned previously, the data communications device (55) requiring location determination may be the user device (50) (eg. when the device is used to estimate its own location, including relative to other objects) or may be a device other than to the user device (50) such as the device of another user (eg. to determine the location of the other user). For the purpose of clarity, and in view of the main embodiment described herein relating to the latter scenario, two different reference numerals (50) and (55) are used to indicate the two devices.

[0039] Accordingly, it will be appreciated that the device requiring location determination may be the same device as the device (50) from which the request for location determination is received, or may be a separate and different device (55). In the embodiment shown in Figure 1 , the request for location determination is received from the user device (50), and the device (55) requiring location determination is a separate (second) device (55). In this way, it will be appreciated that not only does the present invention assist with the location of devices associated with other users, but may also assist with improving accuracy of location data associated with a user’s own device with such location data capable of being utilized for various purposes and in a significant number of software applications operating on the user’s device.

[0040] The skilled person will appreciate that the platform provides a user (30) with a means for determining the positional location (85) associated with their own and / or other data communications devices (50 / 55) operating within a data communications network.

[0041] Figure 1 is divided into Segments 200 to 600 which are further detailed in subsequent Figures 2 to 6. In particular, Segment 200 of Figure 1 shows the server component (20) with which the software application (40) operating on each data communications device (50) is configured to communicate. It will be apparent to the person skilled in the relevant field of technology that the software application (40) may be a mobile application or a web application and that, similarly, the data communications devices (50) utilized by users (30) may be mobile devices or fixed location computing devices. Examples of mobile devices including mobile phones, wearables and laptops, and examples of fixed location computing devices include personal computers and workstations (not shown). The same applies to device (55) requiring location determination, which, as described above, may be the user’s own device (50). The server component (20) is additionally detailed in Figure 2.

[0042] The skilled person will appreciate that the steps described herein may be executed by the devices (50), wherein such operations are facilitated by the software application (40) operating on each device (50). According to another implementation of the present invention, the server (20) is programmed to provide most, or all, of the functions herein described particularly where they cannot be provided locally on the user (50) device or where it may be commercially or technically infeasible to implement such an arrangement. In other words, the steps described herein as performed by the device (50), or components thereof, may be associated with hardware that is located externally of the devices such as the remote central server (20) (ie. in a distributed architecture). Different arrangements are possible in this regard, and alternative variations will be apparent to the person skilled in the relevant field of technology.

[0043] According to one example of a distributed architecture, reliance on centralized servers (20) may be reduced for certain data processing tasks by offloading computations such as location merging, anomaly filtering, and data normalization to the devices (50) themselves. In this way, the platform could operate with lower latency, quicker response times, and less network dependency. In scenarios where connectivity may be limited or intermittent, this local processing ensures that users may continue to access locationbased services and receive accurate results, even in areas where network coverage might not be consistent. This decentralized approach may enhance the speed and reliability of the platform.

[0044] In one implementation, blockchain technology may be utilized to securely store and verify location data shared between users (30) or devices (50 / 55). One or more artificial intelligence techniques may be utilized to manage encryption and access controls, ensuring that location data is securely recorded and can only be accessed by authorized parties. Blockchain techniques may be used to provide an immutable, transparent record of location data, adding an additional layer of security. Blockchain integration improves trust and security when sharing location data, addressing concerns regarding privacy and data manipulation. This may be particularly useful for industries requiring verifiable location information, such as logistics, delivery services, or any application where transparency and security are critical.

[0045] According to a further implementation, an intelligent caching mechanism may be incorporated that temporarily stores frequently requested location data. In this regard,one or more artificial intelligence techniques may be used to determine which data is most relevant storing same in a cache, allowing for faster access and reducing the load on the server (20). The platform would extract data from the cache when necessary, providing faster location updates. This enhancement reduces latency and provides faster location responses, improving the overall user experience, particularly for applications requiring frequent, real-time location updates. By reducing data transmission and computation delays, the platform may enhance performance in real-time tracking applications such as logistics, fleet management, or emergency response in addition to reducing network traffic.

[0046] Segment 300 of Figurel shows a user (30) downloading and installing the application (40) and subsequently accessing the application (40) to establish a user account and profile, including submission of various details and preferences relating to their interaction with the software application (40), and entering a request for positional location determination of a third party data communications device (55) which is operably connected with one or more low orbit satellites (60), one or more Wi-Fi (75) and / or Bluetooth (70) networks, and / or one or more cell towers (65), as further illustrated in Figure 3. Segment 400 of Figure 1 illustrates various interfaces including a location estimation interface (170) providing user (30) with a positional location estimation (85) for device (55), and a zone interface (180) which provides the user (30) with an indication regarding whether the estimated co-ordinates of the device (55) are within one or more predefined zones (90), as further illustrated in Figure 4. Segment 500 of Figure 1 illustrates a connection and communications interface, as further illustrated in Figure 5. Finally, Segment 600 of Figure 1 illustrates further functionality of the software application (40) including an interface (210) that enables users (30) to receive alerts and / or notifications, and a search interface (220) which enables users (30) to conduct particular searches, and as further illustrated in Figure 6.

[0047] As mentioned above, Figure 2 depicts Segment 200 of Figure 1 in greater detail and, in particular, Figure 2 illustrates a server component (20) which includes infrastructure upon which the platform of the present invention operates. The infrastructure may be local or cloud-based.

[0048] The central server (20) may operate one or more computer processors and maintain one or more databases to enable the following functionality and / or storage:• User account register (100) storing user’s details such as name, age, address, contact details, identifiers such as driver’s license or passport details, and any additional data which may be relevant for the purposes of identifying and distinguishing between registered users (30);• Device database (105) storing details related to registered user devices such as the abovementioned portable and fixed location devices (50) which are utilized by users (30) to enhance the positional location functionality associated with the user’s own device (50) or to determine the positional location of another device (55). For example, information such as device serial numbers, telecommunications carriers, registered owners, etc, may be stored in database (105);• Location database (1 10) storing location information relating to each device stored in the devices database (105) including, but not limited to, current and historical recorded locations of each device (if available), and details relating to zones (90) defined by individual users which may represent, for example, geographical areas (eg. suburbs). Detection of a device within one of the pre-defined zones (90) may give rise to one or more additional outputs, as described in further detail below;• Data processing functionality (115) for processing user input commands and data received, to generate relevant outputs for display. For example data processing functionality (115) may be responsible for merging data which has been received from the various different sources including the cell tower(s) (65), Bluetooth (70) or Wi-Fi (75) network(s), and / or low orbit satellite(s) (60), in order to form a composite data set, and normalizing the composite data set and removing anomalies in order to generate a pre- processed dataset used to generate a positional location estimation (85) of a device (50 / 55). In order to determine whether the device coordinates are within predefined zones (90), the functionality (1 15) may use point-in- polygon or similar analytical methods to determine if the device’s coordinates are within pre-defined location coordinates associated with predefined zones (90);• Connection and communications functionality (120) which enables communications amongst users including that described and illustrated with respect to Figure 5;• Alerts / notification functionality (125) which enables users (30) to receive alerts and / or notifications through their device (50) and, in particular, by functions afforded by the software application (40) operating on each device (50), wherein such alerts and / or notifications may be generated based upon predefined criteria and conditions. For example, an alert and / or notification could be generated based upon a positional location estimation (85) generated in respect of a particular device (50 / 55), or an incoming message from another user (30) or an administrator of the software application;• Search functionality (130) which enables users (30) to undertake searching via an interface (220) including with respect to other registered users, and with respect to historical records relating to location co-ordinates associated with the user’s device (50) or other devices (55) for which a location determination has previously been conducted; and• Payment gateway functionality (135) allowing users (30) to manage any required payments through the software application (40) including, for example, payment of any required subscription fees.

[0049] Figure 2 also depicts that server (20) is configured to enable communication (140) with the user’s device (50) and, in particular, with the software application (40) operating on each device (50). Such communications may occur via the internet or other similar data communications network.

[0050] Figure 3 illustrates in greater detail segment 300 of Figure 1 and, in particular, the steps associated with a user (30) installing the software application (40) which may be achieved by downloading the application (40) from an application store or other means. Each user (30) may create an account using the application (40) and the account information may be stored in the user account register (100). As discussed above, the user account register (100) may capture information sufficient to enable each user (30) to be correctly identified.

[0051] The process of downloading the software application (40) is indicated by arrow (150), and interface (160) is also shown which enables users (30) to install the application (40) in order to access the functionality thereof, including to create and maintain a user account and to specify preferences of the user (30). Such preferences may be entered in one or more additional interfaces which may prompt the user (30) to enter such preferences. In other words, once the application has been accessed by a user (30), the user (30) may be presented with an interface, identical or similar to interface (160), to allow the user to add preferences to their profile, including the ability to edit profile / account details. Once sufficient information has been provided by the user (30), and such information has been verified using, for example, one or more digital verification techniques, the user (30) will be successfully registered such that the user (30) becomes a registered user and may utilize functionality afforded by the application (40), which may accord with a subscription level of the user (30).

[0052] Whilst the above description relates to a user (30) downloading and installing a software application (40) to access the functionality of the software application (40) including, for example, to request a determination of the positional location (80) of another data communications device (55), it will be readily understood that other configurations may be possible. For example, such location determination functionality may be implemented as a standard feature of the data communications device (50) without the need for the user (30) to downland and install any software application (40) such that the location identification functionality operates continuously in the background. This particular configuration would be more likely in circumstances where the functionality of the present invention is implemented as a location identification service for the device (50) itself. Alternatively, where the user (30) prefers to obtain details relating to the positional location of another device (55), such a request may be uploaded through a dedicated software application (40) as described herein.

[0053] Figure 3 also illustrates how the additional device (55), which in the embodiment shown is the device requiring location determination, is operably connected with one or more low orbit satellites (60), one or more Wi-Fi (75) and / or Bluetooth (70) networks, as well as one or more cell towers (65). The skilled addressee will appreciate that connection with multiple wireless communications networks and, in particular, the use of one or more low orbit satellites (60), the determination of a location of the device(55) is facilitated such that the determination will have greater positional accuracy than presently achievable. In this way, the data communications network and method proposed herein is more likely to assist a user (30) seeking to locate another device (55) or to utilize location services associated with their own device (50), and may do so irrespective of the operating system (iOS) associated with the device.

[0054] The platform may dynamically adapt to the most suitable data sources for location estimation (eg. by using a multi-modal blending algorithm). Such an Al-powered algorithm would continuously assess the quality of incoming signals from satellites (60), Wi-Fi networks (75), Bluetooth (70), and / or cell towers (65), prioritizing the data source that offers the most reliable input under the current conditions. For example, in open outdoor spaces, satellite data may be prioritized, while in dense urban environments or indoor settings, Wi-Fi or Bluetooth obtained data may be weighted more heavily to indicate greater preference. This dynamic selection process ensures that the location estimation remains accurate even in challenging environments, and provides greater flexibility when seeking to determine a device's position in various scenarios.

[0055] The cross-platform functionality of the present invention enables seamless operation across a variety of devices and operating systems, including iOS, Android, macOS, and Windows, as well as diverse hardware such as smartphones, tablets, and desktop computers. One or more artificial intelligence models may also be utilized to improve interoperability across such platforms, adapting the location algorithms to different device sensors and OS-specific configurations. Cross-platform capability improves location services accessibility across a wide range of users (30), regardless of their preferred devices or operating systems. Accordingly, whether a user is accessing the platform through a smartphone, tablet or laptop, the location data would be synchronized in substantially real-time across all devices, ensuring that users (30) can transition between devices without losing the accuracy or continuity of their location information.

[0056] The platform may further provide a calibration facility that adjusts location accuracy according to the specific device. Different devices, such as smartphones, wearables, or loT sensors, have varying capabilities for location tracking. One or more artificial intelligence models may be utilized to automatically detect the device type and adjust the precision of the location data accordingly, seeking optimal performanceaccording to the available hardware. This is expected to improve the platform’s ability to adapt to a variety of devices, ensuring that location data is as accurate as possible, regardless of the device’s sensor capabilities. Accordingly, a more seamless experience across multiple device types will be provided, ensuring that all users, regardless of device choice, receive accurate location data.

[0057] The compatibility of the platform with a wider range of devices, such as loT devices including wearables, fitness trackers, and other connected devices, may also be beneficial since such devices often come equipped with additional sensors, such as accelerometers, gyroscopes, and magnetometers, which may be integrated into the location estimation process. By utilising the sensor data from such devices, the system may gain additional context regarding the user's movement and physical activity, allowing for more accurate predictions of location in real-time. Additionally, incorporating Al algorithms to analyze sensor inputs provides the ability to detect user patterns and behaviors, further improving location estimation (85).

[0058] The remaining available battery power and user’s activity may also be taken into account to adjust the frequency and position of location updates. For example, when the device (50) is low on power, the platform may automatically lower the frequency and / or accuracy of location estimates. Conversely, when the battery level is sufficient, the platform may provide higher accuracy and more frequent updates. This enhancement allows for more efficient battery usage, ensuring that location-based services continue to function properly while minimizing power consumption. This is particularly important for mobile applications, where battery life is a critical consideration. Users (30) can rely on location tracking without worrying about rapid battery power depletion, which also improves the energy-efficiency of the platform / system.

[0059] Additional data which may be combined with location data from satellites (60), Wi-Fi networks (75) and / or Bluetooth (70), and / or cell towers (65) may include data from other devices associated with other users. For example, introducing crowdsourced location data aggregation may enable the platform to utilise data from multiple users to improve location estimations (85), particularly in areas with poor device density or weak signal reception. By combining data from several devices within a certain geographic area, the platform may infer the most probable location even if individual device data is suspected or expected to lack reliability. One or more artificial intelligence algorithms maybe utilized to process and analyze any crowdsourced data to enhance the platform's predictive capabilities, filling in data gaps where individual devices (50 / 55) may lack strong signals or accurate information. This collective approach may ensure more accurate results, particularly in remote or underserved locations.

[0060] Regarding the utilization of location services associated with the user’s own device, some example scenarios have been previously described in the present specification include assisting a user (30) to a specific point of interest such as an exit door based on a more accurate estimation of the device’s location relative to the door (having a known position), and assisting a delivery driver to an updated destination location associated with a delivery recipient by monitoring the precise location of a device associated with the delivery recipient. Irrespective of the application, it will be appreciated that by utilizing location services in accordance with the present invention, more positionally accurate determinations regarding the location of a user device (50 / 55) will be achievable and beneficial.

[0061] Figure 4 shows Segment 400 of Figure 1 in greater detail and, in particular, the use of the software application (40) to generate a location estimation interface (170) in which a positional location estimation (85) is provided to the user (30) subsequent to the user issuing a request for such information. A further interface (180) is shown which displays particular pre-defined zones (90) and an indication of the zone in which the particular positional location estimation (85) is located.

[0062] It will be appreciated that in the location estimation interface (170), the positional location estimation (85) may appear in any number of formats and may also specify the network (satellite, WIFI and / or Bluetooth, and / or cell tower) involved in determining the positional data, or an indication regarding the extent to which it is involved (eg. by indicating a percentage). In the example shown in Figure 4, coordinates in the form of latitude and longitude coordinates are displayed along with an interactive map including a graphical device known as a “pin” indicating the precise location associated with the estimation (85).

[0063] It will be appreciated that artificial intelligence techniques and machine learning may be implemented to enhance aspects of the present invention. For example, machine learning-based anomaly detection may be incorporated which would enable amachine learning model to identify and correct errors in location data dynamically. This enhancement may involve training models on historical data to recognize irregular patterns caused by environmental factors such as signal interference, weather conditions, terrain, obstacles (eg. buildings, tunnels) or device malfunctions. The platform may adjust algorithms in substantially real-time, filtering out anomalies and ensuring that location estimations remain as accurate as possible despite varying conditions. By continuously learning from incoming data, this approach significantly improves reliability, particularly in complex environments such as crowded indoor spaces or dense urban areas, where traditional location systems fail to provide accurate and reliable location services.

[0064] By integrating adaptive learning models, the platform may learn from user behavior over time, making more accurate predictions about user movements, location preferences, etc. For example, the platform may learn the user’s common routes, frequently visited locations, and preferred times for specific activities. Over time, it may use this information to optimize location predictions, reducing the need for constant recalculation and improving the overall resource use efficiency of the platform. Additionally, adaptive learning allows the platform to anticipate changes in user behavior, automatically adjusting its location-based services without requiring manual input.

[0065] Location accuracy may also be improved by incorporating real-time user feedback to create a closed-loop. In this regard, users (30) may provide immediate feedback regarding the accuracy of their location estimates (85) through simple confirmations or corrections, such as "accurate," "inaccurate," or "location detected in wrong place." One or more artificial intelligence techniques may be utilized to use such feedback to fine-tune the algorithms utilized and improve subsequent location estimations (85). This continuous learning process allows the platform to enhance its accuracy over time, ensuring that each user’s experience is improved and the location services are continually improving.

[0066] Where the user request includes a request to determine whether the data communications device (55) is located within one or more predefined zones (90), an interface (180) such that as shown in Figure 4 may be generated and displayed, which may also include an indication of the network used to generate the positional data and a pin indicating in which predefined zone (90) the device (55) is located according to the positional location estimation (85).

[0067] The data processing functionality (115) may use one or more analytical methods (eg. point in polygon) to determine if the device’s coordinates are within the defined location coordinates associated with one or more of the pre-defined zones (90). This may be useful where, for example, a user (30) is seeking to be notified when another user has entered into a predefined zone (90) (eg. when the user (30) is seeking to meet with the other user).

[0068] The one or more pre-defined zones (90) may present geographic areas defined by the user (eg. suburbs), and detection of the other user entering into a predefined zone (eg. zone 3) may give rise to one or more additional outputs. For example, the additional output may include a notification to the user (30) regarding the location of the other user within a particular pre-defined zone. In another embodiment, once the other user has been detected as entering into a pre-defined zone (90), a communications interface (190) may be presented to each user, as shown in Figure 5 and described in greater detail below, to enable further contact and communications to occur between the users.

[0069] One or more artificial intelligence techniques may be utilized to facilitate the establishment of geographical zones (90). For example, Al-driven geospatial intelligence could automatically create and manage predefined zones (90), such as geographical regions of interest, based on the user's behavior and activities. In this regard, the platform may monitor user movements over time, learning typical patterns, and dynamically adapt these zones (90) as the user’s habits evolve. For instance, the platform could automatically generate "home zones" based on frequent visits to specific locations, or modify zones to reflect updated locations where the user (30) regularly operates. This real-time adjustment of zones (90) would ensure that the platform remains responsive to the user's needs, enabling more proactive location-based actions such as notifications or geofencing.

[0070] Figure 5 shows Segment 500 of Figure 1 in greater detail, and in particular, a communications interface that enables written and verbal communications to be effected between registered users utilizing the software application (40). The skilled addressee will appreciate that requests for contact may be transmitted from one user to another through any known means, including push notifications, text messages, email messages or any other means.

[0071] It will be appreciated that the present invention has a variety of applications. In another application example, a job seeker may be automatically matched with an employer based on the estimation of the positional location of a data communications device associated with each of the employer and job seeker. For example, if one device is detected as residing in sufficiently close proximity to the other device following an estimation of their positional locations, the job seeker may be automatically shortlisted as a candidate for a particular job offered by the employer. Further, the estimation of device location and entry of the device into pre-defined zones may be subsequently used for the purpose of providing the employer with substantially real-time notifications regarding when the candidate is within close proximity or is likely to be in a specific location (eg. for attendance at an interview). Where one device is used to track the location of another device, it will be appreciated that relevant permissions may first be sought and granted by the users associated with such devices.

[0072] Figure 6 shows Segment 600 of Figure 1 in greater detail and, in particular, additional software application interfaces (210) and (220). The interface (210) represents an alert / notification interface which may be configured to automatically generate alerts and / or notifications to the user (30) based upon the detection of a trigger. Such triggers may include, but are not limited to, the receipt of a message through the communication interface of Figure 5, the generation of a positional location estimation (85) as shown in the location estimation interface (170) of Figure 4, etc.

[0073] The interface (220) represents a search interface in which users (30) may be invited to conduct relevant searches using the software application (40) including, for example, a search for contact details of other registered users (30), a search for devices including any devices currently located within certain pre-defined zones (90) (wherein the determination of devices located in particular zones (90) is based upon continuous or regular determination of a positional location estimation (85) in respect of such devices), and searches in relation to available communication networks and information associated therewith including, for example, satellite (60), cell towers (65), Wi-Fi (75) and / or Bluetooth (70) communication networks that are within vicinity of the user (30) and likely to provide the strongest network signal.

[0074] Whilst not shown, the software application (40) may also provide an interface representing a payment interface which may be presented to a user (30) at any time inwhich the user (30) may be required to provide payments. In this regard, various payments options may be presented to the user (30) including, but not limited to, credit card, PayPal, etc.

[0075] Al-powered security and privacy features may also be incorporated to maintain the confidentiality and integrity of user data. For example, the platform may use one or more artificial intelligence techniques to detect unusual access patterns or potential security breaches, automatically adjusting its security protocols substantially in real-time. For example, when the platform detects an abnormal location request, or when data is accessed from an unfamiliar device, enhanced encryption or multi-factor authentication may be triggered to secure the data. These adaptive security measures would ensure that user location data remains protected against unauthorized access or misuse, addressing privacy concerns and regulatory compliance issues.

[0076] The methods and systems described herein may be deployed in part or in whole through a machine that executes computer software, program codes, and / or instructions on a processor. The processor may be part of a server, cloud server, client, network infrastructure, mobile computing platform, stationary computing platform, or other computing platform. A processor may be any kind of computational or processing device capable of executing program instructions, codes, binary instructions and the like. The processor may be or include a signal processor, digital processor, embedded processor, microprocessor or any variant such as a co-processor (math co-processor, graphic coprocessor, communication co-processor and the like) and the like that may directly or indirectly facilitate execution of program code or program instructions stored thereon. In addition, the processor may enable execution of multiple programs, threads, and codes. The threads may be executed simultaneously to enhance the performance of the processor and to facilitate simultaneous operations of the application. By way of implementation, methods, program codes, program instructions and the like described herein may be implemented in one or more threads. The thread may spawn other threads that may have assigned priorities associated with them; the processor may execute these threads based on priority or any other order based on instructions provided in the program code. The processor may include memory that stores methods, codes, instructions and programs as described herein and elsewhere. The processor may access a storage medium through an interface that may store methods, codes, and instructions asdescribed herein and elsewhere. The storage medium associated with the processor for storing methods, programs, codes, program instructions or other type of instructions capable of being executed by the computing or processing device may include but may not be limited to one or more of a CD-ROM, DVD, memory, hard disk, flash drive, RAM, ROM, cache and the like.

[0077] A processor may include one or more cores that may enhance speed and performance of a multiprocessor. In some embodiments, the process may be a dual core processor, quad core processors, other chip-level multiprocessor and the like that combine two or more independent cores (called a die).

[0078] The methods and systems described herein may be deployed in part or in whole through a machine that executes computer software on a server, cloud server, client, firewall, gateway, hub, router, or other such computer and / or networking hardware. The software program may be associated with a server that may include a file server, print server, domain server, internet server, intranet server and other variants such as secondary server, host server, distributed server and the like. The server may include one or more of memories, processors, computer readable media, storage media, ports (physical and virtual), communication devices, and interfaces capable of accessing other servers, clients, machines, and devices through a wired or a wireless medium, and the like. The methods, programs or codes as described herein and elsewhere may be executed by the server. In addition, other devices required for execution of methods as described in this application may be considered as a part of the infrastructure associated with the server.

[0079] The server may provide an interface to other devices including, without limitation, clients, other servers, printers, database servers, print servers, file servers, communication servers, distributed servers and the like. Additionally, this coupling and / or connection may facilitate remote execution of programs across the network. The networking of some or all of these devices may facilitate parallel processing of a program or method at one or more locations without deviating from the scope of the disclosure. In addition, any of the devices attached to the server through an interface may include at least one storage medium capable of storing methods, programs, code and / or instructions. A central repository may provide program instructions to be executed ondifferent devices. In this implementation, the remote repository may act as a storage medium for program code, instructions, and programs.

[0080] The software program may be associated with a client that may include a file client, print client, domain client, internet client, intranet client and other variants such as secondary client, host client, distributed client and the like. The client may include one or more of memories, processors, computer readable media, storage media, ports (physical and virtual), communication devices, and interfaces capable of accessing other clients, servers, machines, and devices through a wired or a wireless medium, and the like. The methods, programs or codes as described herein and elsewhere may be executed by the client. In addition, other devices required for execution of methods as described in this application may be considered as a part of the infrastructure associated with the client.

[0081] The client may provide an interface to other devices including, without limitation, servers, other clients, printers, database servers, print servers, file servers, communication servers, distributed servers and the like. Additionally, this coupling and / or connection may facilitate remote execution of programs across the network. The networking of some or all of these devices may facilitate parallel processing of a program or method at one or more locations without deviating from the scope of the disclosure. In addition, any of the devices attached to the client through an interface may include at least one storage medium capable of storing methods, programs, applications, code and / or instructions. A central repository may provide program instructions to be executed on different devices. In this implementation, the remote repository may act as a storage medium for program code, instructions, and programs.

[0082] The methods and systems described herein may be deployed in part or in whole through network infrastructures. The network infrastructure may include elements such as computing devices, servers, routers, hubs, firewalls, clients, personal computers, communication devices, routing devices and other active and passive devices, modules and / or components as known in the art. The computing and / or non-computing device(s) associated with the network infrastructure may include, apart from other components, a storage medium such as flash memory, buffer, stack, RAM, ROM and the like. The processes, methods, program codes, instructions described herein and elsewhere may be executed by one or more of the network infrastructural elements.

[0083] The methods, program codes, and instructions described herein and elsewhere may be implemented in different devices which may operate in wired or wireless networks. Examples of wireless networks include 4th Generation (4G) networks (eg. Long-Term Evolution (LTE)) or 5th Generation (5G) networks, as well as non-cellular networks such as Wireless Local Area Networks (WLANs). However, the principles described therein may equally apply to other types of networks.

[0084] The operations, methods, programs codes, and instructions described herein and elsewhere may be implemented on or through mobile devices. The mobile devices may include navigation devices, cell phones, mobile phones, mobile personal digital assistants, laptops, palmtops, netbooks, pagers, electronic books readers, music players and the like. These devices may include, apart from other components, a storage medium such as a flash memory, buffer, RAM, ROM and one or more computing devices. The computing devices associated with mobile devices may be enabled to execute program codes, methods, and instructions stored thereon. Alternatively, the mobile devices may be configured to execute instructions in collaboration with other devices. The mobile devices may communicate with base stations interfaced with servers and configured to execute program codes. The mobile devices may communicate on a peer-to-peer network, mesh network, or other communications network. The program code may be stored on the storage medium associated with the server and executed by a computing device embedded within the server. The base station may include a computing device and a storage medium. The storage device may store program codes and instructions executed by the computing devices associated with the base station.

[0085] The computer software, program codes, and / or instructions may be stored and / or accessed on machine readable media that may include computer components, devices, and recording media that retain digital data used for computing for some interval of time, semiconductor storage known as random access memory (RAM), mass storage typically for more permanent storage, such as optical discs, forms of magnetic storage like hard disks, tapes, drums, cards and other types, processor registers, cache memory, volatile memory, non-volatile memory including optical storage such as CD, DVD, removable media such as flash memory (eg. USB sticks or keys), floppy disks, magnetic tape, paper tape, punch cards, standalone RAM disks, Zip drives, removable mass storage, off-line, and similar, other computer memory such as dynamic memory, staticmemory, read / write storage, mutable storage, read only, random access, sequential access, location addressable, file addressable, content addressable, network attached storage, storage area network, bar codes, magnetic ink, and similar.

[0086] The methods and systems described herein may transform physical and / or or intangible items from one state to another. The methods and systems described herein may also transform data representing physical and / or intangible items from one state to another, such as from usage data to a normalized usage dataset.

[0087] The elements described and depicted herein, including in flow charts and block diagrams throughout the figures, imply logical boundaries between the elements. However, according to software or hardware engineering practices, the depicted elements and the functions thereof may be implemented on machines through computer executable media having a processor capable of executing program instructions stored thereon as a monolithic software structure, as standalone software modules, or as modules that employ external routines, code, services, and so forth, or any combination of these, and all such implementations may be within the scope of the present disclosure. Examples of such machines may include, but may not be limited to, personal digital assistants, laptops, personal computers, mobile phones, other handheld computing devices, medical equipment, wired or wireless communication devices, transducers, chips, calculators, satellites, tablet PCs, electronic books, gadgets, electronic devices, devices having artificial intelligence, computing devices, networking equipment, servers, routers and the like. Furthermore, the elements depicted in the flow chart and block diagrams or any other logical component may be implemented on a machine capable of executing program instructions. Thus, while the foregoing drawings and descriptions set forth functional aspects of the disclosed systems, no particular arrangement of software for implementing these functional aspects should be inferred from these descriptions unless explicitly stated or otherwise clear from the context. Similarly, it will be appreciated that the various steps identified and described above may be varied, and that the order of steps may be adapted to particular applications of the techniques disclosed herein. All such variations and modifications are intended to fall within the scope of this disclosure. As such, the depiction and / or description of an order for various steps should not be understood to require a particular order of execution for those steps, unless required by a particular application, or explicitly stated or otherwise clear from the context.

[0088] The methods and / or processes described above, and steps thereof, may be realized in hardware, software or any combination of hardware and software suitable for a particular application. The hardware may include a general-purpose computer and / or dedicated computing device or specific computing device or particular aspect or component of a specific computing device. The processes may be realized in one or more microprocessors, microcontrollers, embedded microcontrollers, programmable digital signal processors or other programmable devices, along with internal and / or external memory. The processes may also, or instead, be embodied in an application specific integrated circuit, a programmable gate array, programmable array logic, or any other device or combination of devices that may be configured to process electronic signals. It will further be appreciated that one or more of the processes may be realized as a computer executable code capable of being executed on a machine-readable medium.

[0089] The computer executable code may be created using a structured programming language such as C, an object oriented programming language such as C++, or any other high-level or low-level programming language (including assembly languages, hardware description languages, and database programming languages and technologies) that may be stored, compiled or interpreted to run on one of the above devices, as well as heterogeneous combinations of processors, processor architectures, or combinations of different hardware and software, or any other machine capable of executing program instructions.

[0090] It will be appreciated by persons skilled in the relevant field of technology that numerous variations and / or modifications may be made to the invention as detailed in the embodiments without departing from the spirit or scope of the invention as broadly described. The present embodiments are, therefore, to be considered in all aspects as illustrative and not restrictive.

[0091] Throughout this specification and claims which follow, unless the context requires otherwise, the word “comprise”, and variations such as “comprises” and “comprising”, will be understood to imply the inclusion of a stated feature or step, or group of features or steps, but not the exclusion of any other feature or step or group of features or steps.

Claims

The claims defining the invention are as follows:

1. A data communications network including connected data communications devices and a method of operating same to determine the positional location of a data communications device operably connected to the network, the method including: receiving, by the one or more processors, a request for positional location determination of a data communications device, the data communications device configured to operably connect with: one or more low orbit satellite(s); one or more Wi-Fi and / or Bluetooth network(s); and / or one or more cell tower(s); retrieving, by one or more processors, data regarding the positional location of the data communications device from the one or more low orbit satellite(s), the one or more Wi-Fi and / or Bluetooth network(s), and / or the one or more cell tower(s); merging, by one or more processors, the retrieved data to form a composite dataset; normalizing, by one or more processors, the composite dataset and removing anomalies to generate a processed dataset; and analysing, by one or more processors, the processed dataset to generate a positional location estimation of the data communications device.

2. A data communications network according to claim 1 , wherein the method further includes: providing, by the one or more processors, in response to the request, the location estimation regarding the location of the data communications device.

3. A data communications network according to either claim 1 or claim 2, wherein the estimation regarding the location of the data communications device includes location co-ordinates.

4. A data communications network according to any one of the preceding claims, wherein anomalies are removed using an anomaly detection technique that dynamically identifies and removes anomalies in the positional location data.

5. A data communications network according to claim 4, wherein the anomaly detection technique includes training one or more machine learning models using historical data such that irregular patterns caused by environmental factors are recognised, the environmental factors including any one or more of: signal interference; weather conditions; terrain; obstacles; or device malfunctions.

6. A data communications network according to any one of the preceding claims, wherein when the data communications device operably connects with data sources including the one or more low orbit satellites, one or more Wi-Fi and / or Bluetooth network(s), and / or one or more cell tower(s), the quality of incoming signals from each data source continuously monitored and assessed such that the data source(s) that provide the most reliable input under current conditions are selected and / or prioritized.

7. A data communications network according to any one of the preceding claims, wherein the method further includes adjusting the precision of the positional location estimation and / or a frequency of generating the estimation according to any one or more of: the device hardware; the operating system of the device, or the battery level of the device.

8. A data communications network according to claim 7, wherein the device hardware is any one of: a smartphone; a laptop; a wearable device; a workstation; ora desktop computer.

9. A data communications network according to either claim 7 or claim 8, wherein the operating system of the data communications device is any one of: iOS;Android; macOS; orWindows.

10. A data communications network according to any one of the preceding claims, wherein the data retrieved and used to generate the positional location estimation further includes data from any one or more of: sensors associated with the data communications device, including from any one or more of: an accelerometer; a gyroscope; a magnetometer; or any other device within a predefined geographical area of the data communications device.1 1. A data communications network according to any one of the preceding claims, wherein the request for determination regarding the location of a first data communications device is: a request received from the first data communications device regarding its location, or a request received from a second data communications device regarding the location of the first data communications device.

12. A data communications network according to any one of the preceding claims, wherein the request for determination regarding the location of a data communications device includes a request to determine whether the data communications device has entered, or is present within, one or more predefined zones.

13. A data communications network according to claim 12, wherein the method further includes: determining, by one or more processors, whether the particular data communications device is located within location co-ordinates defining one or more predefined zones.

14. A data communications network according to either claim 12 or claim 13, wherein the one or more predefined zones represent geographical areas and the method further includes: causing, based on detection of the data communications device within one of the predefined zones, one or more additional actions including notifying a user regarding the location of the data communications device within the one or more predefined zones.

15. A data communications network according to claim 14, wherein notifying the user includes providing the user with information regarding the location of the data communications device.

16. A data communications network according to any one of the preceding claims, wherein the method further includes: prompting, by one or more processors, a user associated with the data communications device to provide substantially real-time feedback regarding the accuracy of the generated location estimation.

17. A data communications network according to claim 16, wherein the method further includes: utilizing, by one or more processors, one or more artificial intelligence techniques to improve subsequent location estimations.

18. A computer-implemented system for determining the positional location of a data communications device, the system including: one or more processors operable to:receive a request for positional location determination of a data communications device, the data communications device configured to operably connect and communicate with: one or more low orbit satellite(s); one or more Wi-Fi and / or Bluetooth network(s); and / or one or more cell tower(s); retrieve data regarding the positional location of the data communications device from the one or more low orbit satellite (s), the one or more Wi-Fi and / or Bluetooth network(s), and / or the one or more cell tower(s); merge the retrieved data to form a composite dataset; normalize the composite dataset and filtering anomalies to generate a processed dataset; and analyse the processed dataset to generate a positional location estimation of the data communications device.

19. A non-transitory computer-readable medium including computer instruction code stored therein, that when executed on one or more processors of a data communications network cause the network to perform the steps of: receiving, by the one or more processors, a request for positional location determination of a data communications device, the data communications device configured to connect and communicate with: one or more low orbit satellite(s); one or more Wi-Fi and / or Bluetooth network(s); and / or one or more cell tower(s); retrieving, by the one or more processors, data regarding the positional location of the data communications device from the one or more low orbit satellite (s), the one or more Wi-Fi and / or Bluetooth network(s), and / or the one or more cell tower(s); merging, by the one or more processors, the retrieved data to form a composite dataset; normalizing, by the one or more processors, the composite dataset and filtering anomalies to generate a processed dataset; and analysing, by one or more processors, the processed dataset to generate a positional location estimation of the data communications device.

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