Technical field

The disclosure herein generally relates to a contained area network and a processor.

Background

The relatively recent availability of massive volumes of information from satellites, aircraft, airborne drones, underwater drones and terrestrial scanners has given rise to widespread need for handling visualising, analysing and other processing. For example, large structures such as buildings, bridges and towers are commonly imaged with airborne drones to perform routine maintenance inspections or to assess damage in areas that are otherwise difficult to reach.

Landscapes are imaged for many reasons, for example, to survey a landform, measure volumes, digitize features and to inspect crops on a farm.

Photogrammetry is the process of taking measurements from photographs. Modern

photogrammetry involves processing photographs with photogrammetry software and may include 3D reconstruction from multiple 2D images.

Visualisation, analysis and other information processing software may be installed on a personal computing device, for example a desktop computer, or accessed via a cloud-based architecture.

The software and data may be accessible by only one computer at a time. A separate software installation may be required for each additional computer. Each additional installation may be associated with the cost of an additional software licence and the cost of another desktop computer. Smaller computing devices, for example tablets, may not have sufficient computing resources, however, for processing the information.

When using a cloud-based architecture, photogrammetry and visualisation software may be hosted on a remote server and accessed over the internet via a web browser. Browser-enabled computing devices can access the software, for example tablets, smart phones, and laptops.

However, there are some serious drawbacks with a cloud-based architecture. Firstly, users may be required to upload their images and data to the cloud, which often requires very high bandwidth. Some users may not wish to upload their images and data to the cloud. Example reasons for not wishing to upload images and data to the cloud include confidentiality and security. For example, the data may reveal confidential information such as:

• the location of a prospective mining site (which could be used by competitors)

• details of a military asset (which could be used by enemies)

• details of public asset such as a power station or bridge (which could be used by

terrorists).

Users may also have concerns that the software host may claim ownership rights to the data.

Another drawback with cloud-hosted software is that it can only be accessed where there is an Internet connection. People working at remote locations (such as prospective mining site) may not have access to the internet. Also, an area that has been hit with a natural disaster (e.g.

earthquake, flood, cyclone) may be disconnected from the internet. It may be crucial to quickly analyse drone images of the local area. In the absence of an Internet connection, the only options are to travel to somewhere that has internet access, or to bring a desktop computer with a local copy of the software.

It may be desirable to overcome at least some disadvantages, or provide consumers with a choice.

Summary

Disclosed hererin is a contained area network. The contained area network comprises a processor comprising a contained area network interface and processor readable tangible media including program instructions which when executed by the processor causes the processor to generate processed geospatial information by processing geospatial information and send the processed geospatial information via the contained area network interface. The contained area network comprises a plurality of personal computing devices comprising a plurality of contained area network interfaces and configured to receive from the processor via the plurality of contained area interfaces the processed geospatial information.

In an embodiment, the program instructions comprise photogrammetry program instructions.

In an embodiment, the program instructions comprise visualisation program instructions.

In an embodiment, the processor readable tangible media includes the geospatial information. In an embodiment, the geospatial information comprises geospatial image information.

In an embodiment, each of the plurality of personal computing devices are configured to generate zoom level information indicative of a selected magnification of a geospatial image, and send the zoom level information to the processor, and the processed geospatial information comprises geospatial image information generated using the zoom level information.

In an embodiment, the geospatial image information comprises overlaid graphic information.

In an embodiment, each of the plurality of personal computing devices comprise personal computing device tangible media including program instructions which when executed by any one of the plurality of personal computing devices causes the personal computing device to generate a geospatial image using the geospatial image information.

In an embodiment, the geospatial image is a three dimensional geospatial image.

An embodiment comprises at least one contained area network interface dongle.

An embodiment comprises at least one of a local area network (LAN) and a personal area network (PAN).

In an embodiment, the processor comprises a ruggedized server.

Disclosed herein is a processor comprising a contained area network interface and processor readable tangible media including program instructions which when executed by the processor causes the processor to generate processed geospatial information by processing geospatial information and send the processed geospatial information via the contained area network interface.

In an embodiment, the program instructions comprise photogrammetry program instructions.

In an embodiment, the program instructions comprise visualisation program instructions.

In an embodiment, processor readable tangible media comprises the geospatial information. The geospatial information may comprise geospatial image information.

An embodiment is configured to receive zoom level information indicative of a selected magnification of a geospatial image, wherein the processed geospatial information comprises geospatial image information generated using the zoom level information. The geospatial information may comprise overlaid graphic information. The geospatial image information may comprise three geospatial dimensions.

Disclosed herein is non-transitory processor readable tangible media including program instructions which when executed by a processor causes the processor to perform a method disclosed herein.

Disclosed herein is a computer program for instructing a processor, which when executed by the processor causes the processor to perform a method disclosed herein.

Any of the various features of each of the above disclosures, and of the various features of the embodiments described below, can be combined as suitable and desired.

Brief description of the figures

Embodiments will now be described by way of example only with reference to the

accompanying figures in which:

Figure 1 shows a schematic diagram of an embodiment of a contained area network. Figure 2 shows a schematic diagram of a processor of figure 1.

Description of embodiments

Figure 1 shows a schematic diagram of an embodiment of a contained area network (“network”) in the form of a local area network, the network being generally indicated by the numeral 10. In the context of the present document, a contained area network is a network or internetwork that does not comprise a network having a spatial scope that is greater than a local area network (LAN). Examples of contained area networks include a LAN, a Near-me network (NAN), a personal area network (PAN), a body area network (BAN), and a network comprising any two or more of a LAN, NAN, PAN and BAN. A network or internetwork comprising a wides area network (WAN) or network of greater spatial scope is not a contained area network. The network comprises a processor 12, a schematic diagram of which is shown in figure 2. The processor 12 comprises a contained area network interface 18 in the form of an Ethernet interface and processor readable tangible media 16 including program instructions which when executed by the processor 12 causes the processor to generate processed geospatial information by processing geospatial information and send the processed geospatial information via the contained area network interface 18. The geospatial information may be in the form of images and data from satellites, airborne drones, underwater drones, and terrestrial scanners, in relation to geography including landscapes, buildings and structures. The geospatial information may generally have two spatial dimensions (“two dimensional”) or have three spatial dimensions (“three dimensional”). The geospatial information may have a time dimension, but it may not. The network 10 comprises a plurality of personal computing devices 20, 22, 24. The plurality of personal computing devices comprises a plurality of contained area network interfaces 28, 30, 32 configured to receive from the processor 12 the processed geospatial information.

The processor 12 is in the form of a computer, examples of which include but are not limited to a HP Z2 mini workstation, a HP VR backpack - a wearable computer - or generally any suitable computer or processor. In the present embodiment, the computer 12 is configured as a local area network server. The plurality of personal computing devices 20,22,24 comprise computing devices in the form of a tablet computer 22,24 and a smartphone 32, however they may comprise laptop computers, desk top computers or generally any suitable form of personal computing device. The processor readable tangible media 16 includes the geospatial information, however it may be in another device. For example the network 10 may comprise network attached storage including the geospatial information, or the geospatial information may be in peripheral storage (for example an external solid state drive). Generally, but not necessarily, the geospatial information comprises geospatial image information, for example digital aerial photographs.

In the present embodiment, the network 10 is in the form of a local area network comprising at least one of a wireless network component (e.g. IEEE 802.11“Wi-Fi”, as defined by documents available on 1 June 2019 from the Institute of Electrical and Electronics Engineers) and a wired network component (e.g. IEEE 802.3 (“Ethernet”), as defined by document available on 1 June 2019, FibreChannel, InfiniBand and PCIe networks). The network comprises a wired IEEE 802.3 link 46 between a wireless access point (“WAP”) 34 in the form of a Wi-Fi WAP and the processor 12. The plurality of personal computing devices are each in wireless communication with the WAP 34 and through a wireless link 44, the WAP 34, and the wired link 46 the processor 12. Alternatively, the processor may be wireless connected to the plurality of personal computing devices 22,24,26 via the wireless access point, or the processor and the plurality of physical layers may be connected via Ethernet cables and an Ethernet switch or hub, for example. Generally, any suitable network configuration may be used. The network may additionally comprise a personal area network (PAN) in the form of, for example, a Bluetooth or generally any suitable PAN. Alternatively, the network 10 may be in the form of a Bluetooth network. The network 10 comprises a router 42 comprising the wireless access point 34. The network 10 may be connected to the internet be plugging the router 42 into an internet wall socket, for example, however the network 10 can still operate when not connected to the internet. When connected to the internet, remote personal computing devices 48 can communicate with the processor 12. Embodiments may not be configured to be in communication with the internet, for example may not comprise a suitable router. Generally, any suitable form of contained area network may be used. Generally, each of the processor 12 and the plurality of personal computing devices 20,22,24 each have an integral contained area network interface, however any one of the processor 12 and the plurality of personal computing devices 20,22,24 may have received a contained area network interface dongle, for example a Wi-Fi dongle. The processor 12 may be a server on a private cloud-based architecture in a secure corporate environment.

The program instructions comprise at least one of photogrammetry program instructions and visualisation program instructions. The photogrammetry program instructions can at least one of determine dimensions and measurements from a plurality of images having only two spatial dimensions (e g a photograph) stored on the tangible media 16, and reconstruct objects

(including geographical objects and landscapes) from the plurality of images stored on the tangible media.

Each of the plurality of personal computing devices 22,24,26 are configured to generate zoom level information indicative of a selected magnification of a geospatial image, and send the zoom level information to the processor 12. The zoom level is selected by a user manipulating a user interface or on a computing device 20,22,24. The processed geospatial information comprises geospatial image information generated using the zoom level information. The geospatial image information can comprise in the present by not all embodiments overlaid graphic information. Each of the personal computing devices 22,24,26 comprise browser software (e.g. INTERNET EXPLORER, SAFARI, or CITROME). The image information is displayed by the browser when running. The browser uses the hypertext transfer protocol (HTTP) to communicate with the processor 12, in addition to the transmission control protocol (TCP) and internet protocol (IP). Any suitable communication protocols may be used.

Programme instructions in the form of visualisation software stored in the processor’s memory creates visualisation information for a plurality of visualisations of the parent object (“tiles”) for more than one zoom level and more than one viewing angle. A browser may assess the location and view angle selected by the user and find a visualisation (“tile”) relevant to display the user selected view of the model on the browser. This may enable massive highly detailed maps and models to be viewed on the plurality of personal computing devices (which may be low computational power computer) with a web browser. The browser, front end, makes calls on the back end for the relevant data. This can also include merging views with multiple data types. Each of the plurality of personal computing devices comprise personal computing device tangible media including program instructions which when executed by any one of the plurality of personal computing devices causes the personal computing device to generate a geospatial image using the geospatial image information. The geospatial image has three spatial dimensions, however it may have less or more dimensions.

The IEEE 802.3 standards, for example, define the transmission of protocol data units (PDUs) including Ethernet frames and Ethernet packets over a network physical medium in the form of, for example, a network cable, backplane lane, or another suitable network medium that connects two nodes of the network. A network cable may be, for example:

• An electrical network cable in the form of a twinaxial network cable, copper network cable, or twisted pair, for example, or

• an optical fibre network cable in the form of single mode or multimode optical fibre, for example.

A standard, for example as defined by IEEE 802.3, FibreChannel, InfiniBand and PCIe standards, may define network electrical and/or optical connections and mechanical connections at the physical level. An Ethernet network node or device generally comprises a system (PHY) compliant with the IEEE 802.3 standard, and is in communication with a media access controller (MAC) of the data link layer, that defines a MAC address for the node or device, and which is responsible for the sending a frame of data from one node of the network to another via the physical layer. The frame is a payload of an Ethernet packet defined at the physical layer. Each end of the network physical medium is connected to an interface of a respective node. The interface comprises a medium attachment unit (MAU) in the form of at least one

communications port of a respective node, which may comprise a transceiver, a receiver or a transmitter, and which may provide a mechanical connection and a communication connection between the node and the network medium. A transceiver may comprise a transceiver module in the form of, for example, a pluggable 10 GE Small Form Factor Pluggable transceiver (10 Gb/s SFP+), a XENPAK transceiver, a XFP transceiver, an embedded PHY receiver, or generally any suitable 10 GE or other type of transceiver. The transceiver may be received in a transceiver socket, the received transceiver being selected for the selected network physical medium.

Embodiments may have a 10 GE receive PHY system and a 10 GE transmit PHY system.

The payload of an Ethernet frame may comprise information, for example within a payload of a TCP protocol data unit (“segment”) that is the payload of the Ethernet frame. Example: private virtual reality

The contained area network 10 may generally enable multiple users to interact with geospatial information (which may be stored on the processor 12) as a virtual reality experience, however other embodiments do not necessarily have this feature. The processor 12 hosts a virtual reality application which uses the geospatial data to generate a virtual reality environment. The geospatial data may be data that has been measured from the real world, or it may be data from the real world that has been modified, or it may be data which has been generated entirely artificially. The network 10 enables geospatial data to be viewed or processed, within a corporation or with controlled external access, by multiple users without using an internet service, and without sharing the data with a third-party cloud host. Several scenarios are now described, in which example used and configurations of the contained area network :

Scenario 1: natural disaster area. Drone footage of an area can be processed by the processor 12 into 3D visualisations and viewed by multiple local search and rescue workers using personal computing devices 20, 22, 24 without an internet service. The confined area network may help to find and victims or repair damage sooner.

To quickly map a disaster area may require a large volume of aerial photos captured by drones, for example, to be processed by the processor 12.

The contained area network 10 enables multiple drone operators to upload data to the processor 12, which may be at the natural disaster area for rapid access to the required data services. Three dimensional inspection models generated by the processor 12 are generally but not necessarily made available to multiple search and rescue personnel via the plurality of personal computing devices 20, 22, 24.

Scenario 2: virtual training. Police or military can use the confined area network 10 to visualise an area or a building before arriving at a site with a live situation or for training, for example. Three dimensional models of a site, derived previously from drone or aerial data, could be stored on the server or copied to it prior to deployment to an incident or training event. Personnel with authority to access the data can navigate around relatively high resolution models of the site using low powered field computers and tablets. The models may be true to scale and location, with high levels of detail over large areas.

Data can be captured from at least one drone, for example, and processed by processor 12 into models to add details to a visualisation. Scenario 3: secret location. The contained area network 10 can be used for analysising a secret area or structure by multiple trusted users of the contained areas network 10, without sharing the data with a third-party cloud host. The data may be kept off the cloud, which may otherwise be a security or confidentiality concern.

Data may be kept on the contained area network 10, which may be a private network of, for example, a company. The data may be available to authorised users using the plurality of personal computing devices 20, 22, 24.

Scenario 4: farmers. The contained area network I bean assist farmers to visualise crop data and better manage crops without an internet connection. Farmers can acquire geospatial information such as satellite imagery and analytics (via couriered storage media or an internet connection when available), for example to assist with advanced crop management such as targeted weed and pest control, waste management and general crop health determination. The contained area network 10 at a field or farm, for example, may assist the farmer to access data to relatively high levels of details, and add data to the virtual site using just a tablet or low powered computer.

Scenario 5: Surveyors. The contained area network 10 can assist surveyors to acquire, process and access data without an internet connection. A surveyor can capture photographs with at least one drone on a remote site, load the images onto a processor, which may process the data into three dimensional models using a light field computer. The quality of the field data can be validated before returning to an office. Data can continue to be processed while in transit, for example back to an office. Once in the office, for example, the data can be send to the contained area network 10.

Scenario 6: customised gaming. The system enables 3D virtual models of specific areas to be created for a gaming environment. Photographs from a drone can be processed into three dimension models, or pre-existing models can be loaded onto the processor 12 to be used in a personalised gaming environment. Processor 12 can create the local scene for gaming use either at the scene location or elsewhere.

Application: private augmented reality system

The same system enables multiple users to interact with geospatial data as an augmented reality experience i.e. graphics overlaid on camera vision of the real world. To enable augmented reality, each mobile device must have a camera and must transmit the GPS location and orientation of the device to the server so that graphics can be generated for the area being viewed.

Examples of software functions

Functions that may be performed by example program instructions that can be stored in the processor’s 12 memory software include:

• 3D and 4D (time based) multi-source data fusion and visualization. Any suitable type of geospatial data can be processed by the contained area network. The geospatial data is generally but not necessarily tiled, or cut up into detailed views and different zoom levels, enabling the relatively high detail to be seen of massive files covering large areas, using a browser application. Multiple data types can be viewed and merged together on a browser application.

• User management, authentication, access control and collaboration. The contained area network 10 enables account administrators to control access of users to data, both internally by creating groups of people in projects, and externally by creating hyperlinks to the project.

• Linking to an existing database, or creating a new one. API integration with external database products can add external contextual data to a project or add a project to data in an external database product.

• Connecting to user-specific processing and analytic software. API connectivity can push data to external processing software and services, and to have the resultant data returned to the proj ect.

• Connecting to user specific processing hardware or server. API connectivity can be used to access external software running on another processor within the contained area netowrk.

• File and project management. Data can be added to an account, folders created, data moved between folders, and data and folders deleted. Projects can be created with a subset of data and users with permission to act on the data.

• Links to user trusted local or global data storage service. Data can be imported from local or cloud storage providers with API credentials to the external accounts.

• Near real-time field based photogrammetry processing (photo to 3D production and visualization). Resource intensive photogrammetry processing on a high powered field server is possible, which can enable data processing at the point of acquisition. • 3D and 4D asset condition inspection and tagging. Inspection of assets such as cell towers, bridges and buildings, is possible, with a digital twin virtual reality model linked to high resolution inspection photos.

• 3D measurements and feature extraction. Multiple users can use the contained area

network 10 to simultaneously mark and measure points, lines, polygons (areas) and volumes and extract the markups (digitize) with real world coordinates.

• SDK and API for mobile, web and desktop application development. External developers can customize the product for their company’s specific applications.

• Automated software update using internet or self-deployable package. Software can manage and update products on cloud SaaS or deployed local installations.

Now that embodiments have been described, it will be appreciated that some embodiments have at least some of the following advantages:

• Users may use a range of computing devices such as tablets, even though the data

typically requires high computing power to access, visualise and process.

• Users may keep their geospatial data confidential by storing and processing data on their own server, while still enabling sharing and collaboration within the organisation.

• Users may have access to software in places where there is no internet connection, for example natural disaster sites, and consequently data may not need to be uploaded to a cloud service.

• Multiple users may access the data, which may be massive geospatial data, and software, and may use small devices without an internet connection to do so.

• Data access is not restricted to a single machine.

Variations and/or modifications may be made to the embodiments described without departing from the spirit or ambit of the invention. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive. Reference to a feature disclosed herein does not mean that all embodiments must include the feature.

Prior art, if any, described herein is not to be taken as an admission that the prior art forms part of the common general knowledge in any jurisdiction.

In the claims which follow and in the preceding description of the invention, except where the context requires otherwise due to express language or necessary implication, the word “comprise” or variations such as“comprises" or“comprising" is used in an inclusive sense, that is to specify the presence of the stated features but not to preclude the presence or addition of further features in various embodiments of the invention.