Patent Description:
Shipping yards may be massive, covering many acres of land. Further, in yards such as rail yards, trailer yards or shipping yards, the yards may shift over time. They may overflow into adjacent areas, fields or parking lots. They may also shrink. Yards may grow out or up, and they may "move" over time, for example into lanes and alleys, parking locations may drift among other challenges.

One issue in managing yards of trailers or containers is locating the suitable trailer for the next load. Typically, yard managers know which trailers are empty or full based on yard location or memory, and they may direct a shunt driver to obtain an empty or full trailer and deliver it to the front of the yard to be ready for transport.

A shunt vehicle is basically a vehicle that can pick up a trailer or container and pull it or carry it to the front of the yard for dispatch.

One issue is that, upon being instructed to shunt a trailer or container, the target is often not at its specified location. Furthermore, location technologies such as GPS can be inaccurate by <NUM>, <NUM> or even <NUM> meters, depending on signal strength and power use of the GPS receiver.

If a shunt vehicle is dispatched to a location incorrectly, it may waste time. In the real world, in many cases the driver of the shunt vehicle can spend <NUM> to <NUM> minutes searching for a container or radioing back for a lost container. Further, for future autonomous vehicles, incorrect dispatching of such vehicle wastes fuel energy, adds traffic to the yard as well as wasting time for other dispatching jobs. The relevant state of the art is represented by <CIT>, <CIT> and <CIT>. <CIT> discloses detection and correction of inventory data errors in inventory tracking databases and/or systems indicating the location of the containers. <CIT> discloses operating at least one camera to create an image of a container by an apparatus on a container handler for use in estimating the container's code. <CIT> discloses systems and methods for real time monitoring of the location of shipping objects at or about transit terminal using a vision based tracking system.

The present invention provides a method as detailed in claim <NUM>. Also provided is a server according to claim <NUM> and computer readable medium according to claim <NUM>. Advantageous features are provided in the dependent claims.

<FIG> is a block diagram of an example simplified computing device that may be used with the examples of the present disclosure.

Specifically, the present disclosure provides for the use of an image sensor apparatus affixed to trailers or shipping containers to create a network of cameras within the container yard, and then use the network of cameras to validate the locations of containers before dispatch. Such examples work even if not every container is equipped with such image sensor apparatus. As provided below, even if a penetration is relatively low, such as <NUM>%, since such asset tracking devices may be spread across the yard there are many potential cameras that can be used to try and obtain the actual view of the target container.

Further, supplemental information such as the location of the image sensor apparatus, compass direction of the field of view of the image sensor apparatus, among other information, is combined with captured images in some cases.

Captured images may be provided to a central station in which a computer can then determine if the trailer in question is actually at its anticipated location. The captured image may be from surrounding trailers. If human processing is used, the image from the image data may be provided on a user interface. If machine processing is used, optical scanning may be used to read information from containers within the image. Such information may include license plates, identifier information written on the trailers, colors of trailers, or other identifying information.

Utilizing the examples above, the shunt vehicle is only dispatched to a location after a confirmation is made that the trailer or container is where it is expected, thereby saving resources for the yard management.

If a container is not located where it is expected, a search for the container can be expanded by obtaining images from other image capture apparatuses in the container yard. The search for the container may utilize an expanding network of image sensor apparatuses, for example, until the container is found.

Such examples are described in more detail below.

Reference is now made to <FIG>, which shows a simplified environment of a storage yard <NUM>. Storage yard <NUM> includes a plurality of shipping containers <NUM>. In some cases, the shipping containers <NUM> may be within a fenced area <NUM>. However, due to the dynamic nature of the shipping yard, some containers, shown with reference <NUM>, are outside of the fenced area <NUM>. Further, in many cases storage yard <NUM> may simply be too big to have a fenced area <NUM>.

Fixed infrastructure points within the storage yard <NUM> may exist. For example, a building <NUM> or a fixed structure <NUM> such as a lamppost, security pole, or crane, among other options, may exist within the storage yard <NUM>.

Shipping containers <NUM> or <NUM> may be placed in rows, or stacked, or simply deposited in an empty location.

In accordance with one aspect of the present disclosure, a dynamic and distributed image capture system is provided. In particular, a subset of containers <NUM> or <NUM> may have associated therewith an image sensor apparatus that can be triggered to start or stop capturing images and communicate the results to a centralized server.

Such image sensor apparatus may be a power limited device, such as a battery-operated device, to allow the system to be deployed without a fixed power supply. However, because the image capture device is power limited, it cannot continuously capture images without quickly draining the battery or otherwise taxing the power source.

The image sensor apparatus uses fleet management tracking devices on the shipping containers <NUM> or <NUM>. Specifically, shipping containers or truck trailers are equipped with sensors that have communication capabilities and provide information about such shipping container or trailer. For example, the sensors may provide temperature readings, location readings through a positioning system such as the global positioning system (GPS), vibration sensors, accelerometers, gyroscopes, among other sensor information.

Reference is now made to <FIG>, which shows an example image sensor apparatus <NUM>. Image sensor apparatus can be any computing device or network node. Such computing device or network node may include any type of electronic device, including but not limited to, mobile devices such as smartphones or cellular telephones. Examples can further include fixed or mobile devices, such as internet of things devices, endpoints, home automation devices, medical equipment in hospital or home environments, inventory tracking devices, environmental monitoring devices, energy management devices, infrastructure management devices, vehicles or devices for vehicles, fixed electronic devices, among others.

Image sensor apparatus <NUM> comprises a processor <NUM> and at least one communications subsystem <NUM>, where the processor <NUM> and communications subsystem <NUM> cooperate to perform the methods described herein. Communications subsystem <NUM> may comprise multiple subsystems, for example for different radio technologies.

Communications subsystem <NUM> allows device <NUM> to communicate with other devices or network elements. Communications subsystem <NUM> may use one or more of a variety of communications types, including but not limited to cellular, satellite, Bluetooth™ Bluetooth™ Low Energy, Wi-Fi, wireless local area network (WLAN), near field communications (NFC), Zigbee, wired connections such as Ethernet or fiber, among other options.

As such, a communications subsystem <NUM> for wireless communications will typically have one or more receivers and transmitters, as well as associated components such as one or more antenna elements, local oscillators (LOs), and may include a processing module such as a digital signal processor (DSP). As will be apparent to those skilled in the field of communications, the particular design of the communication subsystem <NUM> will be dependent upon the communication network or communication technology on which the image sensor apparatus is intended to operate.

Processor <NUM> generally controls the overall operation of the image capture device <NUM> and is configured to execute programmable logic, which may be stored, along with data, using memory <NUM>. Memory <NUM> can be any tangible, non-transitory computer readable storage medium, including but not limited to optical (e.g., CD, DVD, etc.), magnetic (e.g., tape), flash drive, hard drive, or other memory known in the art.

Alternatively, or in addition to memory <NUM>, image sensor apparatus <NUM> may access data or programmable logic from an external storage medium, for example through communications subsystem <NUM>.

In the example of <FIG>, image sensor apparatus <NUM> may utilize a plurality of sensors, which are part of image sensor apparatus <NUM>. For internal sensors, processor <NUM> may receive input from a sensor subsystem <NUM>.

Examples of sensors in the example of <FIG> include a positioning sensor <NUM>, a vibration sensor <NUM>, a temperature sensor <NUM>, one or more image sensors <NUM>, accelerometer <NUM>, light sensors <NUM>, gyroscopic sensors <NUM>, and other sensors <NUM>. Other sensors may be any sensor that is capable of reading or obtaining data that may be useful for image sensor apparatus <NUM>. However, the sensors shown in <FIG> are merely examples, and in other examples different sensors or a subset of sensors shown in <FIG> may be used.

Communications between the various elements of image sensor apparatus <NUM> may be through an internal bus <NUM>. However, other forms of communication are possible.

Image sensor apparatus <NUM> is affixed to shipping containers, rail cars, truck trailers, truck cabs. As used herein, a container can include any shipping container, rail car, truck trailer, truck cab or vehicle.

Such sensor apparatus <NUM> may be a power limited device. For example image sensor apparatus <NUM> could be a battery operated device that can be affixed to a shipping container or trailer. Other limited power sources could include any limited power supply, such as a small generator or dynamo, a fuel cell, solar power, among other options.

Sensor apparatus <NUM> may utilize external power, for example from the engine of a tractor pulling the trailer, from a land power source for example on a plugged in recreational vehicle or from a building power supply, among other options.

External power may further allow for recharging of batteries to allow the sensor apparatus <NUM> to then operate in a power limited mode again. Further, recharging methods may also include other power sources, such as, but not limited to, solar, electromagnetic, acoustic, or vibration charging.

Referring again to <FIG>, where the sensor apparatus <NUM> from <FIG> is affixed to a plurality of the shipping containers <NUM> then a dynamic network for the capturing of images may be created as described below. Specifically, assuming that the image sensor apparatus <NUM> is installed on a number of cargo containers or shipping containers, then even at low penetration rates a given yard may have a number of cameras. For example, even at penetration rates of <NUM>%, <NUM>% or <NUM>%, a yard that has a hundred or a thousand shipping containers will have many cameras that are available for container location and mapping.

Due to the nature of the storage yard <NUM>, the cameras would likely be distributed around the yard. Further, since shipping containers may be stacked or parallel or perpendicular or at other angles to each other, the image capture mechanism may provide various angles to allow for a comprehensive container location mapping and verification system, as described below.

Reference is now made to <FIG>. which shows one example architecture that may be utilized in accordance with the present disclosure. In particular, the example architecture of <FIG> has three movable image sensor apparatuses, namely image sensor apparatus <NUM>, image sensor apparatus <NUM>, and image sensor apparatus <NUM>.

Further, a plurality of fixed image sensor apparatus may exist within the network. These are shown, for example, as fixed sensor apparatus <NUM> and fixed sensor apparatus <NUM>.

In the example of <FIG>, the movable sensor apparatuses <NUM>, <NUM> and <NUM> communicate through an access point <NUM> or base station <NUM>, and thereby can communicate over a wide area network such as the Internet <NUM>. In other examples, the movable sensor apparatuses <NUM>, <NUM> and <NUM> may communicate through other mechanisms over Internet <NUM>, such as a fixed connection or any other wired or wireless communications.

Further, fixed sensor apparatus <NUM> and fixed sensor apparatus <NUM> may communicate with access point <NUM> or base station <NUM>. In other examples, the fixed sensor apparatus <NUM> and/or fixed sensor apparatus <NUM> may communicate through other mechanisms over Internet <NUM>, such as a fixed connection or any other wired or wireless communications.

While the example of <FIG> only shows one access point <NUM>, in other examples a plurality of access points may be provided within a container yard.

Further, the information from any of sensor apparatus <NUM>, <NUM>, <NUM>, <NUM> and <NUM> may be provided to one or more servers <NUM> or <NUM>. For example, if the sensor apparatus <NUM> and <NUM> belong to a first company, such apparatus may communicate with a first company's server <NUM>. Sensor apparatus <NUM> may belong to a second company and may therefore communicate with a second company's server <NUM>.

A single company may have a plurality of servers. A server, central server, processing service, endpoint, Uniform Resource Identifier (URI), Uniform Resource Locator (URL), back-end, and/or processing system may be used interchangeably in the descriptions herein. The server functionality typically represents data processing/reporting that are not closely tied to the location of movable image capture apparatuses <NUM>, <NUM>, <NUM>, etc. For example, the server may be located essentially anywhere so long as it has network access (e.g., <NUM>) to communicate with image capture apparatuses <NUM>, <NUM>, <NUM>, etc..

In accordance with one example of the present disclosure, the various fixed or mobile sensor apparatuses may also communicate with each other. Thus, apparatus <NUM> may communicate directly with apparatus <NUM> or apparatus <NUM>. Further, apparatus <NUM> may communicate with fixed apparatus <NUM> or <NUM>.

Further, the owners of the servers <NUM> and <NUM> may have agreements to allow communication between such servers.

The example architecture of <FIG> is merely provided for illustration purposes and is not limiting to any particular apparatus or architecture. For example, in some cases apparatus <NUM> may only be able to communicate with apparatus <NUM> since they are owned by the same company. In other cases, apparatus <NUM> could communicate with apparatus <NUM> if there is an agreement for security purposes. In other cases, apparatus <NUM> may not be able to communicate directly with apparatus <NUM> since the distance between the two may be too far to allow for such communications.

In other cases, apparatus <NUM> may be out of range of access point <NUM> and may therefore utilize another apparatus such as apparatus <NUM> as a relay for providing information to server <NUM>.

As described above, in many cases, an image sensor apparatus may be a limited power device. For example, the device may operate using a battery. Because of the limited power, the image sensor apparatus does not continually capture images. Continual image capture would drain the battery far too quickly and provide information which may not be relevant most the time. Thus a sensor apparatus may act based on a trigger. As described below, the trigger may be an indication from other sensors of the sensor apparatus that the container has stopped moving for a threshold time period, a message from a network node or another sensor apparatus requesting image data, among other options.

Preliminarily data on the location of a container may be based on manual mapping, rough GPS fixes, or based on dynamic mapping. A network server builds a map of a shipping yard that may be dynamically updated over time. Such map is used as a preliminary location tool to find a particular shipping container.

Reference is now made to <FIG>, which shows a process at an image sensor apparatus on a shipping container to facilitate the creation of a map. The process of <FIG> starts at block <NUM> and proceeds to block <NUM> in which a check is made to determine whether a trigger condition has been met. In particular, the map may need to be updated once preconditions are met. For example, if the shipping container has stopped moving for a threshold period of time, for example <NUM> minutes, then this may indicate that the shipping container is in its final position and thus a cause a trigger to capture images. In other cases, supplemental information such as global positioning system data may be further used with the trigger conditions to ensure that the shipping container is within a trailer yard. Thus, if the shipping container has entered into a geofenced area around the shipping yard, this may indicate that the image capture may be needed. Conversely, if the trailer is located outside of the geofenced area then the shipping container stopping for <NUM> minutes may merely indicate that the driver is a rest period at a rest station or at a location outside the shipping yard and therefore image capture may not be required. Other examples of triggers are possible.

If the threshold is not met at block <NUM>, the process proceeds back to block <NUM> and continues to loop until a threshold condition is met.

From block <NUM>, once the threshold condition is met, the process proceeds to block <NUM> in which the sensor apparatus captures an image.

The process then proceeds to block <NUM> in which the sensor apparatus uses its communication system to send the image to a server. Other supplemental data are also sent to a server. Supplemental data at block <NUM> may include various information, including identifying information for the image sensor apparatus, a last GPS fix captured by the apparatus, or the direction that the container is facing for example derived from an internal compass type sensor on the image capture apparatus, among other information.

From block <NUM> the process then proceeds to block <NUM> and ends.

On the server side, the server maintains a map and dynamically updates the map based on image capture data from a plurality of image sensor apparatuses. Specifically, the process at the server is shown with regard to <FIG> and starts at block <NUM>. The process then proceeds to block <NUM> in which the image data, as well as supplemental data, is received at the server.

The process then proceeds to block <NUM> in which the image data is used to determine the location of the container. The step at block <NUM> may involve providing information on a user interface of a computing device to have an operator determine from various information within the image the location of the trailer. Such information may, for example, include images of fixed structures, other containers within the image that have a known location, among other such information. Further, supplemental information such as the position data or the bearing data of the image sensor is used to narrow the possible locations of such container.

The step at block <NUM> may use optical recognition or other automatic processing to determine the location of the container. For example, such optical recognition may use optical character recognition to determine the neighboring shipping containers based on identification printed on such shipping containers. Further, the optical recognition may utilize a database of images of known fixed structures within such container yard in order to determine the location of the container in question. Optical recognition may be supplemented with the supplemental data to focus the image processing.

In either the human or automatic processing of the image, the use of the neighboring trailers may use two or more trailers to be identified and correlated with map data stored on the server. This may be used to ensure that a neighboring trailer has not been moved and is thus producing an incorrect location result.

From block <NUM>, the process may optionally proceed to block <NUM> in which image processing is used on the remainder of the image to verify the location of other containers. For example, if an image contains data for six containers, if one of such containers is not in its anticipated location, the processing at block <NUM> may identify the new location of such container and update the map within the server to provide the correct location of such container.

From block <NUM> or block <NUM>, the process may proceed to block <NUM> in which the map data within the server is updated.

The process then proceeds to block <NUM> and ends.

The maintenance of the map at the server may request image information from various image sensor apparatuses periodically to ensure map integrity.

In other cases, map data may be updated upon dispatching a shunt vehicle.

Once a trailer needs to be obtained from the yard, a shunt vehicle may be dispatched to obtain the trailer. However, prior to the dispatching of such a shunt vehicle, the location of the trailer may be verified.

The verification of the location of the container may be done utilizing a map as created in the examples described with regard to <FIG> and <FIG> above, or may be based on manual mapping, GPS data or other location based techniques if no such map exists. However, prior to dispatch, the verification of the location of the container is made.

Reference is now made to <FIG>, which shows a process at a sensor apparatus device for use with the verification of the location of the container. The process of <FIG> starts at block <NUM> and proceeds to block <NUM> in which the image sensor apparatus may receive a request to capture an image. As will be appreciated, the image sensor apparatus may have a communication system which does not continuously listen to a communication channel. This may be done to save battery resources on the device if the device is a power limited device.

Therefore, the image sensor apparatus may periodically wake up the radio on the device to listen for requests and then resume a sleep state if no request is received during the opportunity window.

The request received at block <NUM> may come from a server, directly through an access point that the image sensor apparatus has registered with. In other examples, a second image sensor apparatus may be used as a relay, for example if the image sensor apparatus in question is out of coverage of an access point.

In the example of <FIG>, a request is received during the opportunity window at block <NUM> and the process proceeds to block <NUM> in which an image capture occurs.

The process then proceeds to block <NUM> in which the captured image, and other supplemental information such as bearing or GPS location, are returned to the server. The process then proceeds to block <NUM> and ends.

At the server, an example process is shown with regard to <FIG>. The process of <FIG> starts at block <NUM> and proceeds to block <NUM> in which an image request is made to a particular image sensor apparatus. Such image request may be continually or periodically made until a response is received.

A response to the image request is received at block <NUM>. The response includes the received image and other supplemental information.

The process then proceeds from block <NUM> to block <NUM> in which the image is processed. Such image processing may, for example, merely compare the image received at block <NUM> with a previously stored image that was created, for example during a mapping process. If the images match, then the location of the shipping container has not changed. It should be noted that other factors within the image may change, such as the lighting, or the location of some of the shipping containers in the view of the image capture apparatus. However, if the image processing at block <NUM> determines the two images are sufficiently similar then it can be assumed that the location has been maintained.

From block <NUM> the process proceeds to block <NUM> in which a check is made to determine whether the container is in the expected location. If not, the process may then proceed to block <NUM> in which the location of the container is determined. For example, such determination at block <NUM> can be similar to the determination made at block <NUM> of <FIG>.

From block <NUM>, if the container is in the expected location, or based on the new location determined at block <NUM>, the process proceeds to block <NUM> in which the shunt vehicle is dispatched to the now verified location of the shipping container. The process then proceeds to block <NUM> and ends.

The target container may not have an image capture apparatus, or the image capture apparatus on the container may be obscured for some reason. Instead of capturing the image from the target container itself, image capture occurs based on surrounding sensor apparatuses.

A shipping yard maintains a map such as a map shown at <FIG>, indicating the various sensor apparatuses that exist, including the bearing of such sensor apparatuses. Referring to <FIG>, the direction of each sensor apparatus <NUM> is shown. Therefore, based on either the mapping created with regard to <FIG> and <FIG>, or based on manual mapping or GPS data, a location or potential location of the shipping container can be provided on such map. This is shown with regard to potential location <NUM> on the map of <FIG>.

An operator or the computer itself then determines which image capture apparatuses may have the target shipping container in the potential field of view and make a request to such image capture apparatuses <NUM> to capture an image to verify the potential location <NUM>. In some cases, only one image sensor apparatus may be asked to capture an image. In other cases, a plurality of image sensor apparatuses may be asked to capture images and such image data may be spliced together or compared.

Processing of a request for image capture from image sensor apparatuses <NUM> at each image sensor apparatus may use the process of <FIG>.

With regard to network functionality, reference is now made to <FIG>, which shows a process of a server for utilizing other containers to find a container of interest.

The process of <FIG> starts at block <NUM> and proceeds to block <NUM> in which the one or more sensor apparatuses are requested to capture an image.

Each of the sensor apparatuses that are requested to capture an image would then perform the process of <FIG> to capture and return the image and the image would be received at block <NUM> in the example of <FIG>. If a plurality of images are requested, each would be received at block <NUM>.

From block <NUM> the process proceeds to block <NUM> in which the image or images are processed to determine whether the desired container is within the field of view and thus at its anticipated location. The image processing may be done by a human operator or automatically using optical recognition to look for markings on the exterior of the desired container. The container markings for a desired container would typically be known at the server.

The process then proceeds to block <NUM> in which a check is made to determine whether the container is found. If the container is found then the process may proceed to block <NUM> in which a shunt vehicle may be dispatched to the location of the container, the process may then proceed to block <NUM> and end.

Conversely, if the container is not found in the image or images received at block <NUM>, the process may proceed to block <NUM> in which the scope of the search may be expanded. In particular, at block <NUM> other image capture apparatuses may be identified to help determine the location of the shipping container. Such identification may, for example, identify a threshold distance or radius from the anticipated location and use all image sensor apparatuses within such distance. In other cases, the search may be directionally focused, and identify devices on a certain bearing from the anticipated location. Other options for selecting image sensor apparatuses are possible.

From block <NUM>, the process may proceed back to block <NUM> in which each identified image sensor apparatus is requested to perform an image capture. In this way, the process may then proceed back through blocks <NUM>, <NUM> and <NUM> to process the additional images that were captured and a check may be made again at block <NUM> to determine whether the container was found.

If the container is still not found, then the scope of the search may again be expanded at block <NUM> and process may continue to loop in this way until the container is found, until images have been captured by all image sensor apparatuses, or until some maximum search criteria are met.

If the container is found, a map may be updated and the process proceeds to block <NUM> in which the shunt vehicle is dispatched to the verified location of the container.

Using the above, the shunt vehicles is only dispatched to a location after confirming that the container is where it is expected. This saves various resources, including time, fuel and enhances the operation of a shipping yard.

The server performing the examples above may be any network based server or combination of servers. One simplified server that may be used is provided with regards to <FIG>.

In <FIG>, server <NUM> includes a processor <NUM> and a communications subsystem <NUM>, where the processor <NUM> and communications subsystem <NUM> cooperate to perform the methods described herein.

Processor <NUM> is configured to execute programmable logic, which may be stored, along with data, on server <NUM>, and shown in the example of <FIG> as memory <NUM>. Memory <NUM> can be any tangible, non-transitory computer readable storage medium, such as optical (e.g., CD, DVD, etc.), magnetic (e.g., tape), flash drive, hard drive, or other memory known in the art.

Alternatively, or in addition to memory <NUM>, server <NUM> may access data or programmable logic from an external storage medium, for example through communications subsystem <NUM>.

Communications subsystem <NUM> allows server <NUM> to communicate with other devices or network elements.

Communications between the various elements of server <NUM> may be through an internal bus <NUM>. However, other forms of communication are possible.

The examples described herein solve various issues. Specifically, the examples provide a low-cost solution since the image sensor apparatuses may already be part of containers. In the shipping yard example, the yard is typically covered relatively well since such shipping containers tend to get randomly distributed.

The examples described may provide image capture for various angles, increasing chances of finding a shipping container prior to dispatching a shunt vehicle.

The examples described herein are examples of structures, systems or methods having elements corresponding to elements of the techniques of this application. This written description may enable those skilled in the art to make and use examples having alternative elements that likewise correspond to the elements of the techniques of this application. The intended scope of the techniques of this application is given by the appended claims.

While operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be employed. Moreover, the separation of various system components in the implementation descried above should not be understood as requiring such separation in all implementations, and it should be understood that the described program components and systems can generally be integrated together in a signal software product or packaged into multiple software products.

Typically, storage mediums can include any or some combination of the following: a semiconductor memory device such as a dynamic or static random access memory (a DRAM or SRAM), an erasable and programmable read-only memory (EPROM), an electrically erasable and programmable read-only memory (EEPROM) and flash memory; a magnetic disk such as a fixed, floppy and removable disk; another magnetic medium including tape; an optical medium such as a compact disk (CD) or a digital video disk (DVD); or another type of storage device. Note that the instructions discussed above can be provided on one computer-readable or machine-readable storage medium, or alternatively, can be provided on multiple computer-readable or machine-readable storage media distributed in a large system having possibly plural nodes. Such computer-readable or machine-readable storage medium or media is (are) considered to be part of an article (or article of manufacture). The storage medium or media can be located either in the machine running the machine-readable instructions, or located at a remote site from which machine-readable instructions can be downloaded over a network for execution.

Claim 1:
A method at a server (<NUM>, <NUM>, <NUM>) for identifying a location of a target container (<NUM>) within a container yard (<NUM>), the method comprising:
determining, based on a map indicating locations of a plurality of image sensor apparatuses affixed to respective containers in the container yard, an image sensor apparatus as a potential image sensor apparatus that has the target container in its field of view;
requesting (<NUM>, <NUM>) image data from the image sensor apparatus (<NUM>);
receiving (<NUM>, <NUM>, <NUM>) the image data and supplemental data from the image sensor apparatus, the image data comprising images captured by the image sensor apparatus, the supplemental data comprising a location of the image sensor apparatus and a direction of a field of view of the image sensor apparatus; and
processing (<NUM>, <NUM>, <NUM>) the image data and the supplemental data to identify the location of the target container within the container yard.