Server and method for facilitating adding new POI to map

Abstract

According to various embodiments, there is a server for facilitating adding a new POI (Point of Interest) to a map, the server comprising: a memory configured to store instructions; and a processor for executing the stored instructions and configured to: obtain an image capturing at least one place from a computing device associated with a user; extract at least one information about the place using the image, wherein the at least one information is of a predetermined type; and create a request for adding the new POI for the place using the extracted information, wherein if the request for adding the new POI for the place is accepted, the new POI for the place is added to the map, based on the extracted information

Description

SERVER AND METHOD FOR FACILITATING ADDING NEW POI TO MAP TECHNICAL FIELD

[0001] Various embodiments relate to a server and a method for facilitating adding a new POI (Point of Interest) to a map.BACKGROUND

[0002] Creating POI (Point of Interest) for a place, including, but not limited to, an office, a religious place, and hotel for a map may usually be time consuming and expensive. Crowdsourcing POI creation may generally involve a mapper submitting a request for adding the POI for the place including an image of the place (also referred to as an “image of a POI panel”) (for example, clearly indicating a name of the place) and other information such as a category, a telephone number and an address of the place. A computing device associated with the mapper may use a GPS (Global Positioning System) to infer a POI location (for example, latitude and longitude). The mapper may fill required information in a submission form and submit the submission form to request to add the POI for the place. Once the mapper submits the submission form, a task for adding the POI for the place is sent to a map validator who then accept, edit or reject the POI for the place, based on quality, accuracy and / or validity of the submission form. However, there have been some problems in view of the mapper and the validator as follows:a) Mapper: The mapper may have to spend a lot of time to correctly type the name of the place (for example, often lengthy), identify the category of the place, and submit other metadata. Furthermore, while submitting the image (of the POI panel), a server for adding the POI forthe place may take unclear and / or blurry images, or images that may not clearly show a storefront of the place.b) Map validator: Given the scale of the submission forms, the validator may be inundated with millions of submission forms, resulting in huge delays in creating the POI. Furthermore, The validator may also have to deal with the unclear and / or blurry images, spelling errors and / or typographical errors in the name of the POI, or an incorrect category of the POI, from the submission forms received from the mapper.|0003| The current approach for the POI creation from crowdsourcing may have a lower engagement due to a cumbersome process of filling up a lengthy submission form. In addition, as described above, vetting the crowdsourced submission forms may be a manual process with the validator having to deal with submission forms of low quality. This lengthy process may result in huge backlogs resulting in a delayed POI creation, impacting the on-demand service application experience.

[0004] Therefore, there is a need to provide a multimodal Al-based solution that leverages the latest advancements in artificial intelligence to address the above problems.SUMMARY

[0005] According to various embodiments, there is a server for facilitating adding a new POI (Point of Interest) to a map, the server comprising: a memory configured to store instructions; and a processor for executing the stored instructions and configured to: obtain an image capturing at least one place from a computing device associated with a user; extract at least one information about the place using the image, wherein the at least one information is of a predetermined type; and create a request for adding the new POI for the place using theextracted information, wherein if the request for adding the new POI for the place is accepted, the new POI for the place is added to the map, based on the extracted information.

[0006] In some embodiments, the processor is further configured to: determine if a clarity of the image is below a predetermined threshold; and if it is determined that the clarity of the image is below the predetermined threshold, request the computing device to obtain a new image of the place.

[0007] In some embodiments, the processor is further configured to: submit the request for adding the new POI for the place.

[0008] In some embodiments, the processor is further configured to: automatically fill required information about the place in a submission form, based on the extracted information; and submit the submission form as the request for adding the new POI for the place.

[0009] In some embodiments, the processor is further configured to: output the automatically filled information to the computing device; receive an input about the automatically filled information from the user; and correct the automatically filled information based on the input from the user.

[0010] In some embodiments, the processor is further configured to: determine whether to accept the request for adding the new POI for the place; and determine a confidence score of the determination on whether to accept the request for adding the new POI for the place.

[0011] In some embodiments, the processor is further configured to: if it is determined to accept the request for adding the new POI for the place and the confidence score is equal to or greater than a predetermined score, input the request for adding the new POI for the place into a POI database, to conduct at least one predetermined check before adding the new POI for the place.

[0012] In some embodiments, the processor is further configured to: if it is determined to reject the request for adding the new POI for the place and the confidence score is equal to or less than the predetermined score, reject the request for adding the new POI for the place.

[0013] In some embodiments, the processor is further configured to: if the confidence score is in a predetermined score range, send the request for adding the new POI for the place to a validator, to receive a confirmation of an acceptance or a rejection of the request for adding the new POI for the place.

[0014] In some embodiments, the predetermined type includes at least one of a name, an address, and a category of the place.

[0015] According to various embodiments, there is a method for facilitating adding a new POI (Point of Interest) to a map, the method comprising: obtaining an image capturing at least one place from a computing device associated with a user; extracting at least one information about the place using the image, wherein the at least one information is of a predetermined type; and creating a request for adding the new POI for the place using the extracted information, wherein if the request for adding the new POI for the place is accepted, the new POI for the place is added to the map, based on the extracted information.

[0016] In some embodiments, the method further comprises: determining if a clarity of the image is below a predetermined threshold; and if it is determined that the clarity of the image is below the predetermined threshold, requesting the computing device to obtain a new image of the place.

[0017] In some embodiments, the method further comprises: submitting the request for adding the new POI for the place.

[0018] In some embodiments, the method further comprises: automatically filling required information about the place in a submission form, based on the extracted information; and submitting the submission form as the request for adding the new POI for the place.

[0019] In some embodiments, the method further comprises: outputting the automatically filled information to the computing device; receiving an input about the automatically filled information from the user; and correcting the automatically filled information based on the input from the user.

[0020] In some embodiments, the method further comprises: determining whether to accept the request for adding the new POI for the place; and determining a confidence score of the determination on whether to accept the request for adding the new POI for the place.

[0021] In some embodiments, the method further comprises: if it is determined to accept the request for adding the new POI for the place and the confidence score is equal to or greater than a predetermined score, inputting the request for adding the new POI for the place into a POI database, to conduct at least one predetermined check before adding the new POI for the place.

[0022] In some embodiments, the method further comprises: if it is determined to reject the request for adding the new POI for the place and the confidence score is equal to or less than the predetermined score, rejecting the request for adding the new POI for the place.

[0023] In some embodiments, the method further comprises: if the confidence score is in a predetermined score range, sending the request for adding the new POI for the place to a validator, to receive a confirmation of an acceptance or a rejection of the request for adding the new POI for the place.

[0024] In some embodiments, the predetermined type includes at least one of a name, an address, and a category of the place.

[0025] According to various embodiments, a data processing apparatus configured to perform the method of any one of the above embodiments is provided.

[0026] According to various embodiments, a computer program element comprising program instructions, which, when executed by one or more processors, cause the one or more processors to perform the method of any one of the above embodiments is provided.

[0027] According to various embodiments, a computer-readable medium comprising program instructions, which, when executed by one or more processors, cause the one or more processors to perform the method of any one of the above embodiments is provided. The computer-readable medium may include a non-transitory computer-readable medium.BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The invention will be better understood with reference to the detailed description when considered in conjunction with the non-limiting examples and the accompanying drawings, in which:- FIG. 1 illustrates an infrastructure of a system for facilitating adding a new POI (Point of Interest) to a map according to various embodiments.- FIG.2 illustrates a block diagram of a device associated with a user according to various embodiments.- FIG. 3 illustrates a block diagram of a server for facilitating adding a new POI (Point of Interest) to a map according to various embodiments.- FIG. 4 illustrates a flow diagram for a method for facilitating adding a new POI (Point of Interest) to a map according to various embodiments.- FIGS. 5 and 6 illustrate data flow diagrams for a system for facilitating adding a new POI (Point of Interest) to a map according to various embodiments.- FIGS. 7 to 10 illustrate exemplary diagrams for creating a request for adding a new POI (Point of Interest) for a place according to various embodiments.- FIGS. 11 to 13 illustrate exemplary diagrams for creating a request for adding a plurality of new POIs (Points of Interest) for a plurality of places according to various embodiments.- FIGS. 14 and 15 illustrate exemplary diagrams for requesting a computing device to obtain a new image of a place according to various embodiments.DETAILED DESCRIPTION

[0029] The following detailed description refers to the accompanying drawings that show, by way of illustration, specific details and embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure. Other embodiments may be utilized, and structural and logical changes may be made without departing from the scope of the disclosure. The various embodiments are not necessarily mutually exclusive, as some embodiments can be combined with one or more other embodiments to form new embodiments.

[0030] Embodiments described in the context of one of a server and a method are analogously valid for the other of the server and method. Similarly, embodiments described in the context of a server are analogously valid for a method, and vice-versa.

[0031] Features that are described in the context of an embodiment may correspondingly be applicable to the same or similar features in the other embodiments. Features that are described in the context of an embodiment may correspondingly be applicable to the other embodiments, even if not explicitly described in these other embodiments. Furthermore, additions and / or combinations and / or alternatives as described for a feature in the context of an embodiment may correspondingly be applicable to the same or similar feature in the other embodiments.

[0032] In the context of various embodiments, the articles “a”, “an” and “the” as used with regard to a feature or element include a reference to one or more of the features or elements.

[0033] As used herein, the term “and / or” includes any and all combinations of one or more of the associated listed items.

[0034] Throughout the description, the term “module” may be understood as an application specific integrated circuit (ASIC), an electronic circuit, a combinational logic circuit, a field programmable gate array (FPGA), a processor which executes code, other suitable hardware components which provide the described functionality, or any combination thereof. The term of “module” may include a memory which stores code executed by the processor.

[0035] In the following, embodiments will be described in detail.

[0036] FIG. 1 illustrates an infrastructure of a system 200 for facilitating adding a new POI (Point of Interest) to a map according to various embodiments. As shown in FIG. 1, the system 200 may include, but is not limited to, a server 100, a database system 140, and a network 150.

[0037] In some embodiments, the server 100, for example, implemented by a server computer, may include a communication interface 110, a processor 120, and a memory 130 (as will be described with reference to FIG. 3).

[0038] In some embodiments, the system 200 may further include a database 141. In some embodiments, the database 141 may be a part of the database system 140 which may be external to the server 100. The server 100 may communicate with the database 141. In some other embodiments, although not shown, the database 141 may be implemented locally in the memory 130 of the server 100.

[0039] In some embodiments, the system 200 may further include one or more computing devices 160 each associated with a user 170. For example, as shown in FIG. 1, the system 200 may further include a first computing device 160a associated with a first user 170a and a second computing device 160b associated with a second user 170b.

[0040] In some embodiments, the user 170 may include a consumer (who in some contexts herein may also be referred to as a “requester” or a “Pax”) for an on-demand service. In some embodiments, the user 170 may include a merchant (who in some contexts herein may also be referred to as a “retailer”, a “restaurant” or a “Mex”) for the on-demand service. In some embodiments, the user 170 may include a driver (who in some contexts herein may also be referred to as a “delivery service provider”, a “delivery partner”, a “delivery agent” or a “Dax”) for the on-demand service. In some embodiments, the user 170 may include a mapper and / or a general consumer, for example, a consumer using the map.

[0041] In some embodiments, the on-demand service may be a service allowing the consumer to fulfil the consumer’s demand via an immediate access to items and / or services. The consumer may request the on-demand service, such as a transport service or an item delivery service, using a user interface presented on the computing device associated with the consumer. The consumer may make an order for the on-demand service.

[0042] In some embodiments, the user 170 may use an application (also referred to as an “App”), for example, a mobile application, provided by the server 100. For example, the server 100 may be controlled and / or managed by an on-demand service platform provider. The application may be installed in the computing device 160 associated with the user 170, to interact with the server 100.

[0043] In some embodiments, the network 150 may include, but is not limited to, a Local Area Network (LAN), a Wide Area Network (WAN), a Global Area Network (GAN), or any combination thereof. The network 150 may provide a wireline communication, a wireless communication, or a combination of the wireline and wireless communication between the server 100 and the first computing device 160a, and between the server 100 and the second computing device 160b. In some embodiments, the network 150 may provide the wireline communication, the wireless communication, or the combination of the wireline and wirelesscommunication between the first computing device 160a and the second computing device 160b.

[0044] In some embodiments, the computing device 160 may be connectable to the server 100 via the network 150. In some embodiments, the computing device 160 may be arranged in data or signal communication with the server 100 via the network 150. In some embodiments, the computing device 160 may include, but is not limited to, at least one of the following: a mobile phone, a tablet computer, a laptop computer, a desktop computer, a head-mounted display, a smart watch, and a camera device (for example, “KartaCam”). In some embodiments, the computing device 160 may be associated with the user 170. For example, the computing device 160 may belong to the user 170.

[0045] In some embodiments, the computing device 160 may be configured to obtain an image and process the image. In some embodiments, the computing device 160 may include a communication interface 161, a processor 162, a memory 163, and an image capturing module 164 (as will be described with reference to FIG. 2).

[0046] In some embodiments, the computing device 160 may obtain the image. In some embodiments, the user 170 may carry the computing device 160 to capture the image of an external environment, for example, including at least one place. For example, the computing device 160 may be mounted on a vehicle, for example, a roof or a windshield of a car or a pole on a back of a motorcycle, that the user 170, for example, the driver, is driving, to capture the image of the place. As another example, the computing device 160 may be mounted on a helmet of the user 170, for example, the driver, to capture the image of the place.

[0047] In some embodiments, the computing device 160 may include a location sensor. In some embodiments, the location sensor may communicate with at least one of a global positioning satellite (GPS) server, a network server, and a Wi-Fi server, to detect a location of the computing device 160. In some embodiments, the device 100 may generate informationabout the location of the device 100. In some embodiments, the device 100 may record the location of the device 100 with every exposure, so that the image can be matched to the corresponding GPS position. In some other embodiments, the device 100 may generate information about the location and an orientation of the device 100. In some embodiments, the device 100 may record the location and the orientation of the device 100 with every exposure. In some embodiments, the computing device 160 may send the information about the location of the computing device 160 to the server 100 via the network 150. The location of the computing device 160 may be considered as a location of the user 170. For example, if the user 170 is the consumer, the location of the user 170 may be considered as a destination of the on-demand service.

[0048] FIG.2 illustrates a block diagram of a device associated with a user according to various embodiments.

[0049] As shown in FIG. 2, the computing device 160 may include a communication interface 161, a processor 162, a memory 163, and an image capturing module 164.

[0050] In some embodiments, the image capturing module 164 may obtain an image capturing an external environment, for example, including at least one place. The image may include an image capturing the place. In some embodiments, the image may be at least one of a static image (also referred to as a “single image”, “still image” or a “photo”), a plurality of static images (also referred to as “a plurality of images”, “a plurality of photos”, “multiple images” or “multiple photos”), and sequences of images (also referred to as a “moving image” or a “video”). In some embodiments, the image may be a panoramic image. In some other embodiments, the image may be a non-panoramic image. In some embodiments, the image capturing module 164 may be in a form of a camera, for example, an RGB camera. In some embodiments, the image capturing module 164 may generate a raw data image. Thereafter, theimage capturing module 164 may process, for example interpret, the raw data image to obtain the image.

[0051] In some embodiments, the image capturing module 164 may be physically mounted on the computing device 160. Although not shown, in some other embodiments, the image capturing module 164 may be physically mounted on other devices, for example, an image capturing device (not shown) which is communicatively connectable to the computing device 160.

[0052] In some embodiments, the image capturing module 164 may have a certain degree field of view (for example, a 150-degree field of view). In some embodiments, the computing device 160 may include a plurality of image capturing modules 164, for example, four (4) image capturing modules 164. The plurality of image capturing modules 164 may be grouped and synchronised to create a 360-degree field of view. In some embodiments, each of the plurality of image capturing modules 164 may have the same degree field of view. In some other embodiments, each of the plurality of image capturing modules 164 may have a different degree field of view.

[0053] Although not shown, in some embodiments, the computing device 160 may further include a location sensor. In some embodiments, the location sensor may communicate with at least one of a GPS server, a network server, and a Wi-Fi server, to detect a location of the computing device 160.

[0054] Although not shown, in some embodiments, the computing device 160 may further include an orientation sensor. In some embodiments, the orientation sensor may detect an orientation (tilt) of the computing device 160. The orientation sensor may include, but not be limited to, an accelerometer, a gyroscope, and a magnetometer. For example, the accelerometer may detect the orientation of the computing device 160 by measuring an acceleration due to the gravity.

[0055] In some embodiments, the computing device 160 may generate information about the location of the computing device 160. In some embodiments, the computing device 160 may record the location of the computing device 160 with every exposure, so that the image can be matched to the corresponding GPS position. In some other embodiments, the computing device 160 may generate information about the location and the orientation of the computing device 160. In some embodiments, the computing device 160 may record the location and the orientation of the computing device 160 with every exposure.

[0056] In some embodiments, the memory 163 (also referred to as a “database”) may store input data and / or output data temporarily or permanently. In some embodiments, the program code may be embedded in a Software Development Kit (SDK). The memory 163 may include an internal memory of the computing device 160 and / or an external memory. The external memory' may include, but is not limited to, an external storage medium, for example, a memory card and a flash drive.

[0057] In some embodiments, the communication interface 161 may allow the computing device 160 to communicate with a server 100 via a network 150, as shown in FIG. 1. In some embodiments, the communication interface 161 may transmit signals to the server 100, and / or receive signals from the server 100 via the network 150.

[0058] The processor 162 may include, but is not limited to, a microprocessor, an analogue circuit, a digital circuit, a mixed-signal circuit, a logic circuit, an integrated circuit, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), or any combination thereof. Any other kind of implementation of the respective functions, which will be described below in further detail, may also be understood as the processor 162.

[0059] In some embodiments, the processor 162 may be communicatively couplable with the image capturing module 164. In some embodiments, the processor 162 may be arranged in dataor signal communication with the image capturing module 164 to receive the image from the image capturing module 164.

[0060] In some embodiments, the processor 162 may be communicatively couplable with the memory' 163. In some embodiments, the processor 162 may be arranged in data or signal communication with the memory 163 to store data, for example, the image, in the memory 163.

[0061] In some embodiments, the processor 162 may be communicatively couplable with the communication interface 161. In some embodiments, the processor 162 may be arranged in data or signal communication with the communication interface 161 to transmit data, for example, the image, to the memory 130 of the server 100 via the network 150.

[0062] In some embodiments, the processor 162 may receive the image from the image capturing module 164. In some embodiments, the processor 162 may transmit the image to the server 100 via the communication interface 161. In some embodiments, the processor 162 may transmit the image with the corresponding location information, for example, GPS position, to the server 100 via the communication interface 161. For example, the processor 162 may transmit the single image with the corresponding GPS position to the server 100 via the communication interface 161. As another example, the processor 162 may transmit the multiple images with the corresponding GPS position to the server 100 via the communication interface 161. As another example, the processor 162 may transmit the video to the server 100 via the communication interface 161.

[0063] FIG. 3 illustrates a block diagram of a server 100 for facilitating adding a new PO1 (Point of Interest) to a map according to various embodiments.

[0064] As shown in FIG. 3, the server 100, for example, implemented by a server computer, may include a communication interface 110, a processor 120, and a memory 130.

[0065] In some embodiments, the memory 130 (also referred to as a “database”) may store input data and / or output data temporarily or permanently. In some embodiments, the memory130 may be configured to store instructions. In some embodiments, the memory 130 may store program code which allows the server 100 to perform a method 300 (as will be described with reference to FIG. 4). In some embodiments, the program code may be embedded in a Software Development Kit (SDK). The memory 130 may include an internal memory of the server 100 and / or an external memory. The external memory may include, but is not limited to, an external storage medium, for example, a memory card, a flash drive, and a web storage.

[0066] In some embodiments, the communication interface 110 may allow one or more computing devices 160 to communicate with the processor 120 of the server 100 via a network 150, as shown in FIG. 1.

[0067] In some embodiments, processor 120 may include, but is not limited to, a microprocessor, an analogue circuit, a digital circuit, a mixed-signal circuit, a logic circuit, an integrated circuit, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), or any combination thereof. Any other kind of implementation of the respective functions, which will be described below in further detail, may also be understood as the processor 120.

[0068] In some embodiments, the processor 120 may be connectable to the communication interface 110. In some embodiments, the processor 120 may be arranged in data or signal communication with the communication interface 110 to transmit / receive the signals.

[0069] In some embodiments, the processor 120 may obtain an image capturing an external environment, for example, including at least one place. In some embodiments, the processor 120 may obtain the image from a computing device 160 associated with a user 170 via the communication interface 110. In some embodiments, the image may be at least one of a single image, a plurality of images, and a video. In some embodiments, the image may be a panoramic image. In some other embodiments, the image may be a non-panoramic image.

[0070] In some embodiments, the processor 120 may further obtain location information, for example, GPS position, corresponding to the image from the computing device 160 via the communication interface 110. In some embodiments, the processor 120 may concurrently obtain the image and the corresponding GPS location from the computing device 160 via the communication interface 110.

[0071] In some embodiments, the processor 120 may extract at least one information about the place using the image. In some embodiments, the processor 120 may use an Al (artificial intelligence) technology to extract the at least one information about the place based on the image. In some embodiments, the at least one information may be of a predetermined type. In some embodiments, the predetermined type may include at least one of a name, an address, and a category of the place. In some embodiments, the processor 120 may use an OCR (Optical Character Recognition) technology to extract at least one text information, for example, the name information of the place, from the image. In some embodiments, the processor 120 may use a search engine and / or an LLM (Large Language Model) with a search keyword of the name of the place extracted from the image, to extract category information of the place from a web. In some other embodiments, the processor 120 may use a reverse geographical (Rev Geo) module, to extract the address information of the place. For example, the processor 120 may include the reverse geographical module. The Rev Geo may stand for “Reverse Geocoding” (also referred to as an “Address Lookup”), and mean mapping of coordinates (latitude, longitude) to address. The Rev Geo may operate by assuming an existing database of “POls”, “Address” and “location” (for example, latitude, longitude); (given a new location) finding the k-closcst POIs (based on a distance), creating a list of the corresponding k “Addresses”, and calling it a candidate list; and taking the majority vote from the candidate list as “Address” to the new location. As another example, the reverse geographical module may be external to the processor 120. In some embodiments, the processor 120 may use the locationinformation corresponding to the image, obtained from the computing device 160, to extract address information of the place. In some other embodiments, the processor 120 may use the search engine and / or the LLM with the search keyword of the name of the place extracted from the image, to extract the address information of the place from the web. In some other embodiments, the processor 120 may use both the location information obtained from the computing device 160 and the search engine and / or the LLM with the search keyword of the name of the place, to verify the address information of the place.

[0072] In some embodiments, the processor 120 may determine a clarity of the image. In some embodiments, the processor 120 may determine if the clarity of the image is below a predetermined threshold. In some embodiments, if it is determined that the clarity of the image is below the predetermined threshold, the processor 120 may request the computing device 160 to obtain a new image of the place. For example, if the processor 120 determines that the accuracy of the text information extracted from the image is below the predetermined threshold, the processor 120 may request the computing device 160 to obtain the new image of the place. For example, if the processor 120 determines that the clarity of the image is below the predetermined threshold, the processor 120 may request the computing device 160 to obtain the new image of the place.

[0073] In some embodiments, the processor 120 may create a request for adding the new POI for the place using the extracted information. In some embodiments, the computing device 160 may display a submission form as the request for adding the new POI for the place. In some embodiments, the processor 120 may automatically fill required information about the place in the submission form, based on the extracted information. For example, the processor 120 may automatically fill the name information about the place in a first blank of the submission form based on the extracted name information, fill the category information about the place in a second blank of the submission form based on the extracted category information, and fill theaddress information about the place in a third blank of the submission form based on the extracted address information.

[0074] In some embodiments, the processor 120 may output the automatically filled information to the computing device 160. In some embodiments, the computing device 160 may display the automatically filled information on the submission form. In some embodiments, the processor 120 may request the user 170 to provide an input about the automatically filled information, hi some embodiments, the processor 120 may allow the user 170 to correct the automatically filled information on the submission form. For example, the user 170 may correct the name information of the place on the submission form, if the name is wrongly indicated. In some embodiments, the processor 120 may receive the input about the automatically filled information from the user. In some embodiments, the processor 120 may correct the automatically filled information based on the input from the user.

[0075] In some embodiments, the processor 120 may submit the request for adding the new POI for the place. In some embodiments, the processor 120 may submit the submission form, including the image, as the request for adding the new POI for the place. For example, the processor 120 may submit the submission form internally (for example, from a frontend processor (also referred to as a “frontend pipeline”) of the processor 120 to a backend processor (also referred to as a “backend pipeline”) of the processor 120). As another example, the processor 120 may submit the submission form to an external server (not shown).

[0076] In some embodiments, if the request for adding the new POI for the place is accepted, the new POI for the place is added to the map, based on the extracted information. In some embodiments, the processor 120 may determine whether to accept the request for adding the new POI for the place, and add the new POI for the place to the map, if the request for adding the new POI for the place is accepted. In some other embodiments, the processor 120 may determine whether to accept the request for adding the new POI for the place, and the externalserver may add the new POI for the place to the map, if the request for adding the new POI for the place is accepted. In some other embodiments, the external server may determine whether to accept the request for adding the new POI for the place, and the processor 120 may add the new POI for the place to the map, if the request for adding the new POI for the place is accepted. In some other embodiments, the external server may determine whether to accept the request for adding the new POI for the place, and add the new POI for the place to the map, if the request for adding the new POI for the place is accepted. In this regard, the public may view the new POI for the place on the map. For example, as shown in FIG. 1, the first user 170a may request for add the new POI for the place using the first computing device 160a, and the second user 170b may view the new POI which is added to the map displayed on the second computing device 160b. In some embodiments, the Al may be used by the processor 120 and / or the external server to determine whether to accept the request for adding the new POI for the place.

[0077] In some embodiments, the processor 120 may determine whether to accept the request for adding the new POI for the place. In some embodiments, the processor 120 may determine a confidence score of the determination on whether to accept the request for adding the new POI for the place. In some embodiments, the processor 120 may check the image and the required information filled in the submission form, and determine whether to accept the request for adding the new POI for the place. In some embodiments, the processor 120 may use the search engine to determine whether to accept the request for adding the new POI for the place, and the confidence score of the determination on whether to accept the request for adding the new POI for the place.

[0078] In some embodiments, if it is determined to accept the request for adding the new POI for the place and the confidence score is equal to or greater than a predetermined score, the processor 120 may input the request for adding the new POI for the place into a POI database storing all existing POIs of the map, to conduct at least one predetermined check (also referredto as a “post-check”) before adding the new POI for the place to the map. For example, the memory 130 may include the POI database. As another example, the database 141 may include the POI database. As another example, the POI database may be another database (not shown). For example, the processor 120 may check the POI database, to check an internal duplication of the new POI (for example, if the POI already exists in the POI database), and enrich the duplicated POI with rejecting the request for adding the new POI for the place (i.e. the submission form).

[0079] In some embodiments, if it is determined to reject the request for adding the new POI for the place and the confidence score is equal to or less than the predetermined score, the processor 120 may reject the request for adding the new POI for the place (i.e. the submission form), and the new POI for the place may not be added to the map.

[0080] In some embodiments, if the confidence score is in a predetermined score range, the processor 120 may send the request for adding the new POI for the place to a validator, for example, a predetermined human validator. In some embodiments, the validator may receive the submission form including the image from the processor 120, and provide a confirmation on whether to accept or reject the request for adding the new POI for the place. In some embodiments, the processor 120 may receive the confirmation of an acceptance or a rejection of the request for adding the new POI for the place. In some embodiments, if the processor 120 receives the confirmation of the acceptance, the new POI for the place may be added to the map. In some embodiments, if the processor 120 receives the confirmation on the rejection, the new POI for the place may not be added to the map.

[0081] As described above, a real-time (or nearly real-time) POI extraction workflow using multi-modal models (like LMMs) extracting the required information in a single stage by prompting the LMM with relevant information may be provided. The various embodimentsmay increase a mapper (user 170) engagement, increase automation and create a single stop solution for a variety of POI creation workflows.

[0082] The Al based multi-modal solution for the POI creation may automate and simplify several pipeline stages, thereby increasing the efficiency of the POI submission and creation. The various embodiments may largely reduce a turnaround time for the POI creation (for example, to a few minutes) by automating the POI creation for a vast majority of the submissions, thus quickly reducing POI gaps in the map.

[0083] FIG. 4 illustrates a flow diagram for a method 300 for facilitating adding a new POI (Point of Interest) to a map according to various embodiments.

[0084] According to various embodiments, the method 300 for facilitating adding the new POI to the map may be provided.

[0085] In some embodiments, the method 300 may include a step 301 of obtaining an image capturing at least one place from a computing device associated with a user.

[0086] In some embodiments, the method 300 may include a step 302 of extracting at least one information about the place using the image. In some embodiments, the at least one information may be of a predetermined type.

[0087] In some embodiments, the method 300 may include a step 303 of creating a request for adding the new POI for the place using the extracted information.

[0088] In some embodiments, the method 300 may include a step 304 of, if the request for adding the new POI for the place is accepted, adding the new POI for the place to the map, based on the extracted information.

[0089] FIGS. 5 and 6 illustrate data flow diagrams for a system 200 for facilitating adding a new POI (Point of Interest) to a map according to various embodiments.

[0090] In some embodiments, the system 200 may include a server 100. The server 100 include a processor 120 for facilitating adding the new POI to the map. The processor 120 may include a frontend pipeline for a frontend validation, and a backend pipeline for a backend validation.

[0091] In some embodiments, the server 100 may provide an application to a computing device 160 associated with a user 170. The application may be installed in the computing device 160. In some embodiments, the user 170 may be referred to as a “mapper”, and may include a consumer, a merchant and / or a driver.

[0092] As shown in FIG. 5, in some embodiments, the computing device 160 may capture a single image, multiple images and / or a video for an external environment including at least one place (401). In some embodiments, the computing device 160 may upload the single image, the multiple image and / or the video to the server 100. In some embodiments, the processor 120 may receive the single image from the computing device 160, and extract at least one POI from the single image (402). In some embodiments, the POI may refer to a specific location on the map that includes a name and a location (for example, an address, and latitude / longitude values). For example, the POI may represent shops, houses, malls, offices, buildings, residential condos, temples / churches, clinics, education centres, transportation hubs, etc.

[0093] In some embodiments, the processor 120 may extract the POI from the single image, using a multi-modal source, for example, a combination of the LLM and a prompt. In some embodiments, the processor 120 may prompt an LLM (large language model) to extract all POls and key attributes relevant to the all POls. In some embodiments, the key attributes may include at least one information about the place, and be extracted using the single image. As an example, the key attributes include, but are not limited to, a phone number, an email address, and opening / closing hours for each of the POls. For example, the processor 120 may prompt the multi-modal model to extract information about whether the POI is present or not in thesingle image, names of the POIs, and the key attributes of the POIs. An exemplary prompt is as follows:“As an expert Mapper / Annotator based in {country_name}, your task is to extract POIs from images.To assist in your task, we included step-by-step instructions for you to follow:For each POI identified in the image:1. Step-1: Motivate and reason if the POI is a permanent building.2. Step-2: Motivate and reason if the POI name is clearly visible.3. Step-3: Motivate and describe if the POI address (including house number and street) is clearly visible.4. Step-4: Motivate to describe if POI phone number is visible in image.5. Step-5: Motivate to describe if POI email is visible in image.6. Step-6: Motivate to describe the business category of the POI. Business category can be one of [Commercial building, Food and beverage, shop, residential, airport, bank, bar / pub / club, car park, Casino, Church, Cinema / theatre, Education, Embassy, Government building, Harbour, Healthcare, Hotel, Library, Market, Monument, Mosque, Museum, Police station, Sports / Recreation centre. Stadium, Station, Street, Subdivision Gate, Temple, Utilities]7. Step-7: Extract a name of the POI if the name is clearly visible. Otherwise, provide a null string as the value.Fill the following list of dictionaries where each list element is a JSON corresponding to a unique commercial POI in the photo[ { is_POI_a_permanent_building: <boolean value>is_POI_name_visible: <boolean value>POI_address: < string >POI_phone_number: < string >POI_email: <string>POI_business_category:<string>POI_name: < string> } ]Respond as a json object with keys as specified above.”

[0094] In some embodiments, the processor 120 may receive the multiple images, and extract POIs from the multiple images (403). In some embodiments, the processor 120 may extract one or more POIs from each image, and perform Task2Task2 deduplication to merge duplicated POIs (405).

[0095] In some embodiments, the processor 120 may receive the video, and extract key frames of the video (404). Thereafter, the processor 120 may extract POIs from the key frames (403). In some embodiments, the processor 120 may first extract the key frames, which may represent boundaries of a smooth transition in the video. In some embodiments, the processor 120 may treat each key frame as a separate image and follow a pipeline of “multiple images” to extract the POIs. In some embodiments, the processor 120 may extract one or more POIs from each image, and perform Task2Task2 deduplication to merge duplicated POIs (405).

[0096] In some embodiments, the processor 120 may determine if the POI presents in the single image, the multiple images, or the video (406).

[0097] In some embodiments, if it is determined that the POI presents (for example, if the processor 120 finds at least one POI from the single image, the multiple images, or the video), the processor 120 may extract the name of the POI, and the key attributes of the POI (409), and auto-populate the key attributes for the user 170 to review (410).

[0098] In some embodiments, if it is determined that the POI docs not present (for example, if the processor 120 does not find at least one POI from the single image, the multiple images, or the video), the processor 120 may reject a request for adding the new POI for the place, and provide a reason for the rejection (407). In some embodiments, the processor 120 may requestthe computing device 160 to re-capture an image, along with the reason. For example, the reasons may include, but are not limited to, “POI name not visible”, “no visible POI found in image”, etc. Thereafter, the computing device 160 may receive a feedback about the request for adding the new POI for the place from the processor 120.

[0099] In some embodiments, the user 170 may review the auto-filled key attributes, edit the key attributes if necessary (411), and submit the tasks (for example, the request for adding the new POI for the place, in the form of the submission form) for review by the backend pipeline (412).

[0100] As shown in FIG. 6, in some embodiments, the processor 120 may perform postchecks. In some embodiments, for the submission form that the processor 120 determines to be valid POIs with a high degree of confidence, the processor 120 may ingest the submission form into a POI database for post-checks. For example, the processor 120 may check the POI database, to check an internal duplication of the new POI (for example, if the POI already exists in the POI database). Thereafter, the processor 120 may enrich the duplicated POI (416), and reject the request for adding the new POI for the place, and provide a feedback (417). In some embodiments, the processor 120 may check PII (Personally Identifiable Information) detecting and masking, and perform an integrity check (for example, sensitive words removal) (418). In some embodiments, the processor 120 may determine if the request for adding the new POI for the place meets a predetermined SOP (Standard Operating Procedure) (also referred to as a “predetermined standards”) of the on-demand service platform provider. If it is determined that the request for adding the new POI for the place does not meet the predetermined SOP, the processor 120 may reject the request for adding the new POI for the place, and provide a feedback (419). If it is determined that the request for adding the new POI for the place meets the predetermined SOP, the processor 120 may extract the name of the POI, and the key attributes of the POI from the request for adding the new POI for the place (for example, thesubmission form) (420), and ingest the request for adding the new POI for the place (for example, the submission form) into the POI database (421). Thereafter, the processor 120 may accept the request for adding the new POI for the place, and provide a feedback (422). Thereafter, the computing device 160 may receive a feedback about the request for adding the new POI for the place from the processor 120 (413).

[0101] As described above, the various embodiments may utilise any multi-modal model combined with key attribute extractions from images / videos. It may be appreciated that the various embodiments may use a combination of the LLM and the prompt, but are not limited thereto. For example, as an extension, the various embodiments may also be used to incorporate other modalities, such as speech. This may further facilitate a text editing process for the user 170 and assist in collecting additional POI key attributes.

[0102] FIGS. 7 to 10 illustrate exemplary diagrams for creating a request for adding a new POI (Point of Interest) for a place according to various embodiments. FIGS. 11 to 13 illustrate exemplary diagrams for creating a request for adding a plurality of new POIs (Points of Interest) for a plurality of places according to various embodiments.

[0103] As shown in FIG. 7(a), in some embodiments, a computing device 160 associated with a user 170 may display a screen relating to a user interface of an application provided by a server 100. In some embodiments, the user interface may allow the user 170 to add the new POI for the place, to incorporate a new location into the map. In some embodiments, the user interface may further allow the user 170 to verify the place, by verifying information and filling in missing details. In some embodiments, the user interface may further allow the user 170 to review submissions (for example, the request for adding the new POI for the place) to wrap up the entries and rejected images (photos). In this manner, the user 170 may contribute to the map via the user interface of the application.

[0104] As shown in FIG. 7(b), in some embodiments, the computing device 160 may display a screen to add the new POI for the place. In some embodiments, the user may select an icon to take an image, for example, a single image (a photo), multiple images, or a video using an image capturing module 164.

[0105] As shown in FIG. 8(a), in some embodiments, the computing device 160 may take the photo for an external environment including a place, using the image capturing module 164.

[0106] As shown in FIG. 8(b), in some embodiments, after the computing device 160 takes the photo for the external environment including the place, the computing device 160 may display a screen to upload the photo for the place. In some embodiments, the user 170 may upload at least one additional photo for the place (if any). In some embodiments, a processor 120 of the server 100 may extract at least one information about the place using the photo, and create the request for adding the new POI for the place using the extracted information.

[0107] As shown in FIG. 9(a), in some embodiments, the computing device 160 may display a submission form requesting the name of the place, and the name of the place which is extracted from the photo (for example, “A Fashion”) may automatically be filled in the submission form.

[0108] As shown in FIG. 9(b), in some embodiments, the computing device 160 may display the submission form requesting a category of the place, and the category of the place which is extracted from the LLM (for example, “Shop”) may automatically be filled in the submission form.

[0109] As shown in FIG. 10(a), in some embodiments, the computing device 160 may display the submission form requesting an address of the place, and the address of the place which is extracted from a reverse geographical module (for example, “1 ABC Road, Singapore”) may automatically be filled in the submission form.

[0110] As shown in FIG. 10(b), in some embodiments, the computing device 160 may display the submission form requesting the user 170 to input other remarks about the place.

[0111] In some embodiments, if the image capturing module 164 captures the multiple images or the video, there may be multiple POIs each corresponding to the multiple images or multiple key frames of the video. As shown in FIG. 11(a), in some embodiments, the computing device 160 may display a screen for adding another POI for another place to the map. For example, the processor 120 may extract the name of the another place from another photo or another key frame of the video (for example, “B Cafe”), and the computing device 160 may display the name of the another place on the screen.

[0112] As shown in FIG. 11(b), in some embodiments, the computing device 160 may display another submission form requesting the name of the another place, and the name of the another place which is extracted from another photo or another key frame of the video (for example, “B Cafe”) may automatically be filled in the submission form.

[0113] As shown in FIG. 12(a), in some embodiments, the computing device 160 may display the submission form requesting a category of the another place, and the category of the another place which is extracted from the LLM (for example, “Cafe”) may automatically be filled in the submission form.

[0114] As shown in FIG. 12(b), in some embodiments, the computing device 160 may display the submission form requesting an address of the another place, and the address of the another place which is extracted from the reverse geographical module (for example, “ 1 ABC Road, Singapore”) may automatically be filled in the submission form.

[0115] As shown in FIG. 13(a), in some embodiments, the computing device 160 may display the another submission form requesting the user 170 to input other remarks about the another place.

[0116] As shown in FIG. 13(b), in some embodiments, the computing device 160 may submit the submission form and the another submission form. Thereafter, the submission forms may be sent to a backend pipeline, for a validator’s review. After the validator’s review, the computing device 160 may receive a feedback about whether the submission forms are approved or rejected.

[0117] FIGS. 14 and 15 illustrate exemplary diagrams for requesting a computing device to obtain a new image of a place according to various embodiments.

[0118] As shown in FIG. 14(a), in some embodiments, the computing device 160 may display the submission form requesting the user 170 to input other remarks about the place. After the user 170 submits the submission form, if the processor 120 determines that the clarity of the photo is below a predetermined threshold, the processor 120 may request the computing device 160 to obtain a new photo of the place, as shown in FIG. 14(b). In some embodiments, the computing device 160 may take the new photo for the place, using the image capturing module 164. As shown in FIG. 15, in some embodiments, after the computing device 160 takes the new photo for the place, the computing device 160 may display a screen to upload the new photo for the place. In some embodiments, the user 170 may upload at least one additional new photo for the place (if any).

[0119] As described above, according to various embodiments, the below steps may be performed.Step 1) User 170 (mapper): Based on the (mandatory) image(s) or (short) videos of the PO1 taken by the user 170, informing the user 170 immediately if:a. The image is not clear, the POI name is not visible, it is blurry, and / or the POI is invalid.The server 100 may request the user 170 to retake the photo.b. Using OCR, extracting the POI’s name and other metadata, such as its category, telephone number, and opening hours if available.c. Auto-filling the submission form with details extracted in step b to make the submission process less cumbersome for the user 170. By pre-filling the submission form based on the image submitted, the user 170 may also function as a map validator for the extracted content, such as name, opening hours, contact numbers, etc., for the POI based on the image itself.Step 2) Automation: For submission forms that the Al model(s) determines to be valid POIs with a high degree of confidence (for example, if it is determined to accept the request for adding the new POI for the place and the confidence score is equal to or greater than a predetermined score), the server 100 may directly ingest them into the POI database for postchecks such as an internal duplication (for example, the POI already exists in the POI database), PII (Personally Identifiable Information) masking, integrity checks (sensitive words removal), etc.Step 3) The server 100 may also automatically reject the submission forms that do not conform to the predetermined standards, such as invalid POIs, images from the Internet, screenshots, and bad images. For example, the initial estimates may suggest upwards of 80% automation rates, including automatic acceptance / rej ection cases.Step 4) Map validators: For submission forms with lower confidence of acceptance (for example, if the confidence score is less than the predetermined score), the server 100 may enlist the map validators to manually vet the submission forms before accepting (for example, ingesting the POIs into the POI database) or rejecting the submission forms.In some embodiments, the step 1) may be achieved on the edge, for example, on the application running on the computing device 160, while the steps 2) and 3) may involve an offline processing pipeline before accepting or rejecting the submission forms.

[0120] The Al-enabled POI creation workflow according to various embodiments may have the following advantages:a) Increased user (mapper) engagement: More users 170 may be engaged with the mapping application, as the submission process may be seamless and less cumbersome, as much of the data may be pre-filled in the submission form after just taking the image and provide real time feedback in case the captured images / video are of unacceptable quality.b) Instantaneous POI creation: The high automation rates may ensure that the server 100 may create POIs within a few minutes of the mapper’s submission, depending on the volume of submissions.c) Map validators: Map validators may have fewer tasks to validate, thus reducing the turnaround times for POI creations. Further, the obviously bad submissions may be rejected at the top of the funnel, increasing the quality of tasks reaching the validators. Bad submissions may include those POI creation tasks with bad (blurry and non-POI images) or fraudulent (screenshots from websites instead of actual images from the POI location) images or incorrect text. Automating a large percentage of tasks for creating POIs via crowdsourcing without compromising on quality may ensure significant cost reduction as fewer map validators are required.

[0121] As described above, the various embodiments may revamp the conventional frontend design to minimise the user’s 170 clicks for the submission. A noticeable distinction may be the time. According to the various embodiments, the time taking for the user 170 to submit the submission form may drop to approximately 50%. To incorporate the real-time extraction of the key attributes for filling the submission form (for example, business category, POI name, house number, etc.), the server 100 may prompt the LLM and auto-filling for the user 170 to review. For pre-filling address information, the server 100 may use the reverse geographical module.

[0122] It may be appreciated that, the various embodiments may be used with various crowdsource based reporting systems, for example, POI details, a function to add a missing place / POI and verify details of places on the map (for example, MYC (Map Your City) function of the on-demand service platform), a function to report real-time incidents (for example, RTI (Real Time Incident) function of the on-demand service platform), Karta Al camera and other generic hardware devices such as dash cams that allow image / video capturing and / or text-based inputs. It may be appreciated that the various embodiments may be used in various regions / countries with limited efforts required to tune the system for local languages. This may serve as a key POI creation channel for Geo’s B2B offerings.

[0123] In the following, various examples of this disclosure are illustrated:

[0124] Example 1 is a server for facilitating adding a new POI (Point of Interest) to a map, the server comprising: a memory configured to store instructions; and a processor for executing the stored instructions and configured to: obtain an image capturing at least one place from a computing device associated with a user; extract at least one information about the place using the image, wherein the at least one information is of a predetermined type; and create a request for adding the new POI for the place using the extracted information, wherein if the request for adding the new POI for the place is accepted, the new POI for the place is added to the map, based on the extracted information.

[0125] Example 2 is the server of Example 1, wherein the processor is further configured to: determine if a clarity of the image is below a predetermined threshold; and if it is determined that the clarity of the image is below the predetermined threshold, request the computing device to obtain a new image of the place.

[0126] Example 3 is the server according to Example 1 or Example 2, wherein the processor is further configured to: submit the request for adding the new POI for the place.

[0127] Example 4 is the server according to Example 3, wherein the processor is further configured to: automatically fill required information about the place in a submission form, based on the extracted information; and submit the submission form as the request for adding the new POI for the place.

[0128] Example 5 is the server according to Example 4, wherein the processor is further configured to: output the automatically filled information to the computing device; receive an input about the automatically filled information from the user; and correct the automatically filled information based on the input from the user.

[0129] Example 6 is the server according to any one of Examples 1 to 5, wherein the processor is further configured to: determine whether to accept the request for adding the new POI for the place; and determine a confidence score of the determination on whether to accept the request for adding the new POI for the place.

[0130] Example 7 is the server according to Example 6, wherein the processor is further configured to: if it is determined to accept the request for adding the new POI for the place and the confidence score is equal to or greater than a predetermined score, input the request for adding the new POI for the place into a POI database, to conduct at least one predetermined check before adding the new POI for the place.

[0131] Example 8 is the server according to Example 7, wherein the processor is further configured to: if it is determined to reject the request for adding the new POI for the place and the confidence score is equal to or less than the predetermined score, reject the request for adding the new POI for the place.

[0132] Example 9 is the Example 7 or Example 8, wherein the processor is further configured to: if the confidence score is in a predetermined score range, send the request for adding the new POI for the place to a validator, to receive a confirmation of an acceptance or a rejection of the request for adding the new POI for the place.

[0133] Example 10 is the server according to any one of Examples 1 to 9, wherein the predetermined type includes at least one of a name, an address, and a category of the place.

[0134] Example 11 is a method for facilitating adding a new POI (Point of Interest) to a map, the method comprising: obtaining an image capturing at least one place from a computing device associated with a user; extracting at least one information about the place using the image, wherein the at least one information is of a predetermined type; and creating a request for adding the new POI for the place using the extracted information, wherein if the request for adding the new POI for the place is accepted, the new POI for the place is added to the map, based on the extracted information.

[0135] Example 12 is the method according to Example 11, further comprising: determining if a clarity of the image is below a predetermined threshold; and if it is determined that the clarity of the image is below the predetermined threshold, requesting the computing device to obtain a new image of the place.

[0136] Example 13 is the method according to Example 11 or Example 12, further comprising: submitting the request for adding the new POI for the place.

[0137] Example 14 is the method according to Example 13, further comprising: automatically filling required information about the place in a submission form, based on the extracted information; and submitting the submission form as the request for adding the new POI for the place.

[0138] Example 15 is the method according to Example 14, further comprising: outputting the automatically filled information to the computing device; receiving an input about the automatically filled information from the user; and correcting the automatically filled information based on the input from the user.

[0139] Example 16 is the method according to any one of Examples 11 to 15, further comprising: determining whether to accept the request for adding the new POI for the place;and determining a confidence score of the determination on whether to accept the request for adding the new POI for the place.

[0140] Example 17 is the method according to Example 16, further comprising: if it is determined to accept the request for adding the new POI for the place and the confidence score is equal to or greater than a predetermined score, inputting the request for adding the new POI for the place into a POI database, to conduct at least one predetermined check before adding the new POI for the place.

[0141] Example 18 is the method according to Example 17, further comprising: if it is determined to reject the request for adding the new POI for the place and the confidence score is equal to or less than the predetermined score, rejecting the request for adding the new POI for the place.

[0142] Example 19 is the method according to Example 17 or Example 18, further comprising: if the confidence score is in a predetermined score range, sending the request for adding the new POI for the place to a validator, to receive a confirmation of an acceptance or a rejection of the request for adding the new POI for the place.

[0143] Example 20 is the method according to any one of Examples 11 to 19, wherein the predetermined type includes at least one of a name, an address, and a category of the place.

[0144] While the disclosure has been particularly shown and described with reference to specific embodiments, it should be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. The scope of the invention is thus indicated by the appended claims and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced.

Claims

CLAIMS1. A server for facilitating adding a new POI (Point of Interest) to a map, the server comprising:a memory configured to store instructions; anda processor for executing the stored instructions and configured to:obtain an image capturing at least one place from a computing device associated with a user;extract at least one information about the place using the image, wherein the at least one information is of a predetermined type; andcreate a request for adding the new POI for the place using the extracted information, wherein if the request for adding the new POI for the place is accepted, the new POI for the place is added to the map, based on the extracted information.

2. The server according to claim 1, wherein the processor is further configured to:determine if a clarity of the image is below a predetermined threshold; and if it is determined that the clarity of the image is below the predetermined threshold, request the computing device to obtain a new image of the place.

3. The server according to claim 1, wherein the processor is further configured to:submit the request for adding the new POI for the place.

4. The server according to claim 3, wherein the processor is further configured to:automatically fill required information about the place in a submission form, based on the extracted information; andsubmit the submission form as the request for adding the new POI for the place.

5. The server according to claim 4, wherein the processor is further configured to:output the automatically filled information to the computing device;receive an input about the automatically filled information from the user; and correct the automatically filled information based on the input from the user.

6. The server according to claim 1, wherein the processor is further configured to:determine whether to accept the request for adding the new POI for the place; and determine a confidence score of the determination on whether to accept the request for adding the new POI for the place.

7. The server according to claim 6, wherein the processor is further configured to:if it is determined to accept the request for adding the new POI for the place and the confidence score is equal to or greater than a predetermined score, input the request for adding the new POI for the place into a POI database, to conduct at least one predetermined check before adding the new POI for the place.

8. The server according to claim 7, wherein the processor is further configured to:if it is determined to reject the request for adding the new POI for the place and the confidence score is equal to or less than the predetermined score, reject the request for adding the new POI for the place.

9. The server according to claim 8, wherein the processor is further configured to:if the confidence score is in a predetermined score range, send the request for adding the new POI for the place to a validator, to receive a confirmation of an acceptance or a rejection of the request for adding the new POI for the place.

10. The server according to claim 1, wherein the predetermined type includes at least one of a name, an address, and a category of the place.

11. A method for facilitating adding a new POI (Point of Interest) to a map, the method comprising:obtaining an image capturing at least one place from a computing device associated with a user;extracting at least one information about the place using the image, wherein the at least one information is of a predetermined type; andcreating a request for adding the new POI for the place using the extracted information, wherein if the request for adding the new POI for the place is accepted, the new POI for the place is added to the map, based on the extracted information.

12. The method according to claim 11, further comprising:determining if a clarity of the image is below a predetermined threshold; and if it is determined that the clarity of the image is below the predetermined threshold, requesting the computing device to obtain a new image of the place.

13. The method according to claim 11, further comprising:submitting the request for adding the new POI for the place.

14. The method according to claim 13, further comprising:automatically filling required information about the place in a submission form, based on the extracted information; andsubmitting the submission form as the request for adding the new POI for the place.

15. The method according to claim 14, further comprising:outputting the automatically filled information to the computing device; receiving an input about the automatically filled information from the user; and correcting the automatically filled information based on the input from the user.

16. The method according to claim 11, further comprising:determining whether to accept the request for adding the new POI for the place; and determining a confidence score of the determination on whether to accept the request for adding the new POI for the place.

17. The method according to claim 16, further comprising:if it is determined to accept the request for adding the new POI for the place and the confidence score is equal to or greater than a predetermined score, inputting the request for adding the new POI for the place into a POI database, to conduct at least one predetermined check before adding the new POI for the place.

18. The method according to claim 17, further comprising:if it is determined to reject the request for adding the new POI for the place and the confidence score is equal to or less than the predetermined score, rejecting the request for adding the new POI for the place.

19. The method according to claim 18, further comprising:if the confidence score is in a predetermined score range, sending the request for adding the new POI for the place to a validator, to receive a confirmation of an acceptance or a rejection of the request for adding the new POI for the place.

20. The method according to claim 11, wherein the predetermined type includes at least one of a name, an address, and a category of the place.

Images