Electronic device and method for providing information thereof

Abstract

A method for providing information from an electronic device is disclosed. The method for providing information may include the steps of: obtaining a first location dataset relating to a first route from a first origin to a first destination and a second location dataset relating to a second route from the first origin to the first destination; confirming a first geospatial index set corresponding to the first location dataset and a second geospatial index set corresponding to the second location dataset; confirming the number of common indices between the first geospatial index set and the second geospatial index set based on a set algorithm; and determining the similarity between the first route and the second route based on the number of common indices.

Description

Technical Field

[0001] The present disclosure relates to an electronic device and a control method thereof for evaluating the similarity between various routes from the same starting point to the same destination and providing information regarding the similarity.

Background Art

[0002] As the use of the Internet becomes widespread, the market for e-commerce is expanding. In particular, due to the spread of infectious diseases, there is a tendency for the interest in the field of e-commerce / online shopping where non-face-to-face product purchases are possible to increase rapidly.

[0003] The delivery of items such as fresh food, frozen food, delivered food, flowers, and plants requires delivery while maintaining certain conditions such as freshness and warmth, or rapid delivery, compared to the delivery of general items. Therefore, there is an increasing need to provide the optimal route for a delivery person to move from the starting point to the destination.

[0004] In relation to this, prior art documents such as KR10-2403710B1 can be referred to.

Summary of the Invention

Problems to be Solved by the Invention

[0005] The disclosed embodiments seek to provide an electronic device and an information providing method thereof. More specifically, an object is to provide an electronic device and a control method thereof for evaluating the similarity between various routes from the same starting point to the same destination and providing information regarding the similarity.

[0006] The technical problems to be achieved by the present embodiment are not limited to the above technical problems, and other technical problems can be analogized from the following embodiments.

Means for Solving the Problems

[0007] One aspect of this disclosure can provide an information provision method that includes the steps of: acquiring a first location dataset relating to a first route from a first origin to a first destination and a second location dataset relating to a second route from the first origin to a first destination; verifying a first geospatial index set corresponding to the first location dataset and a second geospatial index set corresponding to the second location dataset; verifying the number of common indices between the first geospatial index set and the second geospatial index set based on a set algorithm; and determining the similarity between the first route and the second route based on the number of common indices.

[0008] Furthermore, in one embodiment of the present disclosure, an information provision method can be provided in which the steps of verifying the first geospatial index set and the second geospatial index set include verifying the geospatial cells that cover the coordinates of the location data of the first location dataset and the second location dataset; and verifying the first geospatial index set and the second geospatial index set based on the index corresponding to the geospatial cell.

[0009] Furthermore, in one embodiment of this disclosure, an information provision method can be provided in which the size of the geospatial cell is determined by a measurement accuracy set by the operator.

[0010] Furthermore, in one embodiment of the present disclosure, an information provision method can be provided in which the step of determining the number of common indices between the first geospatial index set and the second geospatial index set includes the step of determining the distance between each of the multiple first geospatial cells corresponding to the first geospatial index set and the multiple second geospatial cells corresponding to the second geospatial index set; and the step of determining one or more indices whose distance is less than or equal to a critical value as common indices.

[0011] Furthermore, in one embodiment of the present disclosure, an information provision method can be provided in which the critical value is determined based on at least one of the following: measurement accuracy set by an operator; order quantity generated within a set radius from the first origin or first destination during the most recently set time; performance of the map engine that provided the first or second route; data throughput; and data transmission delay time.

[0012] Furthermore, in one embodiment of this disclosure, an information provision method can be provided in which the critical value is determined to be smaller as the measurement accuracy is higher, the order quantity is smaller, the performance of the map engine is higher, the data throughput is higher, or the data transfer delay time is shorter.

[0013] Furthermore, in one embodiment of the present disclosure, an information provision method can be provided in which the similarity between the first route and the second route is determined by a value obtained by dividing twice the number of common indices by the sum of the number of first geospatial cells corresponding to the first geospatial index set and the number of second geospatial cells corresponding to the second geospatial index set.

[0014] Furthermore, in one embodiment of the present disclosure, the first route includes the route actually traveled by the first delivery person, the second route includes the route provided by the first map engine, and the information provision method can be provided, further comprising the step of determining a score for the first map engine based on the similarity between the first route and the second route.

[0015] Furthermore, in one embodiment of this disclosure, an information provision method can be provided in which the score of the first map engine is determined to be higher the higher the similarity between the first route and the second route.

[0016] Furthermore, in one embodiment of the present disclosure, the information provision method may further include a step of confirming the actual travel time of the first delivery person via the first route and the estimated travel time via the second route, wherein the score of the first map engine is determined by further considering the difference between the actual travel time and the estimated travel time.

[0017] Furthermore, in one embodiment of this disclosure, an information provision method can be provided in which the score of the first map engine is determined to be higher the faster the predicted travel time is compared to the actual travel time.

[0018] Furthermore, in one embodiment of the present disclosure, the information provision method can be provided, further comprising the steps of: receiving a first recommendation request regarding a route from a first origin to a first destination from the terminal of a first delivery person; and confirming a first time zone corresponding to the time the first recommendation request was received, wherein the similarity between the first route and the second route is determined by the similarity with respect to the first time zone.

[0019] Furthermore, in one embodiment of the present disclosure, the information provision method can be provided, further comprising the steps of: receiving a first recommendation request regarding a route from a first origin to a first destination from the terminal of a first delivery person; confirming the order quantity generated within a set radius from the first origin or first destination within a set time after receiving the first recommendation request; and confirming a first order quantity interval corresponding to the order quantity, wherein the similarity between the first route and the second route is determined by the similarity with respect to the first order quantity interval.

[0020] Furthermore, in one embodiment of the present disclosure, the information provision method further includes the steps of: receiving a first recommendation request regarding a route from a first departure point to a first destination from the terminal of a first delivery person; confirming the degree of traffic congestion within a radius set from the first departure point or the first destination when the first recommendation request is received; and confirming a first traffic congestion section corresponding to the degree of traffic congestion, wherein the similarity between the first route and the second route is determined by the similarity with respect to the first traffic congestion section.

[0021] Furthermore, in one embodiment of the present disclosure, the information provision method can be provided, further comprising the steps of: receiving a second recommendation request regarding a route from a second origin to a second destination from the terminal of a second delivery person; obtaining information regarding one or more routes from the second origin to the second destination provided by one or more map engines; confirming the scores of each of the one or more map engines, which have already been determined based on the similarity between routes previously provided by the one or more map engines and routes previously traveled by the second delivery person; and transmitting information regarding the route provided by the map engine having the highest score among the one or more map engines to the terminal of the second delivery person.

[0022] Furthermore, in one embodiment of the present disclosure, the information provision method can be provided, further comprising the steps of: obtaining information on one or more routes taken by one or more delivery personnel from a third origin to a third destination; determining the similarity between the one or more routes; and determining the route among the one or more routes that has the highest similarity to the other routes as the recommended route from the third origin to the third destination.

[0023] Other aspects of the present disclosure include a transceiver, a memory, and a processor. The processor acquires a first position data set regarding a first route from a first departure location to a first destination and a second position data set regarding a second route from the first departure location to the first destination, identifies a first geo-spatial index set corresponding to the first position data set and a second geo-spatial index set corresponding to the second position data set, determines the number of common indexes between the first geo-spatial index set and the second geo-spatial index set based on a set algorithm, and determines the similarity between the first route and the second route based on the number of the common indexes. An electronic device can be provided.

[0024] Still other aspects of the present disclosure can provide a computer-readable recording medium on which a program for implementing a method performed by an electronic device is recorded.

[0025] Specific matters of other embodiments are included in the detailed description and the drawings.

Advantages of the Invention

[0026] In the case of the proposed embodiments, one or more of the following effects can be expected.

[0027] In the case of the embodiments of this specification, by quantitatively analyzing the similarity between various routes having the same departure location and destination, the rationality of each route can be evaluated.

[0028] Also, in the case of the embodiments of this specification, by adaptively determining a threshold value based on various parameters, the reliability and accuracy of information regarding the similarity between one or more routes can be improved.

[0029] Furthermore, according to the embodiments of this specification, the electronic device can provide a recommended route based on a similarity determined by the time of day the recommendation request was received, the order quantity interval, or the traffic congestion interval, thereby providing the delivery person with the most optimal route.

[0030] Furthermore, according to the embodiments of this specification, the electronic device can recommend the route that is most similar to other routes among the routes actually traveled by the delivery person, thereby recommending an optimized route to the delivery person based on the delivery person's experience.

[0031] The effects of the invention are not limited to those mentioned above, and any other effects not mentioned can be clearly understood by those skilled in the art from the description of the claims. [Brief explanation of the drawing]

[0032] [Figure 1] A system according to one embodiment is shown. [Figure 2] This figure illustrates, in one embodiment, the process by which an electronic device provides information regarding the similarity between one or more paths. [Figure 3] This figure illustrates, in one embodiment, the process by which an electronic device provides information regarding the similarity between one or more paths. [Figure 4] This figure illustrates, in one embodiment, the process by which an electronic device provides information regarding the similarity between one or more paths. [Figure 5a] This figure illustrates, according to one embodiment, the process by which an electronic device determines the similarity between one or more paths. [Figure 5b] This figure illustrates, according to one embodiment, the process by which an electronic device determines the similarity between one or more paths. [Figure 5c] This figure illustrates, according to one embodiment, the process by which an electronic device determines the similarity between one or more paths. [Figure 5d] This figure illustrates, according to one embodiment, the process by which an electronic device determines the similarity between one or more paths. [Figure 5e] This figure illustrates, according to one embodiment, the process by which an electronic device determines the similarity between one or more paths. [Figure 6] A flowchart of an information provision method for an electronic device according to one embodiment is shown. [Figure 7] A block diagram of an electronic device according to one embodiment is shown. [Modes for carrying out the invention]

[0033] The terminology used in the embodiments has been selected, to the greatest extent possible, to be widely used and common terminology, taking into account the function described herein, although this may change depending on the intent of the articulators, case law, the emergence of new technologies, etc. In certain cases, the applicant has also selected some terms at their discretion, in which case their meaning will be described in detail in the relevant explanatory section. Therefore, the terminology used in this disclosure must be defined not merely as names of terms, but based on the meaning of the term and the overall content of this disclosure.

[0034] When a part of the specification "includes" a certain component, unless otherwise stated, this means that it may include other components rather than excluding them.

[0035] Throughout this specification, the expression “at least one of a, b, and c” may encompass “a alone,” “b alone,” “c alone,” “a and b,” “a and c,” “b and c,” or “all of a, b, and c.”

[0036] The term "terminal" as used below can be embodied in computers or portable devices that can connect to servers or other terminals via a network. Here, computers include, for example, laptops, desktops, and laptops equipped with a web browser, while portable devices can include, for example, all kinds of handheld-based wireless communication devices such as IMT (International Mobile Telecommunication), CDMA (Code Division Multiple Access), W-CDMA (W-Code Division Multiple Access), LTE (Long Term Evolution) terminals, smartphones, and tablet PCs, as long as portability and mobility are guaranteed.

[0037] The embodiments of this disclosure will be described below in detail, with reference to the accompanying drawings, so that they can be easily implemented by a person with ordinary skill in the art to which this disclosure pertains. However, this disclosure may be embodied in several different forms and is not limited to the embodiments described herein.

[0038] The embodiments of this disclosure will be described in detail below with reference to the drawings.

[0039] Figure 1 shows a system according to one embodiment.

[0040] Referring to Figure 1, the system may include at least one of the following: an electronic device 100, a worker terminal 120, a delivery person terminal 140, a user terminal 160, and a network 180. However, the system shown in Figure 1 only shows the components relevant to this embodiment. Therefore, it will be understood by a person with ordinary skill in the art related to this embodiment that, in addition to the components shown in Figure 1, other general-purpose components may be included.

[0041] The electronic device 100 is a device that configures and provides diverse information. The electronic device 100 can provide the configured information on a web page or application screen, or in a form that can be displayed on a web page or application screen on a receiving terminal.

[0042] According to one embodiment, the electronic device 100 can determine the similarity between various routes from the same origin to the same destination and provide various information based on the determined similarity. For example, the electronic device 100 can acquire a first location dataset for a first route from a first origin to a first destination and a second location dataset for a second route from the first origin to a first destination, and can confirm a first geospatial index set corresponding to the first location dataset and a second geospatial index set corresponding to the second location dataset. Furthermore, the electronic device 100 can confirm the number of common indices between the first geospatial index set and the second geospatial index set based on a set algorithm, and can determine the similarity between the first and second routes based on the number of common indices.

[0043] The worker terminal 120 is a terminal used by the worker, and the worker can set various parameters related to the similarity between one or more paths using an application or platform installed on the worker terminal 120. For example, the worker can set the measurement accuracy using the worker terminal 120, and the electronic device 100 can determine a critical value that serves as the basis for determination, based on the set measurement accuracy, using the size of the geospatial cell or a common index.

[0044] Each delivery driver terminal 140 is a terminal used by each delivery driver, and the drivers can use the application installed on their terminal 140 to check information about the orders they are assigned. For example, each driver can use their terminal 140 to check information about the delivery tasks assigned to them and can input whether they have completed or refused the assigned delivery tasks. In addition, each driver may be provided with one or more routes from the origin to the destination corresponding to the assigned order using their terminal 140.

[0045] In this context, the delivery person may include an entity that takes over the items from the seller and delivers them to the customer, and the delivery person's means of delivery may include a variety of forms such as walking, motorcycles, bicycles, automobiles, drones, and rail.

[0046] Each user terminal 160 is a terminal used by each user, and each user can use their terminal 160 to access services provided by the network 180. For example, the electronic device 100 can provide the user terminal 160 with an application to provide information related to ordering various items, and users can order various items using the application installed on their terminal 160. Alternatively, users can use their terminal 160 to check real-time delivery information regarding item orders. In this case, the user may include the entity that ordered the delivery of the items.

[0047] The worker terminal 120, the delivery person terminal 140, and the user terminal 160 and the electronic device 100 can communicate with each other within the network 180. The network 180 is a comprehensive data communication network that includes local area networks (LANs), wide area networks (WANs), value-added networks (VANs), mobile radio communication networks, satellite communication networks, and combinations thereof, enabling the constituent entities of each network shown in Figure 1 to communicate smoothly with each other, and may include wired internet, wireless internet, and mobile wireless communication networks. Wireless communication may include, but is not limited to, wireless LAN (Wi-Fi), Bluetooth (registered trademark, same hereinafter), Bluetooth Low Energy, Zigbee, WFD (Wi-Fi Direct), UWB (ultra wideband), infrared communication (IrDA, infrared Data Association), NFC (Near Field Communication), etc.

[0048] Figure 2 is a diagram illustrating the process by which an electronic device 100 provides information regarding the similarity between one or more paths, according to one embodiment.

[0049] In step S200, the electronic device 100 can, in one embodiment, receive order-related information from the user terminal 160. For example, the user terminal 160 can receive information from the electronic device 100 in a form that can be displayed on a web page or application screen, and based on the received information, can display a user interface on its display that allows the user to order various items. Subsequently, the user terminal 160 can obtain input from the user ordering items at a store located at the first departure point, and can transmit order-related information, including information about the items ordered by the user and information about the first destination set by the user as the delivery address, to the electronic device 100.

[0050] In step S210, the electronic device 100 can, in one embodiment, confirm one or more routes from a first origin to a first destination. For example, the electronic device 100 can obtain a location dataset relating to the route from the first origin to the first destination from a map engine that exists as a separate module inside. Alternatively, the electronic device 100 can obtain a location dataset relating to the route from the first origin to the first destination from a map engine of an externally provided map service.

[0051] In this context, the map engine, which outputs the optimal route for a delivery person to travel from their starting point to their destination based on various information such as road specifications, obstacle information, delivery person's means of delivery, and traffic congestion, may be referred to as a map module or map application, but the terminology used is not limited to those mentioned above.

[0052] According to one embodiment, the electronic device 100 can determine a recommended route from among one or more routes based on the scores of one or more map engines that provide one or more routes. For example, the electronic device 100 can check the scores of one or more map engines that have already been determined based on the similarity between the routes previously provided by each of the one or more map engines and the routes previously traveled by delivery personnel. Subsequently, the electronic device 100 can determine the route provided by the map engine with the highest score among the one or more map engines as the recommended route.

[0053] In this case, the score of each of the one or more map engines may be determined to be higher the more similar the routes previously provided by each of the one or more map engines are to the routes previously traveled by the delivery person. Alternatively, the score of each of the one or more map engines may be determined to be higher the more the estimated travel time based on the routes previously provided by each of the one or more map engines is faster than the actual time it took the delivery person to travel.

[0054] In step S220, the electronic device 100 can, in one embodiment, transmit order information and information about one or more routes to the delivery person terminal 140. For example, the electronic device 100 can assign an order to a delivery person and transmit to the delivery person terminal 140 at least one of the following: information about a first origin, information about a first destination, information about one or more routes from the first origin to the first destination, information about the estimated travel time for each of the one or more routes, and information about a recommended route among the one or more routes.

[0055] In step S230, the delivery terminal 140 can, in one embodiment, provide the delivery person with one or more routes from the first departure point to the first destination. For example, the delivery terminal 140 can receive information from the electronic device 100 in a form that can be displayed on a web page or application screen, and based on the received information, can display on the display information about one or more routes from the store (the departure point) to the delivery destination, as well as information about a recommended route among the one or more routes.

[0056] In step S240, the electronic device 100 can receive information from the delivery person terminal 140 regarding the first route actually traveled by the delivery person. More specifically, the delivery person terminal 140 can transmit time data and location data sets generated by the delivery person's movement along the first route to the electronic device 100.

[0057] For example, the delivery terminal 140 can transmit GPS (global positioning system) values ​​acquired at set time intervals or timestamps to the electronic device 100. That is, route information R can be represented by time data and location data sets as follows.

[0058] [Mathematics 1] R=(p_0,p_1,p_2,...,p_n) p_i=(ts_i,lon_i,lat_i),(i<=j,ts_i<=ts_j)

[0059] Here, ts_i may represent the i-th timestamp, lon_i may represent the i-th longitude value, and lat_i may represent the i-th latitude value. However, the types of data included in the time and location datasets are not limited to those described above.

[0060] In step S250, the electronic device 100 can determine the similarity between a first route and one or more routes according to one embodiment. For example, the electronic device 100 can check a first location dataset relating to the first route traveled by the delivery person and a second location dataset relating to a second route among one or more routes, and can check a first geospatial index set corresponding to the first location dataset and a second geospatial index set corresponding to the second location dataset. Subsequently, the electronic device 100 can check the number of common indices between the first geospatial index set and the second geospatial index set based on a set algorithm, and can determine the similarity between the first route and the second route based on the number of common indices.

[0061] In this context, similarity can refer to a value that indicates the degree of similarity between different routes from the same starting point to the same destination, but the terminology used to describe it is not limited to those mentioned above.

[0062] According to one embodiment, the electronic device 100 can identify a first geospatial index set and a second geospatial index set based on geospatial cells corresponding to the coordinates of the location data. More specifically, the electronic device 100 can identify geospatial cells covering the coordinates of the location data in the first location dataset and the second location dataset, and then identify the first geospatial index set and the second geospatial index set based on the index corresponding to the geospatial cell.

[0063] For example, the electronic device 100 can identify the H3 cells that cover the coordinates of the position data in the first position dataset and the second position dataset, and identify the H3 index corresponding to the H3 cell. That is, the electronic device 100 can convert the path information R into a sequence of H3 indices as follows.

[0064] [Math 2] R→H3Seq=(H3Id_0,H3Id_1,H3Id_2,...,H3Id_n)

[0065] Here, H3Id can represent an index expressed as a 64-bit integer.

[0066] On the other hand, the electronic device 100 can use H3, a geospatial indexing system that divides the entire world into hexagonal cells, to identify geospatial cells corresponding to location datasets. However, this is only one embodiment, and the electronic device 100 can use a variety of geospatial indexing systems such as geohash and S2.

[0067] According to one embodiment, the electronic device 100 can determine the size of a geospatial cell based on the measurement accuracy set by the operator. For example, if the operator sets a high measurement accuracy, the electronic device 100 can determine a smaller size for the geospatial cell. Alternatively, if the operator sets a low measurement accuracy, the electronic device 100 can determine a larger size for the geospatial cell.

[0068] According to one embodiment, the electronic device 100 can determine a common index based on a critical value relating to the distance between geospatial cells corresponding to a geospatial index set. More specifically, the electronic device 100 can check the distances between each of the multiple first geospatial cells corresponding to a first geospatial index set and the multiple second geospatial cells corresponding to a second geospatial index set, and determine one or more indices whose distances are less than or equal to a critical value as a common index.

[0069] For example, the electronic device 100 can determine a common index between a first geospatial index set corresponding to a first route and a second geospatial index set corresponding to a second route, based on a modified longest common subsequence (LCSS) algorithm as follows.

[0070] [Math 3] LCSS(H3Seq1(0,n),H3Seq2(0,m)) =0,if H3Seq1 or H3Seq2 is empty,=0 =1+LCSS(H3Seq1(0,n-1),H3Seq2(0,m-1)),if h3Distance(H3Seq1(0,n-1),H3Seq2(0,m-1))<=threshold =max(LCSS(H3Seq1(0, n-1), H3Seq2(0, m)), LCSS(H3Seq1(0, n), H3Seq2(0, m-1))), otherwise

[0071] Here, H3Seq1 represents the first geospatial index set, and H3Seq2 represents the second geospatial index set. Furthermore, threshold indicates the critical value used to determine whether or not a cell is a common index, and h3Distance indicates the function used to calculate the distance between H3 cells.

[0072] On the other hand, the electronic device 100 can use a modified LCSS algorithm to determine a common index between geospatial cells corresponding to a geospatial index set, but this is only one embodiment, and the electronic device 100 can use a variety of algorithms.

[0073] According to one embodiment, the electronic device 100 can determine a critical value based on at least one of the following: measurement accuracy set by the operator, the order quantity that occurred within a set radius from a first origin or first destination during the most recent set time, the performance of the map engine that provided each of one or more routes, data throughput, and data transmission delay time. For example, the electronic device 100 can determine a smaller critical value if the measurement accuracy is high, the order quantity is low, the map engine performance is high, the data throughput is high, or the data transfer delay time is short.

[0074] In this way, the electronic device 100 can adaptively determine critical values ​​based on various parameters, thereby improving the reliability and accuracy of information regarding the similarity between one or more paths.

[0075] According to one embodiment, the electronic device 100 can determine similarity based on the number of common indices and the number of geospatial cells corresponding to the spatial index sets. More specifically, the electronic device 100 can determine the similarity as a value obtained by dividing twice the number of common indices by the sum of the number of first geospatial cells corresponding to the first geospatial index set and the number of second geospatial cells corresponding to the second geospatial index set.

[0076] For example, the electronic device 100 can determine the similarity between information R1 about the first path and information R2 about the second path based on the following formula.

[0077] [Math 4] similarity(R1,R2)=len(LCSS)*2 / (len(H3Seq1)+len(H3Seq2))

[0078] Here, LCSS can represent a sequence of common indices, and len can represent a function that calculates the size or length of the sequence.

[0079] On the other hand, while the electronic device 100 can determine the similarity as a value between 0 and 1 regardless of the actual road network, this is only one embodiment. The electronic device 100 can determine the similarity based on the distance between two routes or based on the actual road network. More specific examples of how the electronic device 100 determines the similarity between two routes will be described in detail with reference to Figures 5a to 5e.

[0080] In step S260, the electronic device 100 can, in one embodiment, transmit information regarding the similarity between the first route and one or more routes to the worker terminal 120. For example, the worker terminal 120 can receive information from the electronic device 100 in a form that can be displayed on a web page or application screen, and based on the received information, can display information on the display regarding the similarity between the first route and one or more routes traveled by the delivery person.

[0081] In step S270, the electronic device 100 can, in one embodiment, determine the score of each of the one or more map engines that provided one or more routes. More specifically, the electronic device 100 can determine the score of each of the one or more map engines based on at least one of the following: the similarity between the first route actually traveled by the delivery person and the one or more routes, the actual travel time of the delivery person, and the difference in estimated travel time between the one or more routes.

[0082] For example, the electronic device 100 can determine a higher score for each of the one or more map engines if the similarity between the first route actually taken by the delivery person and one or more other routes is high. Alternatively, the electronic device 100 can determine a higher score for each of the one or more map engines if the estimated travel time is faster than the actual travel time of the delivery person.

[0083] Figure 3 is a diagram illustrating the process by which an electronic device 100 provides information regarding the similarity between one or more paths, according to one embodiment. Content that overlaps with Figure 2 will be briefly explained or omitted.

[0084] In step S300, the electronic device 100 can, in one embodiment, receive a recommendation request from the delivery person terminal 140 regarding a route from the first departure point to the first destination. For example, the electronic device 100 can assign an item delivery task from a store located at the first departure point to a delivery person and transmit order information to the delivery person terminal 140. Subsequently, the delivery person terminal 140 can transmit a recommendation request to the electronic device 100 regarding a route that can be traveled from the first departure point to the first destination, based on the delivery person's input.

[0085] In step S310, the electronic device 100 can, in one embodiment, confirm one or more routes from a first origin to a first destination. For example, the electronic device 100 can obtain a location dataset relating to the route from the first origin to the first destination from a map engine that exists as a separate module inside. Alternatively, the electronic device 100 can obtain a location dataset relating to the route from the first origin to the first destination from a map engine of an externally provided map service.

[0086] According to one embodiment, the electronic device 100 can determine a recommended route from among one or more routes based on the scores of one or more map engines that provide one or more routes. For example, the electronic device 100 can check the scores of one or more map engines that have already been determined based on the similarity between the routes previously provided by each of the one or more map engines and the routes previously traveled by delivery personnel. Subsequently, the electronic device 100 can determine the route provided by the map engine with the highest score among the one or more map engines as the recommended route.

[0087] According to one embodiment, the electronic device 100 can determine a recommended route from among one or more routes based on the scores of one or more map engines for one of the following: a time period corresponding to the time the recommendation request was received, an order quantity section, or a traffic congestion section.

[0088] For example, the electronic device 100 can check the first time zone corresponding to the time the recommendation request was received and check the scores of one or more map engines that have already been determined for the first time zone. Then, the electronic device 100 can determine the route provided by the map engine with the highest score for the first time zone from among the one or more map engines as the recommended route.

[0089] As another example, the electronic device 100 can check the order quantity generated within a set radius from the first origin or first destination within a set time after receiving a recommendation request, and check the first order quantity interval corresponding to the order quantity. Subsequently, the electronic device 100 can determine as the recommended route the route provided by the map engine with the highest score for the first order quantity interval among one or more map engines.

[0090] As yet another example, when the electronic device 100 receives a recommendation request, it can check the level of traffic congestion within a set radius from the first departure point or first destination, and identify the first traffic congestion section corresponding to that level of traffic congestion. Subsequently, the electronic device 100 can determine the route provided by the map engine with the highest score for the first traffic congestion section from among one or more map engines as the recommended route.

[0091] In this way, the electronic device 100 can provide a recommended route based on a similarity determined by the time of day the recommendation request was received, the order quantity interval, or the traffic congestion interval, thereby providing the delivery person with the most optimal route.

[0092] In step S320, the electronic device 100 can, in one embodiment, transmit information about one or more routes to the delivery person terminal 140. For example, the electronic device 100 can transmit to the delivery person terminal 140 at least one of the following: information about one or more routes from a first departure point to a first destination, information about the estimated travel time for each of the one or more routes, and information about a recommended route among the one or more routes.

[0093] In step S330, the electronic device 140 can, in one embodiment, provide the delivery person with one or more routes from the first departure point to the first destination. For example, the delivery person terminal 140 can receive information from the electronic device 100 in a form that can be displayed on a web page or application screen, and based on the received information, can display on its display information about one or more routes from the store (the departure point) to the delivery destination, as well as information about a recommended route among the one or more routes.

[0094] In step S340, the electronic device 100 can receive information from the delivery person terminal 140 regarding the first route actually traveled by the delivery person. For example, the delivery person terminal 140 can transmit time data and location data sets generated by the delivery person's movement along the first route to the electronic device 100.

[0095] In step S350, the electronic device 100 can, in one embodiment, determine the similarity between the first route and one or more routes with respect to at least one of the time period, order quantity section, or traffic congestion section corresponding to the time the recommendation request was received. More specifically, the electronic device 100 can check at least one of the time period, order quantity section, or traffic congestion section corresponding to the time the recommendation request was received, and determine the similarity between the first route and one or more routes with respect to at least one of the checked time period, order quantity section, or traffic congestion section.

[0096] For example, the electronic device 100 can determine the first time zone corresponding to the time the first recommendation request was received, and determine the similarity between the first route and one or more routes with respect to the first time zone.

[0097] As yet another example, the electronic device 100 can, within a set time after receiving a recommendation request, check the order quantities generated within a set radius from the first origin or first destination, and identify the first order quantity interval corresponding to the order quantities. Subsequently, the electronic device 100 can determine the similarity between the first route and one or more routes with respect to the first order quantity interval.

[0098] As yet another example, when the electronic device 100 receives a recommendation request, it can check the level of traffic congestion within a set radius from the first departure point or first destination, and identify the first traffic congestion section corresponding to that level of traffic congestion. Subsequently, the electronic device 100 can determine the similarity between the first route and one or more routes with respect to the first traffic congestion section.

[0099] In step S360, the electronic device 100 can, in one embodiment, determine the score of each of the one or more map engines that provided one or more routes. For example, the electronic device 100 can determine the score of each of the one or more map engines based on at least one of the following: the similarity between the first route actually traveled by the delivery person and one or more of the routes, the actual travel time of the delivery person, and the difference in estimated travel time between the one or more routes.

[0100] Figure 4 is a diagram illustrating the process by which the electronic device 100 provides information regarding the similarity between one or more paths, according to one embodiment. Content that overlaps with Figure 2 will be briefly explained or omitted.

[0101] In step S440, the electronic device 100 can, in one embodiment, receive information about the route taken by each of one or more delivery personnel from the first departure point to the first destination. For example, the electronic device 100 can receive information about the first route actually taken by the first delivery person from the first delivery person terminal 400, information about the second route actually taken by the second delivery person from the second delivery person terminal 410, and information about the third route actually taken by the third delivery person from the third delivery person terminal 420.

[0102] In step S450, the electronic device 100 can, in one embodiment, determine the similarity between one or more routes from a first departure point to a first destination. For example, the electronic device 100 can determine the similarity between the first, second, and third routes traveled by the first, second, and third delivery personnel, respectively.

[0103] In step S460, the electronic device 100 can, in one embodiment, receive a recommendation request from the fourth delivery person terminal 140 regarding a route from the first departure point to the first destination. For example, the electronic device 100 can assign the delivery of items from a store located at the first departure point to the fourth delivery person and transmit order information to the fourth delivery person terminal 430. Subsequently, the fourth delivery person terminal 430 can transmit a recommendation request to the electronic device 100 regarding a route that can be traveled from the first departure point to the first destination, based on the input from the fourth delivery person.

[0104] In step S470, the electronic device 100 can, in one embodiment, determine a recommended route based on the similarity between one or more routes. For example, the electronic device 100 can determine the recommended route to be the route that has the highest similarity to the other routes among the first, second, and third routes traveled by the first, second, and third delivery personnel, respectively, who have the same origin and destination as the route for which a recommendation was requested.

[0105] In step S480, the electronic device 100 can, in one embodiment, transmit information regarding a recommended route from the first departure point to the first destination. For example, the electronic device 100 can transmit information regarding one or more routes taken by other delivery personnel from the first departure point to the first destination, and information regarding a recommended route among those one or more routes.

[0106] In step S490, the fourth delivery terminal 430 can, in one embodiment, provide the fourth delivery person with a recommended route. For example, the fourth delivery terminal 430 can receive information from the electronic device 100 in a form that can be displayed on a web page or application screen, and based on the received information, can display on its display information about one or more routes from the store (origin) to the delivery destination (destination) and information about a recommended route among the one or more routes.

[0107] In this way, the electronic device 100 can recommend the route that has the highest similarity to other routes among the routes actually traveled by the delivery person, thereby recommending an optimized route based on the delivery person's experience.

[0108] Figures 5a to 5e illustrate the process by which the electronic device 100 determines the similarity between one or more paths, according to one embodiment. Content that overlaps with Figure 2 will be briefly explained or omitted.

[0109] According to one embodiment, the electronic device 100 can check a first position data set for a first route from a departure point to a destination and a second position data set for a second route. For example, referring to Figure 5a, the electronic device 100 can check a GPS value set for a first route 520 from a first departure point 500 to a first destination 510. Alternatively, referring to Figure 5b, the electronic device 100 can check a GPS value set for a second route 530 from a first departure point 500 to a first destination 510.

[0110] According to one embodiment, the electronic device 100 can identify a first geospatial index set corresponding to a first location dataset and a second geospatial index set corresponding to a second location dataset. More specifically, the electronic device 100 can identify geospatial cells covering the coordinates of the location data in the first and second location datasets, and identify the first and second geospatial index sets based on the index corresponding to the geospatial cells.

[0111] For example, referring to Figure 5c, the electronic device 100 can identify multiple first geospatial cells 540 covering each coordinate in the GPS value set for the first route 520, and identify the first geospatial index set corresponding to the multiple first geospatial cells 540. Alternatively, referring to Figure 5d, the electronic device 100 can identify multiple second geospatial cells 550 covering each coordinate in the GPS value set for the second route 530, and identify the second geospatial index set corresponding to the multiple second geospatial cells 550.

[0112] According to one embodiment, the electronic device 100 can determine a common index based on a critical value relating to the distance between geospatial cells. More specifically, the electronic device 100 can check the distance between each of the multiple first geospatial cells 540 and second geospatial cells 550 and determine one or more indices whose distance is less than or equal to a critical value as a common index.

[0113] For example, referring to Figure 5e, the electronic device 100 can determine, based on the LCSS algorithm, one or more indices from the first geospatial index set and the second geospatial index set whose distance is less than or equal to a critical value as a common index. That is, the electronic device 100 can identify a common geospatial cell 560 between a plurality of first geospatial cells 540 and a plurality of second geospatial cells 550.

[0114] According to one embodiment, the electronic device 100 can determine similarity based on the number of common indices and the number of geospatial cells corresponding to the spatial index sets. More specifically, the electronic device 100 can determine the similarity as a value obtained by dividing twice the number of common indices by the sum of the number of first geospatial cells corresponding to the first geospatial index set and the number of second geospatial cells corresponding to the second geospatial index set.

[0115] For example, the electronic device 100 can determine the similarity between the first route 520 and the second route 530 as 0.17857, which is obtained by dividing twice the number of common indices, 10, by the sum of the number of first geospatial cells 540, 67, and the number of second geospatial cells 550, 45, as shown in the following formula.

[0116] [Number 5] similarity(R1,R2)=10*2 / (67+45)=0.17857

[0117] Figure 6 shows a flowchart of an information provision method for an electronic device according to one embodiment. The previously mentioned descriptions may apply to any overlapping content.

[0118] In step S600, the electronic device can acquire a first location dataset relating to the first route from the first departure point to the first destination, and a second location dataset relating to the second route from the first departure point to the first destination.

[0119] According to one embodiment, the electronic device can acquire a location dataset relating to a route generated by the actual movement of a delivery person. Alternatively, the electronic device can acquire a location dataset relating to a route from a map engine that exists as a separate module internally or from a map engine of an externally provided map service.

[0120] At step S620, the electronic device can verify the first geospatial index set corresponding to the first location dataset and the second geospatial index set corresponding to the second location dataset.

[0121] According to one embodiment, when the electronic device checks the first geospatial index set and the second geospatial index set, it can check the geospatial cells that cover the coordinates of the respective location data in the first location dataset and the second location dataset, and then check the first geospatial index set and the second geospatial index set based on the index corresponding to the geospatial cell.

[0122] According to one embodiment, the size of a geospatial cell can be determined by the measurement accuracy set by the operator.

[0123] In step S640, the electronic device can determine the number of common indices between the first geospatial index set and the second geospatial index set based on the set algorithm.

[0124] According to one embodiment, when the electronic device checks the number of common indices between a first geospatial index set and a second geospatial index set, it can check the distances between each of the multiple first geospatial cells corresponding to the first geospatial index set and the multiple second geospatial cells corresponding to the second geospatial index set, and determine one or more indices whose distances are less than or equal to a critical value as common indices.

[0125] According to one embodiment, the critical value may be determined based on at least one of the following: measurement accuracy set by the operator, order quantity generated within a set radius from a first origin or first destination during the most recently set time, performance of the map engine that provided each of one or more routes, data throughput, and data transmission delay time.

[0126] According to one embodiment, the critical value can be determined to be smaller as the measurement accuracy increases, the order quantity decreases, the map engine performance increases, the data throughput increases, or the data transfer delay time decreases.

[0127] In step S660, the electronic device can determine the similarity between the first and second paths based on the number of common indices.

[0128] According to one embodiment, the similarity between the first and second routes can be determined by dividing twice the number of common indices by the sum of the number of first geospatial cells corresponding to the first geospatial index set and the number of second geospatial cells corresponding to the second geospatial index set.

[0129] According to one embodiment, the first route includes the route actually traveled by the first delivery person, and the second route includes the route provided by the first map engine. The electronic device can determine a score for the first map engine based on the similarity between the first and second routes. In this case, the score for the first map engine can be determined to be higher the higher the similarity between the first and second routes.

[0130] According to one embodiment, the electronic device confirms the actual travel time of the first delivery person via the first route and the estimated travel time via the second route, and the score of the first map engine may be determined by further considering the difference between the actual travel time and the estimated travel time. In this case, the score of the first map engine may be determined to be higher the faster the estimated travel time is compared to the actual travel time.

[0131] According to one embodiment, the electronic device can receive a first recommendation request regarding a route from a first origin to a first destination from the terminal of a first delivery person, and can confirm a first time zone corresponding to the time the first recommendation request was received. At this time, the similarity between the first route and the second route can be determined by the similarity with respect to the first time zone.

[0132] According to one embodiment, the electronic device receives a first recommendation request regarding a route from a first origin to a first destination from the terminal of a first delivery person, and within a set time after receiving the first recommendation request, it can confirm the order quantity generated within a set radius from the first origin or first destination and confirm the first order quantity interval corresponding to the order quantity. At this time, the similarity between the first route and the second route may be determined by the similarity with respect to the first order quantity interval.

[0133] According to one embodiment, the electronic device receives a first recommendation request regarding a route from a first origin to a first destination from the terminal of a first delivery person. Upon receiving the first recommendation request, the device can check the degree of traffic congestion within a radius set from the first origin or first destination and identify a first traffic congestion section corresponding to the degree of traffic congestion. At this time, the similarity between the first route and the second route may be determined by the similarity with respect to the first traffic congestion section.

[0134] According to one embodiment, the electronic device can receive a second recommendation request regarding a route from a second origin to a second destination from the terminal of a second delivery person, and can obtain information on one or more routes from the second origin to the second destination provided by one or more map engines. The electronic device can also check the scores of one or more map engines, which have already been determined, based on the similarity between routes previously provided by one or more map engines and routes previously traveled by the second delivery person, and can transmit information on the route provided by the map engine with the highest score among the one or more map engines to the terminal of the second delivery person.

[0135] According to one embodiment, the electronic device can acquire information about one or more routes taken by one or more delivery personnel traveling from a third origin to a third destination, determine the similarity between one or more routes, and select the route with the highest similarity to the other routes as the recommended route from the third origin to the third destination.

[0136] Figure 7 shows a block diagram of an electronic device 100 according to one embodiment.

[0137] In one embodiment, the electronic device 100 may include a transceiver 720, a memory 740, and a processor 760. The electronic device 100 shown in Figure 7 only shows components relevant to this embodiment. Therefore, a person with ordinary skill in the art related to this embodiment will understand that other general-purpose components may be included in addition to those shown in Figure 7. In an embodiment, the transceiver 720 may be included in a communication device. Also, in an embodiment, the processor 760 may be included in a controller.

[0138] The Transceiver 720 is a device for wired / wireless communication and can communicate with external electronic devices. These external electronic devices can be terminals or servers. The communication technologies used by the Transceiver 720 may include GSM (Global System for Mobile communication), CDMA (Code Division Multi Access), LTE (Long Term Evolution), 5G, WLAN (Wireless LAN), Wi-Fi (Wireless-Fidelity), Bluetooth, RFID (Radio Frequency Identification), Infrared Data Association (IrDA), ZigBee, and NFC (Near Field Communication).

[0139] The processor 760 can control the overall operation of the electronic device 100 and process data and signals. The processor 760 may consist of at least one hardware unit. The processor 760 can also operate through one or more software modules generated by executing program code stored in memory 740. Because the processor 760 can include memory, it can execute program code stored in memory to control the overall operation of the electronic device 100 and process data and signals.

[0140] The processor 760 obtains a first location dataset for the first route from the first origin to the first destination and a second location dataset for the second route from the first origin to the first destination, checks the first geospatial index set corresponding to the first location dataset and the second geospatial index set corresponding to the second location dataset, checks the number of common indices between the first and second geospatial index sets based on the configured algorithm, and can determine the similarity between the first and second routes based on the number of common indices.

[0141] The electronic device according to the above embodiment may include a processor, memory for storing and executing program data, permanent storage such as a disk drive, a communication port for communicating with external devices, and user interface devices such as a touch panel, keys, and buttons. A method embodied in a software module or algorithm may be stored on a computer-readable recording medium as computer-readable code or program instructions executable on the processor. Here, computer-readable recording media include magnetic recording media (e.g., ROM (read-only memory), RAM (random-access memory), floppy disks, hard disks, etc.) and optical reading media (e.g., CD-ROM, DVD (Digital Versatile Disc)). Computer-readable recording media may be distributed across a network of computer systems, and computer-readable code may be stored and executed in a distributed manner. The medium may be computer-readable, stored in memory, and executed by the processor.

[0142] This embodiment can be represented by functional block configurations and diverse processing stages. Such functional blocks can be embodied by a variety of hardware and / or software configurations that perform specific functions. For example, the embodiment may employ direct circuit configurations such as memory, processing, logic, and look-up tables, which can perform diverse functions under the control of one or more microprocessors or other control devices. Just as the components can be executed as software programming or software elements, this embodiment includes a variety of algorithms embodied by combinations of data structures, processes, routines, or other programming configurations, and can be embodied in programming or scripting languages ​​such as C, C++, Java, and assembler. Functional aspects can be embodied by algorithms executed by one or more processors. Furthermore, this embodiment may employ prior art for electronic environment configuration, signal processing, and / or data processing. Terms such as “mechanism,” “element,” “means,” and “configuration” can be used broadly and are not limited to mechanical and physical configurations. The terms may also include the meaning of a series of software processes (routines) in conjunction with a processor, etc.

[0143] The embodiments described above are merely examples, and other embodiments may be embodied within the scope of the claims described later.

Claims

1. A method for providing information about electronic devices, A step of obtaining a first location dataset relating to a first route from a first departure point to a first destination and a second location dataset relating to a second route from the first departure point to the first destination, The steps include verifying the first geospatial index set corresponding to the first location dataset and the second geospatial index set corresponding to the second location dataset, A step of determining the number of common indices between the first geospatial index set and the second geospatial index set based on the set algorithm, An information provision method comprising the step of determining the similarity between the first path and the second path based on the number of common indices.

2. The step of verifying the first geospatial index set and the second geospatial index set is: The steps include: confirming the geospatial cells (cells) that cover the coordinates of the location data in the first location dataset and the second location dataset, The information provision method according to claim 1, comprising the step of confirming the first geospatial index set and the second geospatial index set based on the index corresponding to the geospatial cell.

3. The information provision method according to claim 2, wherein the size of the geospatial cell is determined by a measurement accuracy set by the operator.

4. The step of determining the number of common indices between the first geospatial index set and the second geospatial index set is: A step of confirming the distance between each of the multiple first geospatial cells corresponding to the first geospatial index set and the multiple second geospatial cells corresponding to the second geospatial index set, The information provision method according to claim 1, comprising the step of determining one or more indices whose distance is less than or equal to a critical value as a common index.

5. The aforementioned critical value is, The measurement accuracy set by the operator, The quantity of orders placed within a radius set from the first departure point or the first destination during the most recently set time period, The performance of the map engine that provided the first or second route, Data throughput and, The information provision method according to claim 4, determined based on at least one of the data transmission delay time and the following.

6. The aforementioned critical value is, The information provision method according to claim 5, wherein the measurement accuracy is higher, the order quantity is smaller, the map engine performance is higher, the data throughput is higher, or the data transfer delay time is shorter, the smaller the size determined.

7. The similarity between the first and second paths is, The information provision method according to claim 1, wherein the value is determined by dividing twice the number of common indexes by the sum of the number of first geospatial cells corresponding to the first geospatial index set and the number of second geospatial cells corresponding to the second geospatial index set.

8. The first route includes the route actually traveled by the first delivery person, The second route includes the route provided by the first map engine, The information provision method according to claim 1, further comprising the step of determining a score for the first map engine based on the similarity between the first route and the second route.

9. The score of the first map engine is, The information provision method according to claim 8, wherein the higher the similarity between the first route and the second route, the higher the determination.

10. The aforementioned method of providing information is: The process further includes confirming the actual travel time of the first delivery person via the first route and the estimated travel time via the second route. The information provision method according to claim 8, wherein the score of the first map engine is determined by further considering the difference between the actual travel time and the predicted travel time.

11. The score of the first map engine is, The information provision method according to claim 10, wherein the expected travel time is determined to be higher the faster the actual travel time is.

12. The aforementioned method of providing information is: The process includes receiving a first recommendation request regarding the route from the first departure point to the first destination from the terminal of the first delivery person, The process further includes the step of confirming a first time zone corresponding to the time the first recommendation request was received, The information provision method according to claim 1, wherein the similarity between the first route and the second route is determined by the similarity with respect to the first time period.

13. The aforementioned method of providing information is: The process includes receiving a first recommendation request regarding the route from the first departure point to the first destination from the terminal of the first delivery person, A step of confirming the order quantity that occurred within a set time after receiving the first recommendation request, within a set radius from the first origin or first destination, The process further includes the step of confirming a first order quantity interval corresponding to the aforementioned order quantity, The information provision method according to claim 1, wherein the similarity between the first route and the second route is determined by the similarity with respect to the first order quantity interval.

14. The aforementioned method of providing information is: The process includes receiving a first recommendation request regarding the route from the first departure point to the first destination from the terminal of the first delivery person, Upon receiving the first recommendation request, the steps include: confirming the degree of traffic congestion within a radius set from the first departure point or the first destination; The process further includes the step of confirming a first traffic congestion section corresponding to the aforementioned traffic congestion level, The information provision method according to claim 1, wherein the similarity between the first route and the second route is determined by the similarity with respect to the first traffic congestion section.

15. The aforementioned method of providing information is: The stage in which a second recommendation request regarding the route from the second departure point to the second destination is received from the second delivery person's terminal, A step of obtaining information about one or more routes from the second departure point to the second destination, provided by one or more map engines, A step of confirming the score of each of the one or more map engines, which has already been determined based on the similarity between the routes previously provided by the one or more map engines and the routes previously traveled by the second delivery person, The information provision method according to claim 1, further comprising the step of transmitting information regarding the route provided by the map engine having the highest score among the one or more map engines to the terminal of the second delivery person.

16. The aforementioned method of providing information is: The step of obtaining information about one or more routes taken by one or more delivery personnel from a third origin to a third destination, The step of determining the similarity between one or more paths, The information provision method according to claim 1, further comprising the step of determining, among the one or more routes, the route having the highest similarity to the other routes as the recommended route from the third departure point to the third destination.

17. A computer-readable non-temporary recording medium that stores a program for causing a computer to execute the method according to claim 1.

18. An electronic device, Transceiver and, Memory and A processor is included, and the processor is A first location dataset relating to the first route from the first departure point to the first destination and a second location dataset relating to the second route from the first departure point to the first destination are obtained. The first geospatial index set corresponding to the first location dataset and the second geospatial index set corresponding to the second location dataset are checked. Based on the established algorithm, the number of common indices between the first geospatial index set and the second geospatial index set is determined. An electronic device that determines the similarity between the first and second paths based on the number of common indices.

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