WO2022019953A1

WO2022019953A1 - Human-friendly geocodes

Info

Publication number: WO2022019953A1
Application number: PCT/US2020/070196
Authority: WO
Inventors: Sekhar Chandra
Original assignee: Sekhar Chandra
Priority date: 2020-07-22
Filing date: 2020-07-22
Publication date: 2022-01-27

Abstract

A computer implemented method is presented for generating human-friendly location identifiers for precisely identifying and communicating any place on the Earth. The method converts geographical coordinates such as (latitude, longitude) to intuitively hierarchical geocodes and elegantly assembles them in a form resembling a real-world address. Not only do these location identifiers look like, act like real-world addresses, but they also behave like them thanks to their localizability, interoperability and navigability.

Description

Title of Invention: HUMAN-FRIENDLY GEOCODES

Technical Field

[0001] This invention, generally, relates to a method and apparatus for identifying and com municating locations, and in particular to a method and apparatus for identifying and communicating locations using precise location identifiers that look like, act like and behave like real-world addresses.

Background Art

[0002] In recent years, geocode schemes have come into general use to precisely identify and communicate locations. These schemes typically make use of a reference grid system, such as a latitude-longitude grid, to produce geocode-based location identifiers.

[0003] A few examples of existing geocode schemes include Geohash, Global Area Reference System (GARS), GEOREF, Maidenhead Locator System, Mapcode, Military Grid Reference System (MGRS), Natural Area Codes, Open Location Codes (or Plus Codes), Open Postcode, US National Grid (USNG), Universal Transverse Mercator (UTM), What3words, and Xaddress, etc. A comprehensive list of various geocode schemes in existence today may be found at https://en.wikipedia.org/wiki/Discrete_global_grid (last accessed on June 21, 2020).

[0004] While existing geocode schemes excel at identifying locations with high precision, they all inherently suffer from significant problems. For instance, the existing schemes often produce location identifiers resembling a random string of numbers, characters and/or unrelated words making the geocodes harder to remember and communicate. The existing geocode schemes are also challenging to navigate given a nearby location identifier because often the encoded directionality and distances are obscured and in comprehensible to humans without detailed knowledge of their complex inner- workings. Finally, the existing geocode identifiers do not often contain any references to localities/towns/cities further disconnecting them from humans.

[0005] Due to their inherent problems, the existing geocode schemes typically are not intuitive for humans. As a result, they are difficult to comprehend, adopt and use. The present invention aims to solve these problems.

Summary of Invention

[0006] Various aspects of the invention provide methods and apparatus for generating human-friendly location identifiers for precisely identifying and communicating worldwide locations. Despite being geocode -based, the location identifiers of the present invention are intuitive in that they look like, act like and behave like real-world addresses. The location identifiers, referred to as SmartAddresses hereafter, are offline- friendly and do not need database lookups. And, SmartAddresses not only pinpoint locations globally, but also tell the time-zone differences between them.

[0007] The first aspect of the invention is directed to computer implemented methods of converting a location’s information in the form of geographical coordinates, such as latitude and longitude, to a SmartAddress and vice versa. For example, according to the present invention, the SmartAddress of the Eiffel Tower is “@3608 BEAU CHATEAU 66, 75007 PARIS” which not only resembles a real-world address in France but also pinpoints the Eiffel Tower to the last 10 meters. In addition, details are presented demonstrating the localizability, interoperability and navigability of the SmartAddresses to make them human-friendly.

[0008] In second aspect, the invention also provides techniques for converting existing location identifiers, such as Open Location Code and USNG/MGRS, to a Smar tAddress form to aid their memorability and recall.

[0009] Lastly, a computer system to carry out the present invention is disclosed.

Advantageous Effects of Invention

[0010] SmartAddresses have unique advantages over existing geocode schemes. Despite being geocode-based, SmartAddresses look like, act like and behave like real-world addresses but at global scale. Because of their global applicability, SmartAddresses are capable of instantly giving unified urban-style street addresses all locations on the Earth.

[0011] Unlike existing geocodes, SmartAddresses are localizable, interoperable and navigable at global scale. In addition, SmartAddresses contain locality/town/city in formation to appeal to the locals. And, they not only encode space but also time in that SmartAddresses can even tell the time-zone difference between any two locations on the globe.

[0012] SmartAddresses are also more precise than real-world addresses anywhere on the Earth because they are geocoded. More importantly, SmartAddresses work even in disputed areas and in areas without streets, towns, or developments. And, in areas where real-world addresses do already exist, SmartAddresses provide the unique advantage of backward compatibility because, unlike real-world addresses, Smar tAddresses will continue to work even if the street/town/city name changes in the future.

[0013] All in all, the present invention advantageously combines the precision of geocode location identifiers and the simplicity of urban-style street addresses in the form of SmartAddresses.

Brief Description of Drawings [0014] The invention will now be described in detail with reference to the following figures in which:

Fig-1

[0015] [fig-1] illustrates a 2-level hierarchical grid on the surface of the Earth.

Fig.2

[0016] [fig-2] illustrates an overview of the location encoding & decoding of Smar- tAddresses.

Fig.3

[0017] [fig-3] illustrates a detailed flowchart of location encoding to produce a Smar- tAddress.

Fig.4

[0018] [fig-4] illustrates overlays of the first- and second-level geocodes.

Fig.5

[0019] [fig-5] illustrates overlays of the third- and forth-level geocodes.

Fig.6

[0020] [fig-6] illustrates an overlay of the fifth-level geocodes.

Fig.7

[0021] [fig-7] illustrates a US-style SmartAddress of the Eiffel Tower.

Fig.8

[0022] [fig-8] illustrates a language-localized SmartAddress of the Eiffel Tower.

Fig.9

[0023] [fig-9] illustrates a fully-localized SmartAddress of the Eiffel Tower.

Fig.10

[0024] [fig.10] illustrates a distance estimation example with SmartAddresses.

Fig.ll

[0025] [fig.l 1] illustrates a time-zone difference estimation example.

Fig.12

[0026] [fig.12] illustrates a flowchart of decoding a SmartAddress.

Fig.13

[0027] [fig.13] illustrates a schematic of encoding and decoding Open Location Code identifiers.

Fig.14

[0028] [fig.14] illustrates a US-style OLC SmartAddress of the Eiffel Tower.

Fig.15

[0029] [fig.15] illustrates a schematic of encoding and decoding USNG identifiers.

Fig.16 [0030] [fig.16] illustrates a detailed flowchart of encoding a USNG identifier.

Fig-17

[0031] [fig.17] illustrates a USNG SmartAddress of the Eiffel Tower.

Fig.18

[0032] [fig.18] illustrates a detailed flowchart of decoding a USNG SmartAddress.

Fig.19

[0033] [fig.19] illustrates a computer system to carry out the present invention.

Fig.20

[0034] [fig.20] illustrates a computer program to generate SmartAddresses.

Fig.21

[0035] [fig.21] illustrates a computer program to decode SmartAddresses.

Fig.22

[0036] [fig.22] illustrates a computer program to encode Open Location Codes.

Fig.23

[0037] [fig.23] illustrates a computer program to decode OLC SmartAddresses.

Fig.24

[0038] [fig.24] illustrates a computer program to encode USNG identifiers.

Fig.25

[0039] [fig.25] illustrates a computer program to decode USNG SmartAddresses.

Description of Embodiments

[0040] Although the following detailed description contains many specifics for the purposes of illustration, anyone of ordinary skill in the art will appreciate that many variations and alterations to the following details are within the scope of the invention. Ac cordingly, the following embodiments of the invention are set forth without any loss of generality to, and without imposing limitations upon, the claimed invention.

[0041] The present invention is illustrated using a discrete global grid on the surface of the Earth containing five hierarchical grid levels. A coordinate system based on latitude- longitude is considered without losing generality to the applicability of the current invention to other coordinate systems.

[0042] For simplicity, an example of a 2-level hierarchical grid is illustrated in Figure 1 along with the first- and second-level grid cells, Cl and C2 and their reference co ordinate systems, X _/ -Y _/ SL X ₂ -Y · Cell Cl (or any point inside it) is identified globally by its hierarchical cell coordinates (X _/ , Y _/ ) = (1, 3). And, cell C2 (or any point inside it) is identified globally by its hierarchical cell coordinates, (X _/ , Y ) = (2, 1) and (X₂ , Y₂ ) = (1, 3) and locally by (X ₂ , Y₂ ) = (1, 3).

[0043] Table 1 lists the grid discretization parameters, (P _N , Q _N ), corresponding to a five- level hierarchical latitude-longitude grid. Here, the grid contains 5 hierarchical cells: Cl, C2, C3, C4, and C5 with sizes ranging from 0(100 km) to 0(10 m). [0044] [Table 1]

Table 1. Hierarchical discretization parameters of the Earth’s latitude-longitude grid. [0045] The cell sizes change with latitude due to the graticule-based grid discretization.

Table 2 shows the dimensions of the cells C1-C5 in X (East) and Y (North) directions as a function of their mean latitude (2).

[0046] [Table 2]

Table 2. Cell dimensions as a function of their mean latitude, 2.

[0047] The Y-dimension (L ₁- ) of the fifth-level cell, C5, 10 m, defines the precision of the corresponding geocode location identifiers. This is comparable to the typical accuracy of GPS-enabled smartphones around the world and may be considered sufficient for the purpose of identifying locations on Earth. However, when/where it’s not sufficient, one might supplement the location identifiers with auxiliary information such as unit/ apartment/suit number or similar information to help disambiguate multiple locations of interest inside a last-level cell. The other alternative is to simply adjust the grid resolution by fine-tuning the hierarchical discretization parameters (P _N , Q _N ). [0048] At 10-meter resolution, there are about 7.4 trillion last-level cells covering the entire surface of the Earth. Each last-level cell C5 is identified globally by its hierarchical co ordinates (X 1 , Y 1 ), (X 2 , Y 2 ), (X 3 , Y 3 ), (X 4 , Y 4 ), and (X₅ , Y₅ ). The cell co ordinates are then encoded to generate a global location identifier, referred to as Smar- tAddress, resembling a real-world address. The encoding is easily reversible.

Therefore, when required, a SmartAddress can be easily decoded to generate the cell’s latitude and longitude coordinates.

[0049] A schematic 200 of the location encoding and decoding operations is illustrated in Figure 2. The encoding operations, involving steps 202 and 204, convert (latitude, longitude) coordinates 201 to an intermediate set of hierarchical coordinates 203, and finally to a SmartAddress 205. The decoding operations, involving steps 206 and 208, convert a SmartAddress 205 back to latitude & longitude coordinates 201. The encoding operations are described in detail next.

[0050] Figure 3 illustrates a detailed flowchart 300 of the encoding operations consisting of modules 302, 304 and 306. Module 302 shifts the origin to the 180° longitude and south pole. Module 304 computes the hierarchical cell coordinates 203. Finally, module 306 encodes the coordinates as hierarchical geocodes and then assembles them to generate a SmartAddress. This is illustrated next with an example of the Eiffel Tower located at (latitude, longitude) of (48.858436°, 2.294607°).

[0051] Table 3 lists the hierarchical cell coordinates and the corresponding geocodes of the Eiffel tower according to the present invention. The hierarchical geocodes (G1-G5) correspond to the cells C1-C5, respectively. Note that G3L is a language-localized geocode (described later). Also, note that the symbols ‘@’ and ‘+’ (in geocodes G1 and G4) do not encode any information. The symbols are added to help computers and humans to recognize SmartAddresses.

[0052] [Table 3]

Table 3. Hierarchical coordinates and the computed geocodes of the Eiffel Tower. [0053] In addition to the geocodes G1-G5, a SmartAddress also makes use of additional location information such as its locality name and zip/postal code in a process called “full-localization” (described later). Table 4 shows the supplemental geocodes G10 and G14 corresponding to the Eiffel Tower’s real-world address components.

[0054] [Table 4]

Table 4. Supplemental geocodes of the Eiffel Tower.

[0055] The geocodes G1-G5 are constructed according to the formulas listed in Table 5. [0056] [Table 5]

Table 5. Hierarchical geocodes & their evaluation for the Eiffel Tower. Note: concat method simply concatenates the parameters passed.

[0057] The geocode formulas encode coordinates of cells C1-C5 to produce human- friendly, geocode identifiers: G1-G5 and G3L. For illustration, the formulas are evaluated for the Eiffel Tower in column 2 of Table 5. Note that the evaluation of geocodes G2, G4 and G5 is fairly simple whereas G1 and G3 involve evaluation of the geocodelets, g _]x , g _{/ v} , g _{3 x} , and g _{3 v} as described next.

[0058] Geocode G1 consists of two geocodelets: g _]x and g , , . Geocodelet, _{/x ,} is evaluated as shown in Table 6. g _]x takes on an integer value in 1-48 and serves as a global longitude-band identifier and it can also be used to estimate the time-zone difference between locations as described later. Geocodelets, g _]x <= 24 correspond to the Western Hemisphere whereas g _]x >= 25 correspond to the Eastern Hemisphere. [0059] [Table 6]

Table 6. Gcocodclct, g _]x , values.

[0060] Geocodelet, g _{/ y} , is the second component of the G1 geocode and is evaluated as shown in Table 7. g i _y takes on a character value in A-Z and serves as a global latitude-band identifier g _{/ v} values in N-Z correspond to the Northern Hemisphere whereas the values in A-M correspond to the Southern Hemisphere.

[0061] [Table 7]

Table 7. Gcocodclct, g _/v , values.

[0062] Geocode G3 is produced by concatenating the geocodelets, g _{3 x} and g _{t ,} . Each geocodelet is computed using a custom base-20 encoding. For the US-style Smar- tAddresses, the digits 0-19 of each base-20 encoding are represented by a list of English words starting with A-T in alphabetical order. Note that all 20 letters in A-T are used to represent the base-20 digits. Other target language words can also be used for language-localization as described later. Tables 8 and 9 list the geocodelets, g _{3 x} and g 3 _y , respectively used for US-style SmartAddresses.

[0063] [Table 8]

Table 8. Geocodelet, g _3x values for US-style geocode, G3. [0064] [Table 9]

Table 9. Geocodelet, g _3y values for US-style geocode, G3.

[0065] As shown in Tables 8 and 9, two lists of curated words are chosen for the base-20 encodings to ensure that the concatenation of g _{3 x} and g _{3 v} produces a pair of words re sembling a somewhat meaningful landmark, street or area name. For instance, with the chosen sets of English words, G3 can take on 400 different values, such as AUTUMN ARCADE, AUTUMN BAY, BLUE ARCADE, and BLUE BAY, etc., to produce SmartAddresses resembling US-style street addresses.

[0066] It is worth noting that the geocodes, G1-G5 are simple, intuitive and predictable for all the cells thanks to the elegantly crafted geocode formulas. This is evident in Figures 4, 5 and 6 which illustrate the hierarchical cells C1-C5 overlaid by their geocodes G1-G5. These geocodes are uniquely assembled to generate SmartAddresses that look like, act like and behave like real-world addresses. The novel assembly of the hier archical geocodes G1-G5 form the backbone of the present invention and give Smar tAddresses unique advantages such as localizability, navigability and interoperability as described next.

[0067] Figure 7 illustrates an assembled US-style SmartAddress 700 for the Eiffel Tower. A SmartAddress consists of two lines: 701 and 702 resembling an urban-style street address in the US. The first line 701 is composed of geocodes G4, G3 and G5, in that order. And, the second line 702 is composed of geocodes G10 and G12. It should be noted that G10 is an optional component in 700 corresponding to the locality /town/city name. If no locality information is available, the state or country name can be used for G10. In disputed territories, G10 can be completely ignored since it is optional. And, G12 is a concatenation of G1 and G2 and is referred to as the -i-code hereafter.

[0068] The geocode G3 offers room for flexibility in a SmartAddress. As previously shown in Tables 8 and 9, G3 is a pair of words corresponding to the base-20 encodings of the cell coordinates. It is reiterated that only the first letters of the pair of words actually encode the coordinates and not the whole words per se. For example, BLUE CASTLE, BIG CONSTRUCTION, or another word pair, with letters B & C in that order, are all equivalent G3 geocodes for the Eiffel Tower. In other words, one could just substitute the default G3 geocodes with an equivalent pair of words that best describes the encoded location, landmark or region to make SmartAddresses (700) even more relevant.

[0069] Taking the flexible G3 geocodes a step further, one could even language localize them to other Latin-script based target languages, such as French, Spanish, Italian, German, etc. For example, the English-based word pair in G3 can be replaced with an equivalent word pair starting with the same first letters in a target language for language localization. Next follows, an example of the localization for the Eiffel Tower to French language.

[0070] Figure 8 shows a language-localized SmartAddress 800 for the Eiffel Tower in

French. The geocode G3L, with value ‘BEAU CHATEAU’, is the language-localized geocode. Note that G3L is equivalent to G3 (‘BLUE CASTLE’) because both have the same first letters, B and C, in the same order. Furthermore, one can extend the language localization to non-Latin-script based target languages. This is done by transliterating a curated list of words in the target language to English and then using them as the base-20 encodings for G3L. Next, the interoperability of SmartAddresses is discussed.

[0071] Interoperability is often overlooked by geocode-based location identifiers. In addition to the language-localization, the present invention’s SmartAddresses can also be “fully localized” to even include actual zip/pin code and locality name following the local ad dressing standards. This ensures that fully localized SmartAddresses can coexist with local real-world addresses for interoperability. The full localization technique is il lustrated next for the Eiffel Tower.

[0072] Figure 9 illustrates a fully-localized SmartAddress 900 of the Eiffel Tower in French. The first line 801 is localized to French language as described previously in language- localization. And, the second line 902, with value “75007 PARIS”, contains the actual postal code (G14) followed by the locality name (G10) as per the French address standards. It should be noted that the two lines, 902 and 702, are considered equivalent. This is because line 702 can be easily constructed based on the information contained in 902. This step involves looking up the (latitude, longitude) values of the geographic center of the area represented by the postal/zip code in 902 and computing its -i-code ( G12) required for 702.

[0073] Due to the complexities of the real-world, SmartAddresses may need to be augmented with additional information when there is ambiguity in precisely identifying locations. Typically, this might happen in dense urban areas, multi dwelling units or high-rise buildings, etc. where the 10-meter resolution of Smar tAddresses is not adequate or a vertical location identifier is required. In such cases, SmartAddresses (700, 800, 900) can be easily augmented with auxiliary infor ation such as unit, apartment and suit number, etc.

[0074] The global applicability of the present invention is illustrated next with a few examples of SmartAddresses around the world. Table 10 shows US-style Smar tAddresses (700) and their semi/fully-localized forms (800 or 900) for various landmarks around the world.

[0075] [Table 10]

Table 10. US-style SmartAddresses and their localized forms around the world.

[0076] Some additional advantages of the SmartAddresses are discussed next.

[0077] Similar to a real-world address, SmartAddresses (700 and 800) contain area codes called +codes (G12) that act like postal or zip codes but at global scale. The +codes offer several unique advantages over traditional postal/zip codes. One of the ad vantages is that the +codes have the same format worldwide. For any location on the Earth, +codes have a 5-character alphanumeric format of “+DDADD”, where D is a digit in 0-9 and A is a character in A-Z. For example, the -i-code (G12) of the Eiffel Tower is ‘+25U53’.

[0078] In addition, the area represented by a -i-code (corresponding to the size of cell C2) is much larger than that of a postal/zip code. For instance, the area corresponding to the -i-code G12 of Eiffel Tower is 40 times larger than the city of Paris. Therefore, often +codes do not change within big cities unlike the traditional postal/zip codes. And, when they do change because a city happens to be split across multiple +codes, there will be no more than 4 +codes within such a city which is still far fewer than typical zip/postal codes within a city. For instance, the whole city of Paris has just 4 +codes whereas the actual postal codes in Paris is greater than 20.

[0079] Another advantage of the SmartAddresses stems from the fact that their first lines ( 701 or 801) are unique within a +code area. Therefore, just the first line of the Eiffel Tower’s SmartAddress, “@3608 BLUE CASTLE 66”, functions as a valid, precise, local identifier within its +code area of size 40 times the area of Paris. In summary, the first line of a SmartAddress (a) works as a valid local identifier in areas much larger than whole cities, (b) still works even if no traditional street address is available, and, (c) is more precise than a traditional real-world address if one is available. And so, in addition, SmartAddresses may be extremely useful for location communication in emergency and search & rescue operations.

[0080] SmartAddresses also have the unique advantage of backward compatibility. Because the locality-name (G10) is an optional component in SmartAddresses (700 & 800), a SmartAddress with valid components of G1-G5, will still refer to the same location even if the locality-name changes in the future. In other words, ignoring the effects of plate tectonics, SmartAddresses (700 & 800) are backward compatible even if the locality /town/city name changes. Note that this advantage does not apply to the “fully-localized” SmartAddresses (900) because the locality name (G10) and postal code (G14) are mandatory components in 900.

[0081] Another advantage of the present invention is attributed to the hierarchical nature of the geocodes (G1-G5). This can be exploited by using the hierarchical geocodes (GIGS) as database keys to efficiently attribute, store and retrieve geographically relevant information at various geographic resolutions (ranging from -100 km to -10 m) in spatial-indexing databases.

[0082] Another advantage of the present invention is that SmartAddresses can be easily validated offline simply by checking the validity of the encoded hierarchical cell co ordinates 203. A valid SmartAddress does not, however, mean that it is error-free. For instance, a valid SmartAddress may still contain human errors such as incorrect digits/ values for the geocodes G1-G5. When error checking is required, a SmartAddress can be easily augmented with a visual hash. For instance, when an incorrect SmartAddress is entered, the visual hashes will not match and the user can be notified of the error right away.

[0083] Another advantage of the present invention is that it is easy to reason about the direc tionality, distances and even time-zone differences between SmartAddresses just by a quick glance as described next.

[0084] Figure 10 illustrates techniques for estimating the directionality and distance with an example of the Eiffel Tower 1006 and a nearby location 1008 within the same -i-code. The local SmartAddresses (701) of 1006 and 1008 are “@3608 BLUE CASTLE 66” and “@3608 DIAMOND DRIVE 66”, respectively. Note that the two locations only differ in the G3 geocodes corresponding to third-level cells (C3). And so, for con venience, a local C3-cell grid 1000 is also shown in Figure 10.

[0085] As shown in Figure 10, the G3 geocodes of the cells are intuitively predictable. And so, often, the directionality between the two locations can be deduced just by glancing at the SmartAddresses. In this example, it is fairly easy to conclude that “@3608 DIAMOND DRIVE 66” (1008) is just two C3 blocks to the east and one C3 block to the north of the Eiffel Tower (1006).

[0086] The straight-line distance 1010, between the two locations can be approximated based on the easting and northing distances, 1012 and 1014, respectively. Here, the easting and northing distances are 2 and 1 C3 cells, respectively. At the Eiffel’s tower latitude of 49°, the C3 cell dimensions, L _3X and L _3Y , are 2.75 km and 4.2 km, re spectively (from Table 2). Therefore, the straight-line distance 1010 between the two locations can be estimated to be ~6.9 km using simple trigonometry. This estimate compares well with the actual distance of 6.89 km between the two locations considered.

[0087] As mentioned previously, SmartAddresses not only encode spatial information but also time-zone information. The time-zone difference between two SmartAddresses can be easily estimated based on their +codes alone. This is illustrated with an example of two locations 1006 (Eiffel Tower) and 1106 (San Jose, CA) in Figure 11. Their + codes (G12) are +25U53 and +08S97, respectively. And, their corresponding longitude bands ( g _]x ) are 25 and 08, respectively. Because each longitude band corresponds to 0.5 hours of time-zone difference, the approximate time-zone difference between the two locations can be estimated as (25 - 08) * 0.5 hours. The estimate of 8.5 hours compares well with the actual time-zone difference of 9 hours between Paris and San Jose, CA.

[0088] Figure 12 illustrates a flowchart 1200 of decoding a SmartAddress to produce latitude-longitude coordinates 201. Module 1202 decodes the geocodes in a Smar tAddress to generate hierarchical cell coordinates 203. Module 1204 initializes the latitude-longitude coordinates. And, module 1206 converts the hierarchical coordinates 203 to (latitude and longitude) coordinates 201. And finally, module 1208 inverts the origin offset done previously in location encoding module (302).

[0089] The detailed discussion so far has covered the encoding and decoding operations and various advantageous features of the present invention such as navigability, local- izability and interoperability of the SmartAddresses. Next, details on the applicability of present invention to existing hierarchical geocode schemes are described.

[0090] The present invention can be easily adapted and applied to other hierarchical geocode schemes to improve their memorability and recall. This is illustrated by considering two such schemes: Open Location Code and United State National Grid (USNG).

[0091] Similar to the present invention, the Open Location Code (OLC) scheme also uses a 5-level hierarchical grid but with its own set of grid discretization parameters distinct from those listed in Table 1. In the OLC scheme, a location’s (latitude, longitude) co ordinates are converted to the hierarchical cell coordinates and each coordinate is geocoded employing a custom base-20 encoding. A technique is described next to encode an Open Location code to produce an equivalent OLC SmartAddress re sembling a real-world address.

[0092] Figure 13 illustrates a high-level schematic 1300 of the encoding and decoding op erations to convert an Open Location Code (OLC) 1301 to an equivalent OLC Smar tAddress 1305 and vice versa. The operations involve an intermediate step of computing the native cell coordinates 1303. Steps 1302 and 1304 correspond to the encoding operations whereas steps 1306 and 1308 correspond to the decoding op erations. This is illustrated for the Eiffel Tower whose Open Location Code is 8FW4V75V+9R.

[0093] Table 11 lists the cell coordinates 1303 of the Eiffel Tower within the OLC hier archical grid system. The native coordinates 1303 can be directly encoded as geocodes (OLC1 - OLC5) by applying the formulas G1 - G5 listed in Table 5. Here, OLC1 = Gl, OLC2 = G2, OLC3 = G3, OLC4 = G4, and OLC5 = G5.

[0094] [Table 11]

Table 11. Open Location Code cell coordinates and their geocodes for the Eiffel Tower.

[0095] The geocodes, OLC1 - OLC5, are then arranged to form an equivalent OLC Smar tAddress 1400 as shown in Figure 14 to improve its memorability and recall. The same techniques described previously for language-localization 800 and full-localization 900 can be applied to 1400 to make it locality-friendly. The application of the present invention to USNG codes is described next.

[0096] The USNG scheme employs a 3-level hierarchical grid. Figure 15 illustrates a high- level schematic 1500 of the encoding and decoding operations to convert an USNG code 1501 to an equivalent USNG SmartAddress 1505 and vice versa. The operations involve an intermediate step of computing the hierarchical cell coordinates 1503. Steps 1502 and 1504 correspond to the encoding operations whereas steps 1506 and 1508 correspond to the decoding operations.

[0097] The encoding operations are illustrated for the Eiffel Tower whose USNG location identifier is 31U DQ 4825011950 ” corresponding to 1-meter resolution. The geocodes “3iC7” and “DQ” correspond to the first- and second-level geocodes, U1 and U2, respectively. The numbers 48250, 11950 are the easting and northing (in meters) corresponding to the native third- level cell coordinates, (E ₃ , N ₃ ). The easting and northing values (E ₃ , N ₃ ) can be converted to hierarchical cell coordinates (X ₃ , Y ₃ ), (X , Y ), and (X ₅ , Y ₅ ) following the grid discretization parameters, D ₃ , D ₄ , and D j , listed in Table 12. The corresponding geocodes U3, U4 and U5 can be computed as follows.

[0098] [Table 12]

Table 12. The discretization parameters used for USNG SmartAddress encoding.

[0099] A flowchart 1600 to convert the USNG easting and northing values to the hier archical cell coordinates is illustrated in Figure 16. Module 1602 corresponds to the initialization. And, module 1604 computes the hierarchical cell coordinates 1503. Finally, module 1606 encodes the coordinates as geocodes: U3, U4 and U5. Here, U3 = G3, U4 = G4, and U5 = G5. Table 13 lists the computed coordinates 1503 and the corresponding geocodes (Ul, U2, U3, U4, and U5) for the Eiffel Tower.

[0100] [Table 13]

Table 13. Hierarchical cell coordinates and the corresponding geocodes U1 - U5 for the Eiffel Tower’s USNG code.

[0101] The geocodes U1 - U5 are then assembled to form an equivalent USNG Smar- tAddress 1700 as illustrated in Figure 17 to improve its memorability and recall. The same techniques described previously for language-localization 800 and full- localization 900 can be applied to 1700 to make it locality-friendly.

[0102] Figure 18 illustrates a flowchart 1800 of decoding an equivalent USNG Smar- tAddress 1700 to produce its USNG code 1501. Module 1802 decodes the geocodes, U3, U4 and U5 to produce hierarchical coordinates 1503. Module 1804, initializes the (easting, northing) values. And, module 1806 computes the (easting, northing) values. Finally, module 1808 assembles and returns the USNG code.

[0103] A computer system is illustrated next to carry out the present invention.

[0104] Figure 19 illustrates an example of a location identification and communication system 1900 according to the present invention. The system comprises a number of client devices (smartphones 1902, personal computers 1904, other client devices 1906) connected to a central server 1912 over a network 1910. Configurable client software 1908 on the client devices may contain a variety of computer programs specially designed to carry out the invention. Although, for clarity, a simpler system is presented in Figure 19, it will be understood that in practice the system 1900 may comprise a large number of client devices connected to a central server over a wide variety of networks.

[0105] It should be noted that components corresponding to the network 1910 and central server 1912 are optional in system 1900. This is because the present invention’s location identifiers (700, 800, 900, 1400, and 1700) can be encoded and decoded offline on a client device 1906 with the aid of the specialized client software programs 1908 designed to carry out the present invention in the offline mode.

[0106] Figure 20 illustrates a client software program 2000 to compute SmartAddresses (700 , 800 and 900) according to the present invention. In module 2002, the user’ s or device’s latitude and longitude 201 may be obtained from accessing the built-in GPS unit, a specialized location service software program or from the input device of the client device 1906. Module 2004 computes the hierarchical cell coordinates 203 according to the flowchart 300. Module 2006 encodes the cell coordinates to produce hierarchical geocodes G1-G5 and assembles a SmartAddress (700, 800, 900). And, finally module 2008 returns an assembled SmartAddress to an output device or another computer program on the client device 1906 for further processing.

[0107] Figure 21 illustrates a client software program 2100 to decode SmartAddresses according to the present invention. In module 2102, a SmartAddress (700, 800, 900) to be decoded may be obtained from an input device of the client device 1906, from a network 1910 or from another client software 1908. In module 2104, the received location identifier is decoded first to produce hierarchical cell coordinates (203). In module 2106, the decoded cell coordinates are then converted to the latitude and longitude coordinates (201). Finally, module 2108 returns the (latitude, longitude) co ordinates to an output device or another computer program on the client device 1906 for further processing.

[0108] Anyone skilled in the art will be able to adapt the system 1900 to carry out the other parts of the invention to encode and decode existing hierarchical geocode identifiers such as Open Location Code (OLC) 1301 and USNG codes 1501 to their equivalent SmartAddresses (1400 and 1700) and vice versa. The client software programs 2000 and 2100 can be easily modified for this purpose following the description of the current invention. For reference, Figures 22 and 23 show modules of computer programs 2200 and 2300 to convert Open Location Codes 1301 to equivalent OLC SmartAddresses 1400 and vice versa. Similarly, Figures 24 and 25 show computer programs 2400 and 2500 to convert USNG/MGRS codes 1501 to equivalent USNG SmartAddresses 1700 and vice versa. Modules 2202, 2204, 2206, 2208, 2302, 2304, 2306, and 2308 are fairly descriptive for anyone skilled in the art and therefore, can be easily reproduced based on similar module descriptions in Figure 20 and 21. Similarly, modules 2402, 2404, 2406, 2408, 2502, 2504, 2506, and 2508 are also self-explanatory and can be easily reproduced following the current invention.

Claims

[Claim 1] A computer implemented method for generating human-friendly location identifiers comprising: receiving location information in the form of geographical coordinates such as latitude and longitude; computing plurality of hierarchical geocodes; and assembling the computed geocodes to produce a location identifier re sembling a real-world address.

[Claim 2] A computer implemented method for inverting the method of claim 1 comprising: receiving a location identifier resembling a real-world address; computing plurality of hierarchical geocodes; and converting the computed geocodes to geographical coordinates such as latitude and longitude.

[Claim 3] A computer implemented method for generating human-friendly, location identifiers comprising: receiving location information in the form of other publicly-available, hierarchically-geocoded location identifiers; computing plurality of hierarchical geocodes; and assembling the computed geocodes to produce a location identifier re sembling a real-world address.

[Claim 4] A computer implemented method of inverting the method of claim 3 comprising: receiving a location identifier resembling a real-world address; computing plurality of hierarchical geocodes; and converting the computed geocodes to the other publicly-available, hier archically-geocoded location identifiers.