Abstract:
A method of providing crime risk data in the absence or partial absence of officially reported data uses a scoring system based on images of locations within particular regions where crime data is to be assessed. The collected crime data may be normalized to actual crime data were both exist to calibrate the proxy crime data derived from the images.

Description:
CROSS REFERENCE TO RELATED APPLICATION 
       [0001]    This application claims the benefit of 61/328,786, filed Apr. 28, 2010, and is a continuation in part of U.S. patent application Ser. No. 12/597,425, filed Oct. 23, 2009, entitled “Mobile Navigation System with Graphic Crime-Risk Display”, both hereby incorporated by reference. 
     
    
     BACKGROUND OF THE INVENTION 
       [0002]    The present invention relates to information systems for use by travelers and in particular to an information system which provides the user with an indication the crime risk of a particular location. 
         [0003]    GPS and other navigation systems for portable use may contain digital maps of specific areas and may superimpose a user&#39;s location determined by the GPS on a graphical representation of the map. While the maps used in GPS systems currently are relatively static, it is also known to provide an ability to download updated or new maps with the GPS system to keep the loaded map system current, to load new maps for new areas or use wireless or cellular technology to exchange map information. The maps may include points of interest, restaurants, and other data likely to be useful to the traveler. 
         [0004]    Such systems are in particular demand by users who are unfamiliar with the roads in an area, and for this reason are particularly attractive to travelers and offered as a feature in rental cars. A traveler with a GPS system and an updated map, however, may have a false sense of security based on a knowledge of his or her location on the map but an ignorance about the safety of that location. For this reason, it has been proposed to provide a map overlay or the like indicating a risk of crime in the user&#39;s location as displayed on the GPS system. One such system is described in PCT application PCT/US2008/061482 claiming a priority date of Nov. 26, 2007 and entitled: “Mobile Navigation System with Graphic Crime-Risk Display” hereby incorporated by reference. 
         [0005]    A potential barrier to providing crime risk information to travelers and the like is in obtaining accurate crime data. While many municipalities by law must make such data available, the information is not always presented in a form that may be readily collected and disseminated to the public. Communities often have mixed incentive to accurately report crime and many communities provide no such reporting. 
         [0006]    The above referenced patent application describes using non-crime data such as population density, average income, density of government buildings and police stations and the like to supplement actual crime data. Such proxy data is imperfect and additional or superior proxy data would therefore be desirable. 
       SUMMARY OF THE INVENTION 
       [0007]    The present invention provides a source of proxy data derived from actual images of an area, scored according to visual features that are correlated to crime. Such images may be obtained readily from services such as Google using services such as Street View™ and Panoramio™ and may be scored automatically by image processing software or manually using Internet systems such as Mechanical Turk™ which enlist individuals. 
         [0008]    Specifically, the invention may provide a method of deriving crime data for different regions comprising the steps of: (a) collecting image data of the regions; (b) scoring the image data according to proxies for crime risk; and (c) presenting a map of the regions on a graphic display terminal having multiple shaded zones depicting crime risk based on the scoring for each region. 
         [0009]    It is thus a feature of at least one embodiment of the invention to provide a continuous or semi-continuous crime risk overlay in the face of absence of crime data for many locations. 
         [0010]    The method may further collect reported crime data by law enforcement officials for at least some regions and compare the scoring of the image data for the regions to the collected crime data to derive normalization information. The normalization information may be applied to the scores for regions where reported data by law enforcement officials has not been collected to provide uniform crime data for the different regions. 
         [0011]    It is thus a feature of at least one embodiment of the invention to employ actual crime data to calibrate the proxy crime data. 
         [0012]    The scoring of image data may evaluate factors selected from the group of visibility of trash, visibility of graffiti, visibility of window bars. 
         [0013]    It is thus a feature of at least one embodiment of the invention to identify visual features highly correlated to crime risk. 
         [0014]    The scoring of image data may evaluate factors selected from the group of visibility of late model cars, quality of the road surface, business types, number of residences visible. 
         [0015]    It is thus a feature of at least one embodiment of the invention to identify visual features indirectly related to crime risk. 
         [0016]    The spacing of the collection of images of the region may be adjusted according to the scoring of a region. 
         [0017]    It is thus a feature of at least one embodiment of the invention to compensate for inaccuracy in the proxy process by increasing sampling density. 
         [0018]    The scoring is performed by individuals viewing the images. 
         [0019]    It is thus a feature of at least one embodiment of the invention to provide a system that may accommodate a wide variety of image types. 
         [0020]    The images may be presented to the individuals as a panorama of 360°. 
         [0021]    It is thus a feature of at least one embodiment of the invention to ensure a comprehensive review of an environmental area. 
         [0022]    The scoring may include a marking of the images by the user viewing the images to highlight components of the scoring. 
         [0023]    It is thus a feature of at least one embodiment of the invention to provide the ability to reveal the underlying basis for the proxy to the end-user. 
         [0024]    The invention may provide an apparatus for implementation of the above method and in particular a navigation system having a graphics display and an electronic memory storing: (i) a street map; and (ii) crime data linked to locations. A computer executing a stored program may communicate with the graphics display, and the electronic memory to: (i) generate a display of a street map different locations; (ii) generate an overlay to the street map depicting the crime data different locations; (iii) generate an indication of whether the overlay is generated from officially collected crime data or from a proxy for crime data. 
         [0025]    It is thus a feature of at least one in body meant of the invention to provide an indication to the user of the basis for the crime risk data so as to improve confidence in the system. 
         [0026]    These and other object of the invention may apply to only some embodiments described herein and thus should not be used to define the scope of the invention 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0027]      FIG. 1  is a simplified figure of a display of a GPS device per the present invention showing by shaded areas a graphical representation all of criminal risk; 
           [0028]      FIG. 2  is a block diagram of the components of the GPS system of  FIG. 1  including map and crime data memories; 
           [0029]      FIG. 3  is a figure similar to that of  FIG. 1  showing the GPS display at a first time of day; 
           [0030]      FIG. 4  is a figure similar to that of  FIG. 3  showing the GPS display at a later time of day; and 
           [0031]      FIG. 5  is a set of graphical representations of the transformation of point crime data into the crime mapping of the present invention; 
           [0032]      FIG. 6  is a flow chart showing statistical development all of crime data from crime proxies; 
           [0033]      FIG. 7  is a block diagram of an extraction system for collecting comprehensive crime data on a real-time basis; 
           [0034]      FIG. 8  is a flow chart of the program executed by the extraction system of  FIG. 7 ; 
           [0035]      FIG. 9  is a flowchart of a map creator program used with the extraction system of  FIG. 7 ; 
           [0036]      FIG. 10  is a schematic diagram of a shape file created by the map creator program of  FIG. 9 ; 
           [0037]      FIG. 11  is a figure similar to that of  FIG. 1  showing accommodation of limited access highways in the display of the present invention; and 
           [0038]      FIG. 12  is a flowchart of a program using the crime data developed by the present invention for route planning purposes. 
           [0039]      FIG. 13  is a simplified system of a computer system communicating on a network for generation of the crime risk data per the present invention; 
           [0040]      FIG. 14  is a schematic representation of panoramic image data available at a variety of sample points for which crime data must be determined; 
           [0041]      FIG. 15  is a flow chart of the principal steps of the present invention as may be implemented entirely or in part on an automatic basis in an electronic computer; and 
           [0042]      FIG. 16  is a display produced by the present invention showing crime risk and supporting images. 
       
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
       [0043]    Referring now to  FIG. 1 , a GPS device of a type that may be mounted in a car or the like may provide a housing  12  supporting one or more user controllable buttons  14  on the side of a color graphic display  16 . As is generally understood in the art, the display  16  may depict a map showing streets  18  and a cursor  20  showing the location of the vehicle. The orientation of the streets may change to show the direction of travel of the vehicle according to standard conventions, for example, the direction of travel being vertical on the display  16 . 
         [0044]    The present invention may further provide for a first and second zone of shading  22  and  24  superimposed on the map and depicting a measure of the crime in the vicinity of the cursor  20 . The shading may be different brightnesses, colors, or highlighting, a density of points (either randomly placed or each indicating a crime), or simply boundary markings according to techniques well known in the art and may cover particular streets  18  (to be visually in front of the street) or be covered by the street (to be visually behind the street) reflecting the degree to which the crime risk indicated by the shading affects those on the street. 
         [0045]    For example, a local street  18   a  might be covered by shading  22  denoting a likelihood of auto theft. This is because auto theft would affect anyone parking on the local street  18   a . Conversely, a limited access highway  18   b  may be positioned visually in front of the shading  22  denoting a likelihood of auto theft, because travelers on the highway  18   b  would not be susceptible to problems of auto theft. A shading  24  denoting weapon crimes, on the other hand, might cover limited access highway  18   b  to the extent that such activity reflects a more significant risk to highway travelers. 
         [0046]    Referring now to  FIG. 2 , the GPS system  10  may employ standard GPS electrical architecture including a GPS receiver  30  communicating with a microcontroller  32  executing a standard operating system program. The GPS receiver may receive a GPS signals through a GPS antenna  34  and relay position information and time information to the microcontroller  32 . The microcontroller  32  may in turn control the display  16  to output the map of  FIG. 1 , for example, according to map data  36  held in a memory  37  and according to the time and position information from the GPS receiver  30 . The microcontroller  32  may also include an antenna  35 , or a socket  39  for standard memory card  38 , or other media input allowing downloading of map data  36  and crime risk data  41  into the GPS system  10 . 
         [0047]    This crime risk data  41 , as will be described, provides data compatible with the map data  36  to produce the shadings  22  and  24  described above. In particular the crime risk data  41  may provide for geographic coordinates demarcating zones of crime risk represented by areas of the shading  22  and  24 , crime risk types represented by colors, textures, or brightness of the shading  22  and  24 , and crime risk severity also represented by colors, textures or brightnesses. Different crime risk data  41  for a given location may be keyed to different times during the day, for example, business hours and after the business hours as will be described below. Alternatively or in addition the crime risk may be keyed to dates or ranges of dates to reflect seasonal variations, for example, weather or tourist influx. Alternatively, when the crime data is collected it may be linked to environmental conditions such as air temperature, phase of the moon, precipitation. For GPS systems that provide updated weather information be presented crime data may be adjusted to conform to those current environmental conditions. The crime risk types may include and distinguish among, for example, auto theft, assaults against persons, drug arrests, traffic violations such as speeding, and the like. In addition non-crime data proxies may be provided such as population density, average income, density of government buildings and police stations, and the like. 
         [0048]    Referring now to  FIG. 3 , the keying of crime data to different times of the day allows the display  16  to provide for different crime shadings  22  and  24  depending on the time derived from a clock of the GPS receiver  30 . For example, during business hours, as shown in  FIG. 3 , a crime zone of shading  22  might be fairly isolated representing streets that are not main thoroughfares or the like, whereas at a later time, for example, after the normal business day, crime zone of shading  22  may increase and a new zone of crime shading  24  may appear. The user may be given a feature allowing them to accelerate the clock to look at the transition of crime during the day in animated form. In one display mode, the animation may cycle through the current day with a depiction of the time of day so as to give the user an indication of changes in crime patterns that they may experience in that area. 
         [0049]    Referring now to  FIG. 5 , crime data may be obtained from a variety of public sources, generally as crime points  40 ,  42  or  43  where a given crime will be identified as to type, time of day and date, and location on a geographic grid  44 . This data may retained as point data indicating an incident of a crime type (for example through color) and its location, or may be turned into areal crime shadings  22  and  24  through the use of a first two-dimensional convolution kernel  46  applied to each crime point  40 ,  42  and  43  (only crime point  42  shown for clarity) where the two-dimensional convolution kernel  46  is aligned with each transportation corridor  50  on the grid  44  reflecting a general propensity of crime risk to travel with people along transportation corridors. In this case, a simple two-dimensional Gaussian curve may be used as the convolution kernel  46  reflecting a general fall off of crime as one moves away from the crime scene. A sum of the results of the two-dimensional convolution kernel  46 , applied to each crime point  40   42  and  43 , for each transportation corridor  50 , may then be modified by a general blurring convolution kernel  52  which provides a smooth continuity of crime risk over broader area. The height of the surface created after the convolution by kernel  52  may be represented by iso-crime lines  54  assigning both spatial extent and risk to each particular crime type. 
         [0050]    As will be understood, a crime map  56  is created from the iso-crime lines  54  and stored in the GPS system  10 . A crime shading  22  or  24  can then be created by applying a predetermined threshold to the crime map including the area within iso-crime lines  54  greater than or equal to this threshold. Typically this threshold will be set by the manufacturer but may be adjusted by the user to allow their risk propensities to be respected. 
         [0051]    In cases where the crime data is sparse at the given magnification of the map, invoking the crime data it may cause a zooming out all the map to a resolution were meaningful crime statistics can be displayed. The user may set the thresholds for the amount of crime risk to be displayed and the types of crime to be displayed, for example opting to show only severe crime risks or crime risks key to the current time of day, range of dates, or environmental conditions. The user may opt to view only actual crime data or actual crime data and crime data derived from proxy sets as will be described. 
         [0052]    The crime maps of  56  may be updated periodically and provided to subscribers to give them ongoing indications of possible risks. 
         [0053]    Referring now to  FIG. 6 , not all jurisdictions provide crime data and there may be some situations where crime data provided by a particular area is suspect or incomplete. In these cases the user may still be provided with crime shadings  22  and  24  by using a statistical process in which more readily available data termed “proxy sets”  60  are collected for various geographical regions. These proxy sets may include, for example, standard census data including population density and income ranges, and may be augmented with commercially available data such as home prices, loan defaults, insurance claims, and the like. Without the need to understand the sociological implications of this demographic data, the proxy sets  60  may be correlated to known crime data  62  for the same regions by a correlation process  64  of type well known in the art to produce a set of correlation rules  66  relating one kind of data to the other. For example, through standard regression, a formula may be developed equating the proxy set with particular crime risk. These correlation rules  66  may be applied to proxy sets  68  of other jurisdictions having unknown or suspect crime data to develop synthesized crime data  70  that may still provide the user with some guidance in areas where there would otherwise be no guiding data. 
         [0054]    Referring now to  FIG. 7 , the collection of high-resolution crime data providing time place and crime type as is necessary to produce the present invention is hampered by two significant factors. First, in the United States, and in most countries, police activity is exclusively in the hands of local governments who therefore hold the exclusive right to the operation of a police force and the collection and dissemination of crime data. Such government entities operate outside of the private sector and can be indifferent to market demands to provide comprehensive and accessible crime data. The control of this data by local governmental entities can also create a disincentive to make crime data freely and easily available if that data may reflect poorly on local communities. These factors are reflected in the wide variety of different websites reporting crime data in a tabular form that requires entry of specific addresses before data will be released. 
         [0055]    Accordingly, the present inventors have developed an extraction system  72  operating over the Internet  74  to interact with various different crime-reporting sites  76   a - 76   c  in the manner of an individual user capable of adapting to idiosyncratic user interfaces. The extraction system  72  collects data and compiles it into a comprehensive view of the crime situation in a particular area. 
         [0056]    In a preferred embodiment, the extraction system  72  comprises a Web connected computer  78  having a browser  80  executing a gathering program  82 . The gathering program  82  employees a Web address list  84  holding URLs of the particular websites  76   a - 76   c  through which this data is provided. The gathering program  82  further includes a set of scripts  86  uniquely identified to one website  76  and that provides set of steps for iteratively extracting a full set of data from the particular website  76 . The crime data extracted from the website is stored in a uniform format in a database  88  that may be also implemented on the extraction system  76 . If the website requires authorization to access the database of information, login information can be extracted from the page by searching for text after the terms “user” and “password” if that cannot be found the server will check for a password to the site stored in the database. Alternatively if the website requires authorization or password which is protected by requiring a user to respond to a CAPTCHA. In this case either a user can oversee any CAPTCHA each time the server runs the gather process or alternatively the page with the CAPTCHA can be sent to a Amazon (or other company) providing a “Mechanical Turk” program where human operators are paid small amounts of money to do simple tasks that are difficult of a computer. In this manner the gatherer can function without direct user intervention by the server administrator. 
         [0057]    A map generation program  90  converts the data of the database  88  into the desired map formats and may download them again over the Internet  74  to particular users of GPS devices  92 . 
         [0058]    Referring now to  FIG. 8 , the gathering program  82  may begin operation as indicated by process block  94  by contacting an individual website (for example  76   a ) identified for example by the first web address on Web address list  84 . At succeeding process block  96 , the gathering program  82  executes the particular script  86  necessary to extract the data from that websites  76   a . The script  86  will typically execute repeatedly as indicated by arrow  98 , for example, entering in each address on a given street to check the occurrence of crime at that address, if necessary. The scripts  86  will be customized to the particular websites  76  to extract crime type, crime location, and crime time. 
         [0059]    At succeeding process block  100 , additional data may be added to the extracted data from the script  86  itself to provide a complete picture of the crime incidents. Most typically, this added data will be a city and a state which are normally implicit in the data of the particular website  76  but not contained per se in the data output from that website  76 . As noted, data is then formatted in a consistent form and provided to a geocoder  102 , being a website that will take a street address and converted to a longitude and latitude value per process block  104 . At the conclusion of this process, a data structure will be obtained and stored in the database  88  as indicated in the following Table 1. 
         [0000]    
       
         
               
               
               
               
               
               
               
               
               
             
               
               
               
               
               
               
               
               
               
             
           
               
                 TABLE 1 
               
               
                   
               
               
                   
                   
                   
                   
                   
                   
                   
                   
                 UTM 
               
               
                 SAddress 
                 City 
                 State 
                 Zip 
                 Geo 
                 CrimeCode 
                 CrimeDes 
                 Date/Time 
                 Square 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                 111 E 
                 Milwaukee 
                 WI 
                 53202 
                 43.038539, 
                 1 
                 ALL OTHER LARCENY 
                 Oct. 16, 2007 
                 34 
               
               
                 WISCONSIN 
                   
                   
                   
                 −87.909517 
                   
                   
                 08:11 AM 
               
               
                 AV 
               
               
                 1216 E 
                 Milwaukee 
                 WI 
                 53202 
                 43.053092, 
                 5 
                 ALL OTHER LARCENY 
                 Oct. 16, 2007 
                 31 
               
               
                 BRADY ST 
                   
                   
                   
                 −87.896512 
                   
                   
                 09:10 PM 
               
               
                 2066 N 
                 Milwaukee 
                 WI 
                 53202 
                 43.058249, 
                 5 
                 THEFT FROM MOTOR 
                 Oct. 17, 2007 
                 22 
               
               
                 CAMBRIDGE 
                   
                   
                   
                 −87.891785 
                   
                 VEHICLE 
                 11:11 PM 
               
               
                 AV 
               
               
                 133 N 
                 Milwaukee 
                 WI 
                 53202 
                 35.644868, 
                 1 
                 ALL OTHER LARCENY 
                 Oct. 18, 2007 
                 34 
               
               
                 JACKSON 
                   
                   
                   
                 −88.857165 
                   
                   
                 3:11 AM 
               
               
                 ST #233 
               
               
                   
               
             
          
         
       
     
         [0060]    This data structure provides a particular address of a crime and the city, state, and (optionally) zip code, shown in the first through fourth columns. This information, when fed to the geocoder, provides a longitude and latitude value shown in the fifth column. A crime code is usually extracted from the website which provides a coding according to a standard FBI coding scheme or a variant on this scheme implemented by various localities. The script  86  translates these locally implemented codes into a standard FBI coding scheme and stores the code and a written description at columns  6  and  7 . The date and time of the crime is also obtained and stored at column  8  to provide data specific to different seasons or times of the day. Whether data and almanacs may be consulted to add in information about environmental conditions for example air temperature, phase of the moon, precipitation that may improve the predictive power of the crime data when it is displayed. Thus, for example, when there is a new moon at night crime data may increase for some types of crime. 
         [0061]    The program  82  next calculates a UTM grid value, as will be described below, identifying a regular region (e.g. a grid square) in which the crime occurred. This is indicated by process block  106  and added to the data structure at column  9 . 
         [0062]    At process block  108 , after all the data is extracted from a given website  76   a , the next site in the list  84  is accessed and this process is repeated. The extraction system may operate at regular intervals during the day preferably at times of low Internet use. 
         [0063]    Referring now to  FIG. 10 , a crime map may be generated from the data structure of Table 1 by dividing the world into regular polygons, in this case squares having a width and height of 0.005° of longitude or latitude or any size block depending on the granularity which is desired. The mapping to the grid described with respect to process block  106  above, then simply determines whether a particular crime incident  110  occurred within a particular UTM square  112 , each UTM square  112  having a unique identifier  114 . This mapping is precalculated at process block  106  for greater speed in map generation or done at this time for greater flexibility in determining types and times of crime. 
         [0064]    Referring now to  FIG. 9 , the generation of a map may be performed on demand beginning at process block  115  where, for example, according to a user request, the data of the database  88  is sorted by map generation program  90  to obtain crime statistics in a particular area of the world (for example, as defined by a set of UTM numbers) at a particular time and date range. The date range may be dynamically adjusted to obtain a statistically significant sampling of data for the crime map weighting which is most current. In this respect, the data may span more than one year, for example, for seasonal data, looking at comparable seasonal crime during previous years to establish a trend line used to establish current crime values. 
         [0065]    At process block  116 , the sorted data, in one embodiment, is then used to populate a grid of UTM squares  112  within in area to the desired map. The number of crime incidents in each UTM square  112  is then mapped to a color for the square, for example, green shades indicating relatively low crime rates and red shades indicating relatively high crime rates according to standard mapmaking conventions. 
         [0066]    The color values all the UTM squares  112  are then assembled to create a shape file in a vector format defining polygons having vertices and a particular translucent shading value as determined by the number of crime incidents  110 . This shape file creation is indicated at process block  118 . The shape file may then be downloaded, as indicated by process block  120  to a GPS user and provides an overlay on existing maps already held in the GPS device and in a format that may be readily interpreted by most GPS systems. 
         [0067]    Referring now to  FIGS. 8 and 9 , the shape file created at process block  118  may include a margin  122  around limited access highways  124  reflecting the fact that local crime statistics usually do not affect high-speed traffic on busy highways that may go through those neighborhoods. This margin  122  may increase as the scale of the map is increased to provide a visual indication of this feature for travel planning. 
         [0068]    Referring to  FIG. 12 , the present invention also provides a method of incorporating crime data, as described above, into the route planning process. Using the database  88  developed above with respect to  FIG. 8 , travel planning program  130 , such as may operate on a computer similar to that described in  FIG. 7 , may use standard routing techniques per process block  132  to identify a shortest route between two points identified by the user. At process block,  134  that route is traversed point by point per process blocks  136 - 144 . 
         [0069]    If the user has identified a starting time, then as the route is traversed, that time is updated per process block  136  by regular increments and a location along the route determined at process block  138  using known statistics on road type or average traffic velocity. If the user has not identified a starting time an arbitrary time of zero is selected and the time of occurrence of the crimes is ignored. 
         [0070]    At decision block  140 , it is determined whether, at the particular location determined by process block  138 , the route is on a limited access highway. If so, the program  130 , loops back to process block  136  to continue traversal of the route. If at decision block  140  the user is not on a limited access highway, but instead on a local road, then at decision block  142  the crime statistics in the UTM square  112  of the location is reviewed to see whether a crime threshold (selectable by the user) has been exceeded. If not, the program  130  loops back to process block  136  to continue traversal, but if so, a new second shortest route (under the constraint of not using the road passing through the indicated crime zone) is determined and the traversal process is reinitiated looping back to process block  134 . When a route has been fully traversed without exceeding the desired crime threshold, the route is output as indicated by process block  136 . 
         [0071]    This same process could be used to assess the travel risk of a particular route and assign it a quantitative value that could be used for example by shipping or trucking companies to add a safety surcharge based on whether their vehicles travel into unsafe areas. 
         [0072]    The collection of crime data can be augmented by enlisting users of the GPS device itself. Such users, perhaps provided with an incentive with respect to obtaining crime data, can report on their perceptions of crime in the area where they live or with an advanced GPS system providing for two-way communication by entering simple data into the GPS device reflecting their perception of their current location for example “this area is safe” or “this area is unsafe”. While this data would not necessarily be as reliable as other types of crime data, its quality could be factored into an assessment of total crime risk. Further this sort of data may have greater weighting near the time of the reporting. 
         [0073]    Crime data obtained from public sources and through the use of proxies can also be augmented by crime data reported on paper the latter which may be analyzed using optical character recognition or manually input. In this way data can be collected from any source even those not reporting electronically. 
         [0074]    Integrating the current crime system into a concierge service such as COMMAND from Mercedes or ONSTAR from GM could be used to increase response times for calls generated by stopped vehicles in high crime areas. 
         [0075]    Referring now to  FIG. 13 , a computer system  210  useful for production of crime data per the present invention may provide a server/computer  212  executing a stored program  214  to communicate on the Internet  216  with a remote database  220  through a server  218 . The remote database  220  may, for example, include crime data collected by municipalities and the like in addition to ground level images of particular geographic locations. The database  220  need not be a single installation and may, in fact, represent multiple servers  218  and databases  220  accessible through the Internet  216 . 
         [0076]    Multiple individual computers  222  may also communicate through the Internet  216  with the server/computer  212  to provide crime data input that will be stored in database  223 . 
         [0077]    Referring now to  FIGS. 14 and 15 , the program  214  may operate as indicated by process block  224  to identify sample points  227  in a geographic region  230  for which augmenting crime data is desired. Typically, such sampled points will be both in regions where official crime data is required (for bench marking purposes) and regions where scarce or no official crime data is available. Ideally the crime sample points will be randomly selected and dispersed. 
         [0078]    For each sample point  227 , a ground-level image  232  will be developed, for example, of panoramic view of greater than 180° and typically 360° at the sample point  227  as would be visible by a person on the ground. The particular sample points  227  may then be provided to the individual user of computer  222  together with an electronic scorecard to complete based on that image. The individual may be required to circle particular elements on a display screen to allow for machine scoring for each element with different weights for different feature of interest and to permit display of the circled elements to ultimate users for independent assessment of the scoring. 
         [0079]    As indicated by process block  234 , individuals at the computers  222  may then review the images  232  with respect to predetermined categories such as for example, overall impression, the visibility of trash, graffiti, late model cars (e.g. greater than 10 years old), state of repair of buildings, presence of window bars, quality of the roads, business types, number of residences visible, et cetera. These scorecards can be refined by an empirical testing in which actual crime data from law enforcement agencies as reduced to a crime index is compared to a risk value determined from the scorecard categories and correlated to identify those categories with highest correlation. 
         [0080]    For example a questionnaire may provide the following questions: 
         [0000]    (1) multiple pieces of visible trash (yes/no)
 
(2) multiple instances of visible graffiti (yes/no)
 
(3) visible window bars (yes/no)
 
(4) prepare state of road (good/average/poor)
 
(5) visible check-cashing stores (yes/no)
 
(6) visible disabled cars (yes/no)
 
         [0081]    A quantitative score may be developed using the following scoring: 
         [0000]    question 1: yes=10, no=zero
 
question 2: yes=10, no=zero
 
question 3: yes=10, no=zero
 
question 4: good=0, average=5, poor=10
 
question 5: yes=10, no=zero
 
question 6: yes=10, no=zero
 
         [0082]    For example, a questionnaire may be completed with respect to the predetermined categories and scored to produce a quantitative value of 70, for example, were higher values indicate higher crime risk. This value may then be compared to an index value derived from actual crime data, for example, indicating particular categories of crime and the number of incidents per time per area. This index value may be, for example, 80. A normalizing factor may then be developed equal to 80/70 and used to multiply the quantitative values provided from the questionnaire for areas where there is no official crime data. Thus, for example, an area with no official crime data may provide a questionnaire value of 60 and using the normalizing factor derived above of 80/70 may yield a normalized crime value of 68.5. 
         [0083]    When a subjective evaluation of an individual is used in the scoring, a different normalization factor may be used for each such individual, to provide consistency among different individuals. 
         [0084]    As indicated at process block  236 , the proxy data obtained in this manner may be fit to known crime data in the region, if any, and used to provide for higher granularity crime data. Alternatively the proxy data may be used alone to determine the crime risk in an area. When a proxy is used, that fact may be indicated on the display screen to the user. 
         [0085]    As indicated by process block  238 , the crime data, being any or both of actual crime data and proxy data may then be used to provide a map output or the like such as a single indicator bar, graphic, number or the like useful for the user of a mobile phone, home computer, or automotive device, indicating an assessment of crime risk in the particular region selected by the user or derived from GPS or the like from the location of the user. 
         [0086]    Referring now to  FIG. 16 , in the latter case, the map  240  may display standard map features such as roads  242  and the like and provide shaded zones  244  indicating generally a crime risk. Each zone may provide one or more images  246  providing reference for the user of the type of image data underlying a particular crime assessment. In this respect, the images may be ranked according to the amount that they are relied upon in the crime assessment and only the highest ranked image shown, to allow the user to make an independent assessment. The particular images may be highlighted to show features relied upon in the evaluation, for example circling or highlighting of a disabled car. 
         [0087]    The scoring may be statistically processed, for example, by averaging scores in a number of regions and the statistical sampling may be adjusted depending on the score of neighboring regions to obtain additional data. That is, for example, those areas rated with high crime may receive additional sample points to reduce the possibility of an anomaly caused by a single poorly maintained building or the like. Generally, statistical techniques of smoothing, for example, data fitting to a limited order surface, may be applied to the proxy crime data as will be understood in the art. 
         [0088]    It will be understood that the scoring of the images may also be done by computer algorithms using machine learning or the like. It will further be understood that the source of the crime assessment may be indicated to be through the use of proxy sources such as the scoring system described above when actual crime data is not available. 
         [0089]    It is specifically intended that the present invention not be limited to the embodiments and illustrations contained herein and the claims should be understood to include modified forms of those embodiments including portions of the embodiments and combinations of elements of different embodiments as come within the scope of the following claims. All of the publications described herein, including patents and non-patent publications, are hereby incorporated herein by reference in their entireties.