Patent Publication Number: US-2018033109-A1

Title: Using public safety data to manage a criminal event response

Description:
BACKGROUND 
     This disclosure relates generally to computer systems and, more particularly, relates to managing data associated with a criminal event. Managing criminal event response may be desired to be performed as efficiently as possible. The amount of data that needs to be managed by enterprises related to public safety and criminal events is increasing. As data needing to be managed increases, the need for management efficiency may increase. 
     SUMMARY 
     Aspects of the disclosure relate to using data associated with criminal history information, street networks, criminal behavior, and graphical user interfaces in order to efficiently predict likely destinations and routes for a set of individuals who correspond to a criminal event. For example, a set of candidate routes can be determined because, in general, a fleeing bank robber may make a right-hand turn out of the bank parking lot, may avoid u-turns, and may be likely to head towards the closest highway. In addition, by combining such information with traffic information, construction information, as well as non-street-network information such as physical descriptions of the set of individuals, criminal history, and the like, aspects of the disclosure may be useful to accurately determine likely candidate routes that the set of individuals may take. In certain embodiments, likely destinations of the set of individuals may be discerned using aspects described herein. 
     Aspects of the disclosure relate to criminal event response management using a set of public safety data. An origin location of a criminal event can be received. The criminal event may have a set of individuals. Based on the origin location and the set of public safety data with respect to the criminal event a set of candidate target locations for the set of individuals can be identified. Using the origin location and the set of candidate target locations, a set of candidate routes—from the origin location to the set of candidate target locations—may be computed. Based on a set of relationships of the set of candidate routes, determination(s) may be made with respect to a set of predicted locations for the set of individuals and a set of suggested public safety officer positions. Accordingly, the set of predicted locations for the set of individuals and the set of suggested public safety officer positions may be provided. Various performance or efficiency benefits may result. 
     The above summary is not intended to describe each illustrated embodiment or every implementation of the present disclosure. 
    
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
       The drawings included in the present application are incorporated into, and form part of, the specification. They illustrate embodiments of the present disclosure and, along with the description, serve to explain the principles of the disclosure. The drawings are only illustrative of certain embodiments and do not limit the disclosure. 
         FIG. 1  depicts a high-level block diagram of a computer system for implementing various embodiments of the present disclosure. 
         FIG. 2  is a diagrammatic illustration of an example computing environment according to embodiments. 
         FIG. 3  is a flowchart illustrating a method for criminal event response management using a set of public safety data according to embodiments. 
         FIG. 4  is a flowchart illustrating a method for criminal event response management using a set of public safety data according to embodiments. 
         FIG. 5  shows an example use-case of criminal event response management using a set of public safety data according to embodiments. 
     
    
    
     While the invention is amenable to various modifications and alternative forms, specifics thereof have been shown by way of example in the drawings and will be described in detail. It should be understood, however, that the intention is not to limit the invention to the particular embodiments described. On the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention. 
     DETAILED DESCRIPTION 
     Aspects of the disclosure relate to using data associated with criminal history information, street networks, criminal behavior, and graphical user interfaces in order to efficiently predict likely destinations and routes for a set of individuals who correspond to a criminal event. For example, a set of candidate routes can be determined because, in general, a fleeing bank robber may make a right-hand turn out of the bank parking lot, may avoid u-turns, and may be likely to head towards the closest highway. In addition, by combining such information with traffic information, construction information, as well as non-street-network information such as physical descriptions of the set of individuals, criminal history, and the like, aspects of the disclosure may be useful to accurately determine likely candidate routes that the set of individuals may take. In certain embodiments, likely destinations of the set of individuals may be discerned using aspects described herein. 
     In recent years, there have been thousands of bank robberies in the United States. In general, only slightly more than half of the individuals responsible were identified. When a bank robbery occurs, a typical response by law enforcement may be a “bullseye” strategy. According to such strategy, law enforcement situates themselves at varying distances from the bank in hopes to catch the suspects. Such a methodology may be inefficient and can have a low probability of finding the set of individuals. As time elapses, the probability of finding the suspects may decrease further since the number of streets and destinations becomes too great to effectively monitor. Having the ability to predict which routes a set of individuals is likely to take, and furthermore, knowing potential destinations or hideouts of a bank robber, may reduce the number of resources and officers needed to monitor for escaping vehicles. Accordingly, the probability of catching the suspects quickly may increase. Aspects of the disclosure may predict a set of candidate routes for the set of individuals, predict a set of potential destinations, and provide a set of suggested public safety officer positions. 
     Aspects of the disclosure include a method, system, and computer program product for criminal event response management using a set of public safety data such as COPLINK (trademark of International Business Machines Corporation) or the like. An origin location of a criminal event can be received. The criminal event may have a set of individuals. Based on the origin location and the set of public safety data with respect to the criminal event a set of candidate target locations for the set of individuals can be identified. Using the origin location and the set of candidate target locations, a set of candidate routes—from the origin location to the set of candidate target locations—may be computed. Based on a set of relationships of the set of candidate routes, determination(s) may be made with respect to a set of predicted locations for the set of individuals and a set of suggested public safety officer positions. Accordingly, the set of predicted locations for the set of individuals and the set of suggested public safety officer positions may be provided. 
     In embodiments, the set of public safety data can be examined for residence data of a set of persons with a historical record corresponding to the criminal event within a threshold distance of the origin location. In certain embodiments, a subset of the set of persons which have a physical description that corresponds to a reported physical description from the criminal event may be selected. The set of candidate target locations can include at least one of: a set of freeway exits, a set of freeway on-ramps within a threshold proximity of the origin location, a set of city entrances, a set of city exits, a set of rental car facilities, a set of transportation facilities, a set of airports, a set of bus stops, or a set of train stops. The set of candidate routes can include at least one of: a set of property exits from the origin location, a set of routes that uses a turn-propensity weight to indicate a right-hand turn likelihood which exceeds a left-hand turn likelihood, a specific route that uses a u-turn weight to indicate a threshold u-turn likelihood which exceeds a specific u-turn likelihood for the specific route, a set of road construction factors, or a batch of routes that uses a road-segment weight to indicate a major road-segment likelihood which exceeds a minor road-segment likelihood. 
     In embodiments, a set of temporal factors is evaluated. The set of temporal factors can include at least one of: a quantity of time since the criminal event, a set of estimated travel times, or a time of day. In embodiments, providing the set of predicted locations for the set of individuals and the set of suggested public safety officer positions includes presenting a set of visual indicators. In various embodiments, presenting the set of visual indicators includes displaying a color-coded heat map. In certain embodiments, displaying the color-coded heat map includes modifying, in a dynamic fashion based on a set of updated information, the color-coded heat map to indicate a change in the set of predicted locations for the set of individuals and the set of suggested public safety officer positions. Altogether, performance or efficiency benefits (e.g., reliability, speed, flexibility, responsiveness, stability, resource usage, productivity) may result from aspects described herein. Accordingly, aspects may save resources such as bandwidth, processing, or memory. 
     Turning now to the figures,  FIG. 1  depicts a high-level block diagram of a computer system for implementing various embodiments of the present disclosure, consistent with various embodiments. The mechanisms and apparatus of the various embodiments disclosed herein apply equally to any appropriate computing system. The major components of the computer system  100  include one or more processors  102 , a memory  104 , a terminal interface  112 , a storage interface  114 , an I/O (Input/Output) device interface  116 , and a network interface  118 , all of which are communicatively coupled, directly or indirectly, for inter-component communication via a memory bus  106 , an I/O bus  108 , bus interface unit  109 , and an I/O bus interface unit  110 . 
     The computer system  100  may contain one or more general-purpose programmable central processing units (CPUs)  102 A and  102 B, herein generically referred to as the processor  102 . In embodiments, the computer system  500  may contain multiple processors; however, in certain embodiments, the computer system  100  may alternatively be a single CPU system. Each processor  102  executes instructions stored in the memory  104  and may include one or more levels of on-board cache. 
     In embodiments, the memory  104  may include a random-access semiconductor memory, storage device, or storage medium (either volatile or non-volatile) for storing or encoding data and programs. In certain embodiments, the memory  104  represents the entire virtual memory of the computer system  100 , and may also include the virtual memory of other computer systems coupled to the computer system  100  or connected via a network. The memory  104  can be conceptually viewed as a single monolithic entity, but in other embodiments the memory  104  is a more complex arrangement, such as a hierarchy of caches and other memory devices. For example, memory may exist in multiple levels of caches, and these caches may be further divided by function, so that one cache holds instructions while another holds non-instruction data, which is used by the processor or processors. Memory may be further distributed and associated with different CPUs or sets of CPUs, as is known in any of various so-called non-uniform memory access (NUMA) computer architectures. 
     The memory  104  may store all or a portion of the various programs, modules and data structures for processing data transfers as discussed herein. For instance, the memory  104  can store a criminal event response management application  150 . In embodiments, the criminal event response management application  150  may include instructions or statements that execute on the processor  102  or instructions or statements that are interpreted by instructions or statements that execute on the processor  102  to carry out the functions as further described below. In certain embodiments, the criminal event response management application  150  is implemented in hardware via semiconductor devices, chips, logical gates, circuits, circuit cards, and/or other physical hardware devices in lieu of, or in addition to, a processor-based system. In embodiments, the criminal event response management application  150  may include data in addition to instructions or statements. 
     The computer system  100  may include a bus interface unit  109  to handle communications among the processor  102 , the memory  104 , a display system  124 , and the I/O bus interface unit  110 . The I/O bus interface unit  110  may be coupled with the I/O bus  108  for transferring data to and from the various I/O units. The I/O bus interface unit  110  communicates with multiple I/O interface units  112 ,  114 ,  116 , and  118 , which are also known as I/O processors (IOPs) or I/O adapters (IOAs), through the I/O bus  108 . The display system  124  may include a display controller, a display memory, or both. The display controller may provide video, audio, or both types of data to a display device  126 . The display memory may be a dedicated memory for buffering video data. The display system  124  may be coupled with a display device  126 , such as a standalone display screen, computer monitor, television, or a tablet or handheld device display. In one embodiment, the display device  126  may include one or more speakers for rendering audio. Alternatively, one or more speakers for rendering audio may be coupled with an I/O interface unit. In alternate embodiments, one or more of the functions provided by the display system  124  may be on board an integrated circuit that also includes the processor  102 . In addition, one or more of the functions provided by the bus interface unit  109  may be on board an integrated circuit that also includes the processor  102 . 
     The I/O interface units support communication with a variety of storage and I/O devices. For example, the terminal interface unit  112  supports the attachment of one or more user I/O devices  120 , which may include user output devices (such as a video display device, speaker, and/or television set) and user input devices (such as a keyboard, mouse, keypad, touchpad, trackball, buttons, light pen, or other pointing device). A user may manipulate the user input devices using a user interface, in order to provide input data and commands to the user I/O device  120  and the computer system  100 , and may receive output data via the user output devices. For example, a user interface may be presented via the user I/O device  120 , such as displayed on a display device, played via a speaker, or printed via a printer. 
     The storage interface  114  supports the attachment of one or more disk drives or direct access storage devices  122  (which are typically rotating magnetic disk drive storage devices, although they could alternatively be other storage devices, including arrays of disk drives configured to appear as a single large storage device to a host computer, or solid-state drives, such as flash memory). In some embodiments, the storage device  122  may be implemented via any type of secondary storage device. The contents of the memory  104 , or any portion thereof, may be stored to and retrieved from the storage device  122  as needed. The I/O device interface  116  provides an interface to any of various other I/O devices or devices of other types, such as printers or fax machines. The network interface  118  provides one or more communication paths from the computer system  100  to other digital devices and computer systems; these communication paths may include, e.g., one or more networks  130 . 
     Although the computer system  100  shown in  FIG. 1  illustrates a particular bus structure providing a direct communication path among the processors  102 , the memory  104 , the bus interface  109 , the display system  124 , and the I/O bus interface unit  110 , in alternative embodiments the computer system  100  may include different buses or communication paths, which may be arranged in any of various forms, such as point-to-point links in hierarchical, star or web configurations, multiple hierarchical buses, parallel and redundant paths, or any other appropriate type of configuration. Furthermore, while the I/O bus interface unit  110  and the I/O bus  108  are shown as single respective units, the computer system  100  may, in fact, contain multiple I/O bus interface units  110  and/or multiple I/O buses  108 . While multiple I/O interface units are shown, which separate the I/O bus  108  from various communications paths running to the various I/O devices, in other embodiments, some or all of the I/O devices are connected directly to one or more system I/O buses. 
     In various embodiments, the computer system  100  is a multi-user mainframe computer system, a single-user system, or a server computer or similar device that has little or no direct user interface, but receives requests from other computer systems (clients). In other embodiments, the computer system  100  may be implemented as a desktop computer, portable computer, laptop or notebook computer, tablet computer, pocket computer, telephone, smart phone, or any other suitable type of electronic device. 
       FIG. 1  depicts several major components of the computer system  100 . Individual components, however, may have greater complexity than represented in  FIG. 1 , components other than or in addition to those shown in  FIG. 1  may be present, and the number, type, and configuration of such components may vary. Several particular examples of additional complexity or additional variations are disclosed herein; these are by way of example only and are not necessarily the only such variations. The various program components illustrated in  FIG. 1  may be implemented, in various embodiments, in a number of different manners, including using various computer applications, routines, components, programs, objects, modules, data structures, etc., which may be referred to herein as “software,” “computer programs,” or simply “programs.” 
       FIG. 2  is a diagrammatic illustration of an example computing environment  200 , consistent with embodiments of the present disclosure. In certain embodiments, the environment  200  can include one or more remote devices  202 ,  212  and one or more host devices  222 . Remote devices  202 ,  212  and host device  222  may be distant from each other and communicate over a network  250  in which the host device  222  comprises a central hub from which remote devices  202 ,  212  can establish a communication connection. Alternatively, the host device and remote devices may be configured in any other suitable relationship (e.g., in a peer-to-peer or other relationship). 
     In certain embodiments the network  250  can be implemented by any number of any suitable communications media (e.g., wide area network (WAN), local area network (LAN), Internet, Intranet, etc.). Alternatively, remote devices  202 ,  212  and host devices  222  may be local to each other, and communicate via any appropriate local communication medium (e.g., local area network (LAN), hardwire, wireless link, Intranet, etc.). In certain embodiments, the network  250  can be implemented within a cloud computing environment, or using one or more cloud computing services. Consistent with various embodiments, a cloud computing environment can include a network-based, distributed data processing system that provides one or more cloud computing services. In certain embodiments, a cloud computing environment can include many computers, hundreds or thousands of them, disposed within one or more data centers and configured to share resources over the network. 
     Consistent with various embodiments, host device  222  and remote devices  202 ,  212  may be computer systems preferably equipped with a display or monitor. In certain embodiments, the computer systems may include at least one processor  206 ,  216 ,  226  memories  208 ,  218 ,  228  and/or internal or external network interface or communications devices  204 ,  214 ,  224  (e.g., modem, network cards, etc.), optional input devices (e.g., a keyboard, mouse, or other input device), and other commercially available and custom software (e.g., browser software, communications software, server software, natural language processing software, search engine and/or web crawling software, filter modules for filtering content based upon predefined criteria, etc.). In certain embodiments, the computer systems may include server, desktop, laptop, and hand-held devices. 
     In certain embodiments, remote devices  202 ,  212  may include an origin location  210  and a set of public safety data  220 . The origin location  210  and the set of public safety data  220  may include information about a criminal event and various public safety information which is configured to be communicated to the host device  222  for processing. As described herein, a criminal event response management application  230  of the host device  222  may be configured to utilize the origin location  210  and the set of public safety data  220 . The criminal event response management application  230  may have a set of operations. The set of operations can include a receiving operation  231 , an identifying operation  233 , a computing operation  235 , a determining operation  237 , and a providing operation  239 . 
       FIG. 3  is a flowchart illustrating a method  300  for criminal event response management using a set of public safety data (e.g., COPLINK) according to embodiments. Method  300  may begin at block  301 . In embodiments at block  304 , the operational steps such as the receiving, the identifying, the computing, the determining, and the providing each occur in an automated fashion without user intervention or manual action (e.g., using automated computing machinery, fully machine-driven without manual stimuli). The automated operational steps may be performed by a management engine (e.g., as part of a criminal event response management application). 
     At block  310 , an origin location of a criminal event is received. The criminal event has a set of individuals (e.g., one or more persons of interest, accomplices, potential criminals). Receiving can include detecting, sensing, accepting as an input, or otherwise accepting delivery of the origin location. The origin location can include an address (e.g., geographical, street address), a set of coordinates, or the like. For example, the origin location of a bank robbery may include the address of the bank, a specific Automated Teller Machine (ATM), a particular drive-up window/lane, or the like. The origin location may indicate a most recent spot a vehicle or the set of individuals were spotted (e.g., an eyewitness or video indicates the origin location to be an exit behind the building from drive-up lane number two). 
     At block  330 , a set of candidate target locations for the set of individuals is identified. The set of candidate target locations is based on the origin location and the set of public safety data with respect to the criminal event. The set of candidate target locations can include one or more possible destinations. For example, the set of candidate target locations may include a local hideout for the set of individuals or an exit area. In embodiments at block  331 , the set of candidate target locations (e.g., using a geographic repository) includes at least one of: a set of freeway exits (e.g., nearest five exits), a set of freeway on-ramps within a threshold proximity of the origin location (e.g., with ten miles), a set of city entrances (e.g., neighboring city entryways), a set of city exits (e.g., locations to depart a relatively confined area), a set of rental car facilities, a set of transportation facilities, a set of airports, a set of bus stops, a set of train stops, or the like. 
     In embodiments, the identifying operation can include examining the set of public safety data at block  341 . The set of public safety data may be examined for residence data of a set of persons with a historical record corresponding to the criminal event within a threshold distance of the origin location. Examining can include scanning, inspecting, analyzing, parsing, querying, deciphering, or the like. To illustrate, the set of candidate target locations can include residences of persons with prior criminal records (e.g., historical data in the set of public safety data which indicates the suspected crime-type such as robbery) within a threshold distance (e.g., two miles) of the origin location. The set of candidate target locations can include locations of associated-individuals such as significant-others, friends, colleagues, co-workers, family, or the like. 
     In embodiments, the identifying operation can (further) include selecting a subset of the set of persons which have a physical description that corresponds to a reported physical description from the criminal event at block  342 . Selecting can include choosing, saving a data value, entering an input digit/character, or the like. The physical description may relate to an individual (e.g., directly recorded in the set of public safety data as a subject of an event) or an associated-individual (e.g., indirectly part of the set of public safety data in notes of an event though not a subject individual of the event). For instance, associated-individuals can include individuals which correspond to a physical description (e.g., make/model of vehicle, estimated height/weight of individuals). Associated-individuals may include individuals which correspond to the location/address (e.g., physical description matches that of a sibling of an individual indicated to have a prior criminal record that has the same address). 
     At block  350 , a set of candidate routes is computed. The set of candidate routes may be from the origin location to the set of candidate target locations. The set of candidate routes can be computed using the origin location and the set of candidate target locations (e.g., using public/private roads from a first coordinate/address to a second coordinate/address). Computing can include ascertaining, resolving, formulating, or calculating. For example, various routes (e.g., travel/transportation paths/courses) may be computed from the origin location to one or more (e.g., each) of the candidate target locations (e.g., possible/likely destinations). In embodiments at block  351 , the set of candidate routes includes at least one of: a set of property exits from the origin location (e.g., to indicate an initial direction), a set of routes that uses a turn-propensity weight to indicate a right-hand turn likelihood which exceeds a left-hand turn likelihood (e.g., right-hand turns being more frequent/likely than left-hand turns), a specific route that uses a u-turn weight to indicate a threshold u-turn likelihood which exceeds a specific u-turn likelihood for the specific route (e.g., generally disfavoring/avoiding routes which prefer/require u-turns), a set of road construction factors (e.g., disfavoring routes which may be hindered or cause delays by public works projects), or a batch of routes that uses a road-segment weight to indicate a major road-segment likelihood which exceeds a minor road-segment likelihood (e.g., favor major thoroughfares/streets which both have generally faster typical speeds and more traffic to blend with). For example a variety of such factors may be weighted in compiling the set of candidate routes. 
     At block  370 , a set of predicted locations for the set of individuals and a set of suggested public safety officer positions may be determined. The determination(s) can be made based on a set of relationships of the set of candidate routes. The set of relationships may include, correspond to, derive-from, or arise-out-of various comparisons of routes to find similar or overlapping characteristics, features, or locations (e.g., a number of routes match/overlap by utilizing the same block of a particular street). Direction of traffic flow may or may not be accounted for (e.g., heading east on the same block or heading in either direction on the same block). Determining can include ascertaining, resolving, evaluating, formulating, calculating, comparing, or the like. 
     The set of predicted locations for the set of individuals can include one or more geographical positions having probabilities assigned to each predicted location. When multiple individuals are involved, the predicted locations may be developed for each individual, for the group as a whole, or various subsets. The predicted locations may include likelihoods of the individuals having already arrived at potential destinations. In general, the set of predicted locations will indicate particular spots on the set of candidate routes. Accordingly, overlaps in spots by a plurality of candidate routes may indicate a higher likelihood of the individual(s) having been there, being there, or on their way there. In embodiments, the determining operation includes evaluating a set of temporal factors at block  371 . The set of temporal factors can include at least one of: a quantity of time since the criminal event (e.g., a time duration of how long since the robbery concluded), a set of estimated travel times (e.g., lighter traffic, heavier traffic, construction factors, weather factors), a time of day (e.g., morning traffic patterns, afternoon traffic patterns), or the like. 
     The set of suggested public safety officer positions may include particular locations for units to be deployed to. Such positions may include various types including motorcycle positions, car positions, helicopter positions, blockade/checkpoint positions, unmanned aerial vehicle positions, areas to initiate dog-sniffing techniques, citizen-observer positions or the like. The various types may be weighted based on factors described herein (e.g., with respect to the set of predicted locations for the set of individuals). Generally, suggested public safety officer positions may relate to intersections where multiple candidate routes overlap. An indication of expected direction of travel may be included for use by the public safety officers. For example, the set of suggested public safety officer may indicate to place one police car at a first intersection of two main thoroughfares, an unmanned aerial vehicle to observe two different freeway exits, and call for volunteer citizen-observer to watch a one-way side-street. Other possibilities are contemplated. 
     At block  390 , the set of predicted locations for the set of individuals and the set of suggested public safety officer positions can be provided. Providing can include transmitting, sending, conveying, displaying, presenting, messaging, publishing, notifying, or the like. A management engine may perform the providing operation by interacting with one or more other computing devices (e.g., sending data from the management engine to a smartphone). Data communicated as part of the providing operation may be encrypted such that it is protected during transmission to a set of target computing devices (e.g., in contrast to over the air radio waves such that the set of individuals can less easily ascertain what is being communicated with respect to positioning). 
     In embodiments, the providing operation includes presenting a set of visual indicators (e.g., various text, various shapes, various symbols, various colors, various brightness, various contrast) at block  391 . In various embodiments, presenting the set of visual indicators includes displaying a color-coded heat map (e.g., flashing bright red being a set of most likely locations, spotty faded green being a set of lesser likely locations) at block  392 . In certain embodiments, displaying the color-coded heat map includes modifying the color-coded heat map (e.g., enabling introduction of a time-loop view similar to weather-radar) at block  393 . The color-coded heat map may be modified in a dynamic fashion based on a set of updated information (e.g., modifying the color-coded heat map dynamically in real-time on-the-fly). Such modification may indicate a change in the set of predicted locations for the set of individuals (e.g., indicating a higher likelihood that a destination has been reached as time moves on) and the set of suggested public safety officer positions (e.g., indicating for at least one of the public safety officer positions to change such as having an unmanned aerial vehicle patrol a different set of freeway exits). 
     Method  300  concludes at block  399 . Aspects of method  300  may provide performance or efficiency benefits for criminal event response management using a set of public safety data. For example, aspects of method  300  may include positive impacts on flexibility and responsiveness when public safety entities respond to a criminal event. Altogether, performance or efficiency benefits when managing a criminal event response may occur (e.g., speed, flexibility, responsiveness, resource usage). 
       FIG. 4  is a flowchart illustrating a method  400  for criminal event response management using a set of public safety data (e.g., COPLINK) according to embodiments. Aspects of method  400  may be similar or the same as aspects of method  300 . Aspects of the method  400  may substantially correspond to other embodiments described herein, including  FIGS. 1-5  and the related descriptions. Method  400  may begin at block  401 . 
     At block  410 , an origin location of a criminal event can be received. The criminal event may have a set of individuals. At block  430 , based on the origin location and the set of public safety data with respect to the criminal event a set of candidate target locations for the set of individuals can be identified. At block  450 , using the origin location and the set of candidate target locations, a set of candidate routes—from the origin location to the set of candidate target locations—may be computed. At block  470 , based on a set of relationships of the set of candidate routes, determination(s) may be made with respect to a set of predicted locations for the set of individuals and a set of suggested public safety officer positions. Accordingly, the set of predicted locations for the set of individuals and the set of suggested public safety officer positions may be provided at block  490 . 
     In embodiments, the set of candidate routes may be weighted at block  455 . The set of candidate routes can be weighted based on a mapping technique. The mapping technique may indicate a portion of a plurality of routes which overlap (i.e., an overlapping route). Generally, weighting can include assigning a greater or lesser amount of importance, emphasis, or impact to one or more candidate routes. In embodiments, a heavier weight (e.g., greater relative importance) may be assigned to candidate routes that overlap (e.g., share coordinates, shared path) with other candidate routes. The more candidate routes overlap (e.g., more shared coordinates, longer shared path), the heavier the assigned weight may be. For example, if a first route uses Main Street only between A Avenue and B Avenue (e.g., one block) and a second route uses Main Street between A Avenue and D Avenue (e.g., three blocks), each of the first and second routes may be weighted because of the shared one block (e.g., between A Avenue and B Avenue). In addition, if a third route uses Main Street between A Avenue and F Avenue (e.g., five blocks), both the second and third routes may be weighted heavier than the first route due to a more extensive/longer shared path. 
     In various embodiments, the mapping technique which indicates the overlapping route can include a set of mapping operations. A first set of geographical identifiers of a first route may be parsed, extracted, or deciphered at block  456 . A second set of geographical identifiers of a second route may be parsed, extracted, or deciphered at block  457 . The first and second set of geographical identifiers can be compared at block  458  to indicate a hit count of a common geographical area. For instance, a hit count may be incremented when geographical identifiers match within a threshold (e.g., are identical, are within a 5% radius by distance of a local city block). Based on the comparing, the overlapping route may be ascertained (e.g., existence of the overlapping route, a nature of the overlapping route such as to a form or degree) at block  459 . Ascertainment of the overlapping route can occur or be indicated when a hit count for a given area (e.g., for a particular city block, for a given freeway exit) exceeds a threshold value (e.g., more than one route uses the given freeway exit, more than three routes include a certain side-street). 
     In embodiments, the set of relationships is resolved based on the weighting at block  465 . Resolving can include ascertaining, evaluating, formulating, calculating, or the like. The set of relationships can indicate a likelihood of travel. For example, it may be more likely that the set of individuals travel on overlapping portions of routes which overlap relative to non-overlapping portions of routes or routes which do not overlap with other routes. More highly weighted areas may indicate a usefulness of placing public safety officer positions in such highly weighted areas (or certain types of public safety officers). Lesser weighted areas may indicate a different (e.g., lesser) presence of suggested public safety officer positions (or certain types of public safety officers) in the less weighted areas. 
     In embodiments, the set of relationships of the set of candidate routes includes a set of relationship operations at block  469 . A plurality of single candidate routes of the set of candidate routes may be compared with respect to proximity (e.g., geographic nearness, temporal similarity). Based on the comparing, a set of probabilities for a set of segments of the set of candidate routes can be calculated (e.g., using an arithmetic mean, using a clustering technique). Based on the set of probabilities for the set of segments of the set of candidate routes, the set of relationships may be established (e.g., by weighting probabilities of the set of segments, using other environmental factors such as weather or traffic). 
     In embodiments, determining, based on the set of relationships of the set of candidate routes, the set of predicted locations for the set of individuals and the set of suggested public safety officer positions includes a set of determination operations at block  472 . A set of dynamic traffic data (e.g., real-time roadway/vehicle flow/bottleneck information) may be retrieved (e.g., acquired from public safety officers in various positions, pulled from another source). The set of dynamic traffic data can be analyzed. For instance, analyzing can include examining (e.g., performing an inspection), scanning (e.g., reviewing a sample), evaluating (e.g., generating an appraisal), dissecting (e.g., scrutinizing an attribute), searching (e.g., exploring for a reason/ground/motivation), classifying (e.g., assigning a designation), or categorizing (e.g., organizing by a feature). Data analysis may include a process of inspecting, cleaning, transforming, or modeling data to discover useful information, suggest conclusions, or support decisions. Data analysis can extract information/patterns from a data set and transform/translate it into an understandable structure (e.g., a data report which can be provided/furnished) for further use. Using the analyzing, the set of predicted locations for the set of individuals and the set of suggested public safety officer positions can be formulated, calculated, or ascertained (e.g., based on a pattern which is transformed into position indicators). 
     In embodiments, the set of suggested public safety officer positions may be weighted based on a private location capture preference at block  481 . For instance, it may be preferable to approach or capture the set of individuals at a private residence or hideout rather than in a public space (e.g., for safety reasons). Accordingly, the set of suggested public safety officer positions may use a weighting technique which incorporates a likelihood of bystanders in an area. As such, private locations may be weighted greater than public places (e.g., weighting an individual&#39;s residence greater than a public park or stadium). Accordingly, different types of public safety officers may be indicated to be placed differently (e.g., using unmanned aerial vehicles in spaces with larger numbers of people to monitor the set of individuals while using public safety personnel nearer to the individual&#39;s potential hideout). 
     In certain embodiments, a usage assessment may be generated with respect to the criminal event response management. Use of the criminal event response management may be metered at block  497 . For example, productivity improvements may be measured or speed relative to a benchmark (e.g., historical speed of criminal event responses) can be evaluated, etc. Such factors may correlate to charge-back or cost burdens which can be defined in-advance (e.g., utilizing usage tiers) or scaled with respect to a market-rate. An invoice or bill presenting the usage, rendered services, fee, and other payment terms may be generated based on the metered use at block  498 . The generated invoice may be provided (e.g., displayed in a dialog box, sent or transferred by e-mail, text message, initiated for traditional mail) to the user for notification, acknowledgment, or payment. 
     Method  400  concludes at block  499 . Aspects of method  400  may provide performance or efficiency benefits for criminal event response management using a set of public safety data. For example, aspects of method  400  may include positive impacts on flexibility and responsiveness when public safety entities respond to a criminal event. Altogether, performance or efficiency benefits when managing a criminal event response may occur (e.g., speed, flexibility, responsiveness, resource usage). 
       FIG. 5  shows an example use-case of criminal event response management using a set of public safety data according to embodiments. On map  500 , the star symbols  510  may represent a set of suggested public safety officer positions in a particular area. Location  520  may represent an exit (or entrance) from a first roadway to a second roadway. Thoroughfare  530  may represent a major route. The star symbols indicating suggested public safety officer positions may be placed at various intersections of key thoroughfares or exits. Map  500  illustrates an example use-case for performance or efficiency benefits as described herein related to criminal event response management. 
     In addition to embodiments described above, other embodiments having fewer operational steps, more operational steps, or different operational steps are contemplated. Also, some embodiments may perform some or all of the above operational steps in a different order. The modules are listed and described illustratively according to an embodiment and are not meant to indicate necessity of a particular module or exclusivity of other potential modules (or functions/purposes as applied to a specific module). 
     In the foregoing, reference is made to various embodiments. It should be understood, however, that this disclosure is not limited to the specifically described embodiments. Instead, any combination of the described features and elements, whether related to different embodiments or not, is contemplated to implement and practice this disclosure. Many modifications and variations may be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. Furthermore, although embodiments of this disclosure may achieve advantages over other possible solutions or over the prior art, whether or not a particular advantage is achieved by a given embodiment is not limiting of this disclosure. Thus, the described aspects, features, embodiments, and advantages are merely illustrative and are not considered elements or limitations of the appended claims except where explicitly recited in a claim(s). 
     The present invention may be a system, a method, and/or a computer program product. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention. 
     The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire. 
     Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device. 
     Computer readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like, and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user&#39;s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention. 
     Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions. 
     These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks. 
     The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     Embodiments according to this disclosure may be provided to end-users through a cloud-computing infrastructure. Cloud computing generally refers to the provision of scalable computing resources as a service over a network. More formally, cloud computing may be defined as a computing capability that provides an abstraction between the computing resource and its underlying technical architecture (e.g., servers, storage, networks), enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction. Thus, cloud computing allows a user to access virtual computing resources (e.g., storage, data, applications, and even complete virtualized computing systems) in “the cloud,” without regard for the underlying physical systems (or locations of those systems) used to provide the computing resources. 
     Typically, cloud-computing resources are provided to a user on a pay-per-use basis, where users are charged only for the computing resources actually used (e.g., an amount of storage space used by a user or a number of virtualized systems instantiated by the user). A user can access any of the resources that reside in the cloud at any time, and from anywhere across the Internet. In context of the present disclosure, a user may access applications or related data available in the cloud. For example, the nodes used to create a stream computing application may be virtual machines hosted by a cloud service provider. Doing so allows a user to access this information from any computing system attached to a network connected to the cloud (e.g., the Internet). 
     Embodiments of the present disclosure may also be delivered as part of a service engagement with a client corporation, nonprofit organization, government entity, internal organizational structure, or the like. These embodiments may include configuring a computer system to perform, and deploying software, hardware, and web services that implement, some or all of the methods described herein. These embodiments may also include analyzing the client&#39;s operations, creating recommendations responsive to the analysis, building systems that implement portions of the recommendations, integrating the systems into existing processes and infrastructure, metering use of the systems, allocating expenses to users of the systems, and billing for use of the systems. 
     The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions. 
     While the foregoing is directed to exemplary embodiments, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow. The descriptions of the various embodiments of the present disclosure have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.