Method and apparatus for implementing an object oriented...

Data processing: database and file management or data structures – Database design – Data structure types

Reexamination Certificate

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Details

C707S793000, C707S793000, C707S793000, C707S793000

Reexamination Certificate

active

06408304

ABSTRACT:

TECHNICAL FIELD
The present invention relates to object oriented computer programming. More particularly the present invention relates to a method and apparatus for implementing object oriented programming characteristics in a law enforcement computer system.
DESCRIPTION OF RELATED ART
Currently police patrol vehicles contain many types of devices for normal operation such as radios, scanners, lights, sirens, onboard video, computers and speed measurement devices. Each type of the above mentioned device types may be performed by a variety of contrasting mechanisms that serve some generic police function. Speed measurement device types, for instance include RADAR devices (such as the Genesis series of handheld stationary RADAR guns available from Decatur Electronics, Inc. 715 Bright Street Decatur, Ill. 62522) for radar speed tracking. Alternatively or in combination with a RADAR device a police cruiser may be equipped with a LIDAR device (Light Distance And Ranging such as Stalker Lidar a trademark of and available from Ingram Technologies of West Valley City, Utah) for laser speed tracking. Still in addition a cruiser may also carrier a VASCAR unit (Visual Average Speed Computer And Recorder a trademark of and available from Signal Systems (Pty) Limited P.O.Box 58296 Newville, 2114 South Africa) for computerized speed tracking or VASCAR V PLUS (Visual Average Speed Computer And Recorder Video Plus also a trademark of and available from Signal Systems (Pty) Limited) for computerized speed tracking and video recording. All of the these devices take up space in the patrol cruiser, have different interfaces for the patrol officer to learn and utilize, and more importantly, are not integrated to share information with each other or a central dispatcher.
The problem is best illustrated by an example. A typical traffic stop, for example traveling above the posted speed limit (speeding), is usually initiated by an officer confirming that a vehicle is speeding. Some onboard speed measurement device such as RADAR, LIDAR or VASCAR usually provides the conformation. The speed data that is indicated by the speed-measuring device is valuable evidence that might be used by against the suspect at trial. A stop of the vehicle ensues and the officer performs an information check on the suspect and vehicle. Information obtained from the suspect is called in to a central police dispatch. The officer may communicate with the dispatcher through a variety of means such as a radio or data link. Text and image data may be passed to and from the dispatcher through the data link. During the stop the suspect and suspect's vehicle may be video taped. After consultation with the dispatcher the officer issues a citation or warning to the suspect or alternatively may perform an arrest.
At the conclusion of the traffic stop the only record of the events that transpired prior, during, and after the traffic stop are usually in the form of the citation itself. Should the suspect choose to contest the citation, the officer usually appears in court with a copy of the citation, some hastily scribbled notes about the incident and calibration documentation for the speed measurement device. Any other potential evidence, such as a date-stamped output from the speed measurement device, video of the suspect and communications between the officer and dispatcher, are not produced at trial simply because of the amount of trouble necessary to gather the miscellaneous data from disparate sources. In more serious offenses the jurisdiction will gather the data form disparate sources, but at great expense.
Even though data is available from a variety of sources, it is never integrated into a coherent package usable for other law enforcement functions. Normally, particular types of data are gathered and if a suitable database exists for the data, it is entered in the database. No correlation between dissimilar data types is established in the prior art data gathering systems. With reference to the traffic stop example, driver's license databases may not contain any reference to criminal activity unless that activity directly related to the operation of a motor vehicle and therefore is not available to the officer at the scene. Criminal wants and warrants are often times never entered in a driver's history maintained by an agency in charge of motor vehicles and driver licensing. Therefore criminal information is not normally available to an officer making a routine traffic stop unless the officer specifically requests a criminal information check. Ordinarily the officer calls in the tag and driver license numbers for the vehicle and driver to a centralized dispatcher. The dispatcher then “runs” the numbers in a motor vehicle database for vehicle history information and driver information. Occasionally, the suspect's name and description is checked for “wants” and “warrants” in a national, and state database, however, in minor traffic stops this check is skipped due to the time required for a response. The dispatcher then returns only the requested information. Many times an officer cites person for a minor traffic offense only to find out that the suspect is wanted for a far more serious crime.
Similarly, information related to a recent crime or crime in progress is only available to the officer through the dispatcher. Many times the dispatcher acts as an information filter to the officer because the dispatcher is unaware of the crime or because the dispatcher fails to connect a suspect in a minor traffic violation with another crime. The officer is the best judge as to which information might be pertinent to the traffic stop and yet that officer may never receive important information because no integrated system for sharing information exists in the prior art.
Major crimes are another example of a need for sharing information. Nationally there has been a decrease in the occurrence of serious crimes each year from 1993 to 1999 (as reported by the Federal Bureau of Investigation in its Uniform Crime Report issued Nov. 21, 1999 for the first half of 1999). Even though there is a decrease in the total number of serious crimes being committed in the United States, there is no evidence of a corresponding increase in the percentage of solved crimes. The success rate for solving serious crimes is dismal. The USA Today reports that in November 1999 the success rate for murder continues to hover under 70%. Criminals who commit other serious crimes fare even better with law enforcement. For example, the solution rate for larceny is less than 40%, while a car thief has less than a one in five chance of being prosecuted for an individual act. One reason for the lack of success is that no automated system exists for connecting and sharing related information.
When investigating a major crime, law enforcement officers generate information or “leads” that connect a particular suspect to a crime. Generating leads that are related to a particular crime is a tedious undertaking. A lead has at least one connection to some aspect of the crime; although connecting that lead to a person may be more difficult to establish. Two or more leads may be combined with one another, thus strengthening their connections to the crime. More relevant leads may have numerous connections to the crime and may be combined with numerous other leads. The most probable suspects are those who are connected with more leads.
With respect to the crime of homicide, leads that connect a person with the crime include information relating to a suspect's means, motive, relationship with the deceased and opportunity for committing the crime. Information from a neighbor that a husband is unhappy is information that supports motive. Calls placed from the decease's residence to 911 might also indicate that a husband is unhappy and be combined with the neighbor's information in order to strengthen the motive. Thus the husband is a suspect with a probable motive for committing the crime. An unhappy husband has more connections to the crime and deceas

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