EMS Portal

• April 27th, 2015
• in

About

The Alabama Emergency Medical Services and Trauma data has been configured to display in the dashboard shown below.

Currently there is only one database on this portal but other databases can be added to the portal.

Features

• Displays Summary Data
• Performs Dynamic Analysis
• Drill Down tab for specific filtering of data
• Applies Filters to Data
• Does Side-By-Side Data Comparisons
• Performs Crosstabs of Two Variables
• Fast – Uses CARE Processing Engine
• Does Timeline Analysis
• Data sources updated regularly for timely data
• Exports data, charts and graphs to Excel or as an image

ADVANCE

• March 19th, 2014
• in

About

ADVANCE is a powerful web portal dashboard that allows users to analyze and visualize electronic data in a variety of ways. Any database can be configured to display in an ADVANCE dashboard.

Currently the eCite, eCrash, and eWeight databases have been put into ADVANCE. Other databases will be added.

ADVANCE was developed through sponsorship from the Alabama Criminal Justice Information Center and the Alabama Office of Highway Safety. ADVANCE is individually password protected for use by law enforcement personnel.

Features

• Numerous source databases
• Displays summary data
• Performs dynamic analysis
• Searches records
• Applies filters to data
• Generates maps based on GIS
• Does side-by-side data comparisons
• Drill down tab for specific filtering of data
• Uses rapid CARE Processing Engine
• Can view/print eCite tickets and eCrash reports
• Data sources are updated nightly for timely data
• CARE Online Analysis tab for frequency, crosstabs and more
• Report tab for routine reports
• Exports data, charts and graphs to Excel or as an image

SAFETY

• March 19th, 2014
• in

About

SAFETY is a powerful web portal dashboard that allows users to analyze and visualize electronic data in a variety of ways.

This dashboard is designed specifically for traffic safety professionals. It contains crash data including location information and is individually password protected for use by official traffic safety personnel.

Features

• Displays Summary Data
• Performs Dynamic Analysis
• Applies Filters to Data
• Searches Records
• Crash Report Viewer
• Generates GIS maps
• Exports data, charts & graphs to Excel or image
• Report Scheduler – weekly, monthly, quarterly
• Reporting tools – get report emailed to you
• Batch Report Downloads
• Extremely Fast – Uses CARE Processing Engine
• Data sources updated nightly for very timely data

Download the SAFETY flyer

CARE

• March 19th, 2014
• in

An Analysis of Teen-Age Driver Crashes 2005-2008

• January 10th, 2010
• in

This study was conducted at the request of an advocate group that wanted information to assist them in developing public information and education countermeasuers for teen-age drivers. While most past CAPS studies of youth-involved drivers were limited to 16-20 year olds, the advocate group was also interested in 15 year olds, and they were not interested in 20 year olds since their projects were oriented around teen drivers. Several studies were conducted, including CARE IMPACT studies that compared 15, 16-19 and 15-19 year old causal drivers with causal drivers in the older age group.

A Relation Context Oriented Approach to Identify Strong Ties in Social Networks

• October 1st, 2009
• in

Social network graphs have been found to be an extremely effective tool in the identification of potential perpetrators of criminal activity. These graphs can grow extremely large, as illustrated by an example within this paper that contained over 4.9 million nodes and over 211 million edges. Obviously some reduction of these graphs is essential to their being useful. Further, considerable “noise” (false positive relationships) are generated when the graphs are totally comprehensive. This research transformed the original social network into a relational context-oriented edge-dual graph. This was done by evaluating the quality of the connectivity for each edge to obtain a metric to this effect for each edge. By retaining only the strongest edges the overall graph becomes more reliable and more useful in practice.

HIT: A GIS-Based Hotspot Identification Taxonomy

• June 1st, 2009
• in

The authors have developed a Hotspot Identification Taxonomy (HIT) that organizes the various methods for viewing hotspots. Basically they are defined as follow:

• First order – high crash frequency road segments possibly filtered for specific event(s);
• Second order – road segments defined as those that have high event counts specifically related to a countermeasure under consideration (e.g., selective enforcement for the speed event);
• Third order – segments having a high frequency of countermeasure-related events and for which the countermeasure was historically effective.

Effective use of the HIT model required four interrelated activities: data-collection, linear hotspot identification, presentation and assessment.

Analysis of the Wet vs. Dry Counties within Alabama

• January 31st, 2009
• in

CARE IMPACT analyses were performed to compare 13 dry counties with 13 wet counties over their various crash characteristics for a recent five-year (2003-2007) time period. The results fall into two logical categories: those that compare the demographics of the counties and those that compare the crash characteristics with regard to alcohol. A few of the nearly 200 attribute comparisons are presented in this report in order to guide the future direction of the research project.

Alcohol Age Crash Analysis – Projections of the Effect of Lowering the Legal Drinking Age in Alabama

• August 16th, 2008
• in

This report, and the Op Ed that follows it, is in response to a number of prominent college presidents who have recently come out in favor of lowering the drinking age to 18 years. The goal of the report is to project how many additional fatalities will be caused in Alabama should the law be change in Alabama.

Using an Edge-dual Graph and k-connectivity to Identify Strong Connections in Social Networks

• March 1st, 2008
• in

The goal of this paper is to use edge-dual graph transformation techniques to improve the accuracy of social network analysis (SNA). SNA is used in law enforcement to determine if relationships exist among potential suspects, and to identify just what those relationships might be. Relationships can be family, friends, past associates, cell mates and even prison enemies. The paper presented results that showed that this transformation had a very high potential for increasing the accuracy of relationship search routines.