Assessment of Advanced GIS
Tools for E-911 Services
Cole Kelleher
Benjamin Post
CSCI 5980
Outline
 Motivation
 Goals
 Assumptions
 Existing GIS Applications
 Dijkstra’s Algorithm
 Fortune’s Algorithm
 Solution
 Validity of Goals
 Issues and Limitations
Motivation
 Proliferation of location aware devices
 Increase in GIS analysis
 Large potential for application of new GIS services and
workflows for emergency responders
 Improved response time
 Efficient resource management
 Post emergency response analysis
Goals
 Identify potential value added GIS functionality for
emergency response
 Identify infrastructure to support this functionality
 Verify validity of GIS functionality
 Does it already exist?
 Would it be useful?
Assumptions
 Emergency calls collected via automated and manual
methods
 Call vs. triggered alarm
 Formal emergency types for multi-entity (Fire Dept., Police
Dept., etc.) use.
 Use of location aware devices by emergency response
personnel
 Smart-phones, GPS enabled laptops and receivers
Existing GIS Applications
 Crime Stat
 Post crime analysis tool
 Automatic Vehicle Location (AVL)
 Tracks emergency vehicles
 CAD / GIS
 ESRI, AutoCAD
 Display EMR locations
 Display critical infrastructure
Dijkstra’s Algorithm
Overview
 Well known search algorithm within CSci
 Finds the shortest path between two points
 Can be run on a variety of inputs
 Graphs – both pure and weighted
 Rasters
 Speed dependent upon heap
 O(V²) to O(E + V log V)
Dijkstra’s Modification
 Graphs are weighted by Time
 Road Network: road speed/distance = time
 Algorithm is modified to allow the search to run until a
specified time value has been reached along each path.
 Once the search has reached its maxima of allowed travel
time across all nodes, we receive that heap of all nodes which
meet the time constraint
 Useful for determining time based suspect search perimeter
and/or optimal route
Results
Results
Fortune’s Algorithm
Overview
 Maintain Voronoi polygons for emergency personnel to query
for optimal response
 Functional for nearest entity/response team determination
 Three separate sets of polygons
 Fire and EMTs, which are static
 Police, which would are dynamic
 Operates in O(n log n) time
 n = number of entities
Algorithm
 Assumes point set is sorted
 Runs a sweep line across the set
 Once a point is reached, calculates a parabola which forms
the trailing beach line
 At the intersection of 3 beach lines, creates a vertex for one
of the set’s polygons
Results
Results
Results
Interview with Wayne Betcher
 Dispatcher, Goodhue County Sheriff
 Committee, Sheriff’s Assoc NG9-1-1
 Future Technology
 911 via text, VoIP
 Send/Receive video
 Social Media
 Use of collected data
 Spatio-Temporal analysis of patrol routes
Solution
Validity of Goals
 Use of state-of-the-art technologies to support efficient
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


emergency response
Increased response time and delivery of spatial data relevent
to the emergency
Able to meet the needs of multiple emergency entities
Recording of spatial location data for post emergency
response assessment and improvement
Compatible with future crime reporting methods (text
messages, social media, etc.)
Issues and Limitations
 Difficult to Implement and test
 Real-world testing, infrastructure, input specifications, and
delivery method will need to be addressed
 Modified Dijkstra’s Algorithm
 Unknown at this time, would likely be more useful once
NG911 services are enabled
 Cordons: Manhunts and Amber Alerts
 Fortune’s Algorithm
 Difficult to assess, nature of patrol officer might prohibit closest
officer from responding
 Expressed need for polygons representing E911 areas, Fortune’s
might not be appropriate
Sources
 Dijkstra’s Algorithm
 http://en.wikipedia.org/wiki/Dijkstra's_algorithm
 Fortune’s Algorithm
 http://en.wikipedia.org/wiki/Fortune%27s_algorithm
 Automatic Vehicle Location
 http://en.wikipedia.org/wiki/Automatic_vehicle_locatio
n
 Next Generation 911
 http://en.wikipedia.org/wiki/Next_generation_911