Abstract:
This article presents a visual analytics approach to explore hidden patterns in
Rescue 1122 Emergency vehicles in Lahore, the capital city of Punjab, the largest
Province of Pakistan. These emergency vehicles are categorized into fire, rescue
and ambulance services. Depending on the caller’s requirement, they serve the respective
category accordingly. All of these vehicles are equipped with GPS tracker.
The data obtained from these vehicles generate spatio-temporal sequences. These
sequences also known as trajectories which form the core component of moving
object analysis. The aim of this study is to assist government officials for efficient
allocation of emergency vehicles. Currently the Rescue 1122 department works on
a manual allocation that introduce some human lag as well as limitation in processing
time and execution of the whole drill. The results show some interesting
patterns and highlight the areas where there is a need to replan the allocation.
Several visualization techniques are applied in this research to get insight into
potential areas. Another portion of the research shows the involvement of caller
data. Time stamps and nature of calls received by Rescue 1122 are mapped over
time to identify prominent features. Visual analytics presents itself as a viable tool
for analysis of data that generically appears less fruitful. The results are useful for
efficient resource planning by the stakeholders.
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