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Ambulance Response Optimization

Sarthak Khanna1

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-6 , Page no. 281-286, Jun-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i6.281286

Online published on Jun 30, 2019

Copyright © Sarthak Khanna . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Sarthak Khanna, “Ambulance Response Optimization,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.281-286, 2019.

MLA Style Citation: Sarthak Khanna "Ambulance Response Optimization." International Journal of Computer Sciences and Engineering 7.6 (2019): 281-286.

APA Style Citation: Sarthak Khanna, (2019). Ambulance Response Optimization. International Journal of Computer Sciences and Engineering, 7(6), 281-286.

BibTex Style Citation:
@article{Khanna_2019,
author = {Sarthak Khanna},
title = {Ambulance Response Optimization},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2019},
volume = {7},
Issue = {6},
month = {6},
year = {2019},
issn = {2347-2693},
pages = {281-286},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4543},
doi = {https://doi.org/10.26438/ijcse/v7i6.281286}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i6.281286}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4543
TI - Ambulance Response Optimization
T2 - International Journal of Computer Sciences and Engineering
AU - Sarthak Khanna
PY - 2019
DA - 2019/06/30
PB - IJCSE, Indore, INDIA
SP - 281-286
IS - 6
VL - 7
SN - 2347-2693
ER -

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Abstract

We live in a country where the incidents of ambulances not reaching on time are indicative enough of the dismal state of transportation for patients in need of emergency care across the country. Delhi, a city of 22 million people, has only 152 state-run ambulances. More than 20 percent of patients needing emergency treatment have died on their way to the hospital because of delays due to traffic jams. in Delhi, an ambulance takes an average of 27 minutes to reach the site. Response time can even extend into hours. Seeing the current scenario of traffic, time taken is only going to increase. And yet, no steps are being taken to improve the situation. Measures of optimizing ambulance response time prove to be widely unsuccessful due to the lack of a targeted approach. This results in sub-optimal allocation of already overstretched healthcare resources. In 2017 alone, there were more than 8,000 road accidents in Delhi. Ironically enough, about 3,000 accidents led to deaths due to ambulances not reaching on time as they were stuck in Delhi’s traffic. By virtue of the factors discussed above, there arises a need for a scientific approach to optimizing the ambulance response time.

Key-Words / Index Term

Mathematical model, response optimization, speed-density equation. algorithmic paradigms

References

[1] K. Saha, S. Rathee “Agent- Based Traffic Simulator for Autonomous Vehicles” International Journal of Scientific Research in Computer Science and Engineering Vol.5, Issue.2, pp.42-45, 2017
[2] K. Saha, S. Rathee “Agent- Based Traffic Simulator for Autonomous Vehicles” International Journal of Scientific Research in Computer Science and Engineering Vol.5, Issue.2, pp.42-45, 2017