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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM25339

Ambulance App: Recommendation of Hospitals using Machine Learning Techniques

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM25339

Volume:

7 |

8 |

Aug 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

TGR

Thallapalli Ganesh Reddy

VSS

Vaddireddy Sai Swetha

VSR

Vaddireddy Sivananda Reddy

VSPR

Vaddireddy Sai Pranadeesh Reddy

VJR

Vaddireddy Jaswanth Reddy

TS

Thallapalli Sindhuja

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Abstract

The aim of this project is to develop an ambulance booking app using ML model that will allow users to quickly and easily request emergency medical assistance and details of the hospital nearby. The app will be made using Android Studios which is used to develop the UI (in XML) and functioning of the app(in Java). Iterative Model which is basically used to redesign and retest the app until the final application is made according to the objectives. The app will provide a simple and efficient way for patients to contact ambulance services during an emergency, ensuring that they receive timely and appropriate medical care. The proposed app will be designed to address the challenges of accessing emergency medical services in India. The ultimate goal of this project is to improve emergency medical services in India by providing quick access to medical assistance. The app will include features such as GPS tracking, real-time updates on ambulance location, and emergency contact information for users to quickly reach out to family and friends.

KEYWORDS

ML FireBase AndroidStudio

Cite This Article

Thallapalli Ganesh Reddy, Vaddireddy Sai Swetha, Vaddireddy Sivananda Reddy, Vaddireddy Sai Pranadeesh Reddy, Vaddireddy Jaswanth Reddy, Thallapalli Sindhuja, "Ambulance App: Recommendation of Hospitals using Machine Learning Techniques," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 8, Aug 2023.

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Publication Date

8/20/2023

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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