THE INTELLIGENCE AMBULANCE: BRIDGING AI AND HUMAN INTERACTION TECHNOLOGIES
DOI:
https://doi.org/10.46243/jst.2023.v8.i12.pp61-77Keywords:
Ambulance, Human, Artificial Intelligence, Emergency Medical Services.Abstract
The field of emergency medical services (EMS) has undergone significant advancements over the years, with a focus on improving response times, patient care, and overall outcomes. The integration of artificial intelligence (AI) and human interaction technologies into ambulances represents a transformative approach to enhance emergency medical care. The background encompasses the evolution of EMS, the rise of AI in healthcare, and the potential for synergies between technology and human interactions in emergency situations. Historically, ambulances have primarily been vehicles equipped with basic life support equipment and staffed by paramedics and emergency medical technicians to provide initial care during transportation to a medical facility. Communication with hospitals and the processing of patient information be manual and time-consuming. The traditional system is lack of real-time data analysis capabilities and decision support tools that AI can offer in emergency situations. The problem at hand is optimizing emergency medical responses and care through the integration of AI and human interaction technologies within ambulances. This involves addressing challenges such as quick and accurate diagnosis, communication between emergency responders and healthcare facilities, and the provision of real-time medical information to enhance decision-making. The goal is to create a seamless, intelligent, and responsive system that improves patient outcomes during critical moments. The need for the intelligence ambulance arises from the recognition that leveraging AI and human interaction technologies can significantly enhance the efficiency and effectiveness of emergency medical services. In critical situations, quick and accurate decision-making is crucial, and the integration of intelligent systems can provide valuable support to healthcare professionals. This approach can also improve communication, data sharing, and coordination between ambulances, hospitals, and other healthcare entities.
References
Akash Bansode, Sanket Thakare, Sarthak Pawar, Subodh Wavhal and D.S. Rakshe, Smart Ambulance Management Application Using Cloud, IJARIIE-ISSN(O)-2395-4396, Vol-8, Issue-3 2022
Divya Ganesh, Gayathri Seshadri, Sumathi Sokkanarayanan, Panjavarnam Bose, Sharanya Rajan and Mithileysh Sathiyanarayanan, “Automatic Health Machine for COVID-19 and Other Emergencies,” in IEEE-2021
Ms. Aisha Meethian, Althaf B.K., Athinan Saeed, Ligin Abraham, Mohammed Samran, “IOT Based Traffic Control System with Patient Health Monitoring For Ambulance”, ISSN:2395- 5252, Volume 4, Issue 8, August 2022
Himadri Nath Saha, Neha Firdaush Raun, Maitrayee Saha, “Monitoring Patient’s Health with Smart Ambulance system using Internet of Things (IOTs)”, IEEE 2017
Timothy Malche, Sumegh Tharewal, Pradeep Kumar Tiwari and Mohammad Aman Ullah, “Artificial Intelligence of Things- (AIoT) Based Patient Activity Tracking System for Remote Patient Monitoring”, 2022
Erik Alonso, Unai Irusta, Elisabete Aramendi and Mohamud R. Daya, “A Machine Learning Framework for Pulse Detection During Out-of-Hospital Cardiac Arrest”, 2020
Yuanyuan Pan, Minghuan Fu, Biao Cheng, Xuefei Tao and Jing Guo, “Enhanced Deep Learning Assisted Convolutional Neural Network for Heart Disease Prediction on the Internet of Medical Things Platform”, 2020
M. Sheetal Singh, Prakash Choudhary, “Stroke Prediction using Artificial Intelligence”, 2017
Santhana Krishnan J. and Geetha S., “Prediction of Heart Disease using Machine Learning Algorithms” ICIICT, 2019
Akash Bansode, Sanket Thakare, Sarthak Pawar, Subodh Wavhal and D.S. Rakshe, “Smart Ambulance Management Application Using Cloud”, IJARIIE, ISSN(O) - 2395- 4396, Vol-8 Issue-3, 2022
Aiswarya G, Anjali U K, Amal Mathew, Alen Benny, Jamshid C T, Prof. Tinimol Andrews, “Android based Remote Health Monitoring System”, IJERT, Volume 9, Issue 13,2021
M. Dhinakaran, Khongdet Phasinam, Joel Alanya Beltran, Kingshuk Srivastava, D. Vijendra Babu, and Sitesh Kumar Singh, A System of Remote Patients’ Monitoring and Alerting Using the Machine Learning Technique, Journal of Food Quality, 8 February 2022
Sakshi Dhuria, Mohd. Yusuf Khan, Rupal Mishra, Shivam Narsingh, Satya Prakash Singh, “Ambulance Tracking with Patient Health Monitoring by the use of GPS and GSM”,2021
Gowthami.P, “an Android based Patient monitoring System”, vol. 3, IIJIRAE, 2016
P.Ponsudha,Haritha.K,Gayathri.D,HarshithaShree.P,S wetha.C, “Efficient ambulance service with real time ambulance monitoring syatem” International Journal of Applied Engineering Research, 2019
M Sanjay Karanth, Bindhu kumar K T, Gururaj Reddy J, Manoj K, Veda. B, “Smart ambulance with patient monitoring”, 2015
Mery Subito1, Alamsyah, and Ardi Amir, “Web-Based Wireless Monitoring System on Patient’s Vital Sign”, 2019
Tia Gao, Logan K. Hauenstein, Alex Alm, David Crawford, Cassius K. Sims, Azmat Husain, and David M, “Vital Signs Monitoring and Patient Tracking Over a Wireless Network”, 2016
Amogh Powar, Seema Shilvant, Varsha Pawar, Pratiksha Shetgaonkar, Shailendra Aswale, “Data Mining & Artificial Intelligence Techniques for Prediction of Heart attack”, 2019
