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System and method for a IBM IoT driven cognitive search for ambulance vehicles

IP.com Disclosure Number: IPCOM000248842D
Publication Date: 2017-Jan-17
Document File: 4 page(s) / 41K

Publishing Venue

The IP.com Prior Art Database

Abstract

This article discloses a system and method that can significantly decreases the time it takes from starting first aid until an ambulance vehicle arrives at the location of the emergency. By using cognitive IBM Watson and IBM IoT technology typical problems within the alerting procedure are solved.

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System and method for a IBM IoT driven cognitive search for ambulance vehicles

Please note: Used abbreviations (Defined standard from American Heart Association):

AED: Automated External Defibrillator

CPR: Cardio Pulmonary Resuscitation

SDC: Sudden Cardiac Death, cardiopulmonary circuit stop

ACLS: Advanced Cardiac Life Support

Background

The number of people who are dying on a cardiopulmonary circuit stop in Germany is about

100.000 to 200.000 per year. The use of an AED's (Automated External Defibrillators) has a

significant impact on the survival rate. As a numerous portion of this urgent life-threatening

situation happen in public areas AED's were installed at public places like Airports, Railway

Stations or crossroads. Typically AED's are stand-alone systems without connection to rescue

service provider like paramedics or rescue centers of hospitals.

The success rate of a CPR (Cardio Pulmonary Resuscitation) heavily depends on multiple

factors:

the time needed between the SDC (Sudden Cardiac Death, cardiopulmonary circuit 

stop) and start of the CPR

the quality of the first aid performed from the first person who finds the sick person

the readiness to use an available AED

the time until professional help arrives and takes action

and other factors like age of the sick person, preliminary sickness, temperature.

Improving the overlap possibilities between the Basic life support (first aid) and the

Advanced Cardiac Life Support (ACLS) will therefore have a positive effect on the success

rate. Also a quick automatic emergency call will open the possibility to do first aid in parallel

to informing the rescue chain and getting additional advice.

Problem solved

This article describes a system and method that can significantly decreases the time it takes

from starting the first aid until an ambulance vehicle arrives at the location of the emergency.

By using cognitive IBM Watson and IBM IoT technology the method described solves the

problems that:

The first aid person is not familiar with the local rescue chain (e.g. refugees) and 

potentially doesn't take the right actions (e.g. call paramedics)

The rescue center operator potentially doesn't alarm the optimal next available 

ambulance

The paramedics potentially get the wrong information about the location of the 

emergency

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Main claim:

The novel system and method Efficient Ambulance Vehicle Allocation (EAVA) includes an

improved AED that connects to IBM Watson data sets to find the next available ambulance

vehicle. The selection of the ambulance is optimized based on the collected location

information of the emergency location, weather data and street traffic data. Furthermore it

proposes the vehicle for the emergency action and send appropriate locations information to

the vehicle and establishes a call between AED and ambulance vehicle to allow direct

communication between first aid person and paramedics. This was the paramedics can

already propose actions to the first aid person at...