Our Proposal of the System Architecture
Gokul Krishnaa Devaraju
Electrical & Computer Engineering
Carnegie Mellon University
Pittsburgh, PA
gokulk@andrew.cmu.edu
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Chandirasekarendiran Anandan
Electrical & Computer Engineering
Carnegie Mellon University
Pittsburgh, PA
canandan@andrew.cmu.edu
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Jithin Reddy Yaratapalli
Electrical & Computer Engineering
Carnegie Mellon University
Pittsburgh, PA
jyara@andrew.cmu.edu
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Traffic Assisted System for Emergency Medical Services
In the Unites States, stats claim that, over a 20-year period, approximately 4500 accidents occur every year due to ambulances during a medical emergency transportation. However, this can be avoided by efficiently laying a traffic assisted path for the ambulance. In this paper, we propose a system using Wireless Sensor Networks built on the FireFly platform, that can be used by the ambulance service to efficiently and safely transport the patient to the hospital avoiding any accidents. It is also aimed at navigating and traversing the shortest available path to the hospital, at the same time reporting patient status to the hospital, so that attendants at hospitals are equipped and ready to receive the patient.
TASEMS Demo and Working
Case 1: This video shows how TASEMS functions. The app written for TASEMS is used to input the location of the patient as well as the injury sustained by the emergency medical services representative once he reaches the location of accident/injury. Then the Djikstra's algorithm written in the server uses the location of the patient and information of all the nodes at the traffic locations to compute the shortest path. Only those nodes along the shortest path are excited and these nodes are indicated by the blue LED. Once the root node or the last node i.e. the node where the ambulance is loading the patient is excited, it starts sampling for the ambulance presence. Once the ambulance is detected, it sends the response to its parent node to start sampling for the ambulance. This is done all the way to the hospital, therefore alerting the civilian traffic about the speeding incoming ambulance. So, its always only one node trying to detect the ambulance to avoid false detection.
Case 2: We have considered a corner case where there might be a police vehicle who might take the ambulance's path even before the ambulance starts. We have assumed in this case where the cop will eventually move out of the prescribed path to his actual path. So, there will always be one node where neither the ambulance nor the police vehicle arrives for some time. Using this fact, we have placed a timeout for every node i.e. if there is no ambulance detected at any node beyond 5 seconds, all the nodes from the timeout node to the leaf node are excited and all start sampling at the same time to determine where the ambulance is at that moment. Once the ambulance is detected at some intermediate node (between timeout node and the root node), all the nodes from the intermediate node to the root node are flushed and turned off, while the nodes till the intermediate node are now excited like in case 1 in a single hop fashion as the ambulance moves towards the hospital.