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Medical Flights, Internet of Things and Predictive Analytics

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The maintenance of medical flights is a critical part of how well they function. The efficiency of maintenance determines how safe medical flights are. Stating this fact is a no-brainer but something that needs to be reiterated. All air ambulance organizations around the globe take maintenance seriously and employ experienced crew members to take care of this aspect. In spite of this, every year we find medical flights crashing and precious lives being lost. What if there can be a mechanism that can detect faults at their initial stages and highlight them before they balloon into life-threatening events or transform into expensive repairs? Internet of things and predictive analytics, in combination, can solve this problem.

Internet of Things for Medical Flights

Internet of things can seem like a concept from some science fiction movie but, in reality, the concept is simple. Internet of things are devices that can gather data from any equipment and transmit it to a centralized service wirelessly. They usually contain a SIM card just like your mobile phones that allow them to communicate with different servers. Let’s consider an over-simplified example of how it works. Take for instance that an IoT device is connected to the tires of fixed-wing medical flights. It would constantly monitor the air pressure of the wheels and when it goes down, the IoT device would instantly communicate the same to a centralized server. The maintenance staff can then ensure that the tire pressure is maintained.

The Role of Predictive Analytics

Several IoT devices can be fit into various components of medical flights. They would constantly monitor the workings of each of such devices and transmit the data to a dashboard. This data is very valuable. Predictive analytics is a branch of computer engineering that makes sense of all this data – through various permutations and combinations – and arrives at a prediction. For instance, if the engine vibration is within a certain frequency, the life of the engine would be X number of years; however, if it exceeds that frequency, the life would be reduced by Y number of years. Predictive analytics takes into consideration historic data and results and creates a bridge between them.

The technology has the potential to transform the way medical flights are maintained today.

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