Improved immune algorithm for sudden cardiac death first aid drones site selection

Out-of-hospital cardiac arrest (OHCA) requires a fast emergency response, while traditional emergency takes too long to meet the demand. Combining a drone with a defibrillator can provide rapid resuscitation of OHCA patients. The aims are to improve survival in OHCA and to minimize the total system cost.

We developed an integer planning model for sudden cardiac death (SCD) first aid drone siting based on a set covering model with the stability of the siting system as the main constraint, considering the rescue time and total system cost. Using 300 points to simulate potential cardiac arrest locations in the main municipal district of Tianjin, China, the SCD first aid drone siting points are solved using an improved immune algorithm.

Based on the actual parameters set by the SCD first aid drone, 25 siting points were solved in the main municipal district of Tianjin, China. These 25 sites were able to cover 300 simulated potential demand points. The average rescue time was 127.18 s and the maximum rescue time was 296.99 s. The total system cost was 136,824.46 Yuan. Comparing the pre- and post-algorithm solutions, the system stability was improved by 42.22%, and the maximum number of siting points corresponding to demand points was reduced by 29.41% and the minimum number was increased by 16.86%, which is closer to the average.

We propose the SCD emergency system and use the improved immune algorithm for example solving. Comparing the solution results using the pre- and post-improvement algorithms, the cost solved by the post-improvement algorithm is less and the system is more stable.