Towards a Distributed SMA-based Solution for the Interoperability of Hospital Information Systems for Better Routing of Emergency Ambulances
Keywords:Multi-Agent Systems MASs, interoperability, ACO Ant Colony Optimization, Hospital Information Systems HISs, Distributed Emergency Ambulance DEA
Multi-agent systems MASs have been widely used to interoperate hospital information systems (HISs). The use of MASs for HISs interoperability has become a central solution, especially in the field of emergency medicine. In emergencies, the notion of delay is relative, because responders only have a few minutes to react. This emergency response time has an important role in the event that an accident occurs on the road. Existing procedures for the emergency ambulance (EA) dispatch strategy are based on manual dispatch. In this work, we are introducing a distributed emergency ambulance (DEA) routing system to control emergency latency time, which includes driving route planning to guide emergency vehicles and the allocation of distributed emergency resources (emergency ambulances and hospitals) to reduce the EA response time caused by traffic or the wrong human decision to transport ambulance to the accident site. The allocation of resources (hospitals) is ensured through a recommendation system based on the interoperability of several interconnected HISs using a multi-agent system. The proposed solution takes into consideration dynamic traffic flow information during the day to build dynamic paths for EA. The improved method is based on a distributed architecture to calculate and find the optimal pathway for a set of emergency vehicles based on ACO ant colony optimization techniques. The results of the simulation show that the proposed method can decrease the total travel time of the ambulance to reach the accident position compared to conventional methods that use lights and sirens to warn other vehicles to free up the road for the ambulance or use a traditional approach based on the vision/reflection of the driver to choose in a random way the paths to take. Based on such a solution, ambulance staff will be able to save lives by optimizing the total journey with the minimum travel.
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Copyright (c) 2021 MERYEM FAKHOURI AMR, MOUHCINE ELGAREJ, NEZHA BENMOUSSA, KHALIFA MANSOURI, MOHAMMED QBADOU
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