HerzKISO – Heart-safe cities through AI-based defibrillator location optimization

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Within the EU, nearly half a million people die of sudden cardiac death every year. The rapid and targeted use of AEDs (automated external defibrillators) is an effective means of significantly increasing the chances of survival. For this reason, the widespread distribution, easy location and public accessibility of defibrillators is essential.

Against this background, the research project »HerzKiSO« is developing a novel, transferable planning concept that can be implemented in other areas: imputation methods based on publicly available sources create the data basis on which the optimal locations of AEDS are determined by mathematical optimization. The goal is to ensure an unbiased and area-wide availability of defibrillators in order to give as many citizens as possible access to a life-saving device and thus create a technical basis to make German cities heart safe.

Ensure widespread availability of defibrillators

Sudden cardiac death has a fatality rate of approximately 90%. Fast help in the first minutes and especially the use of AEDs by first responders contributes significantly to saving lives. However, it is essential that an emergency contact person can direct a first responder to a functioning AED within close range of the emergency scene. Currently, however, there are too few AEDs installed in many areas to ensure widespread availability of AEDs. Therefore, the HerzKISO research project is developing a novel method for optimized AED location planning to determine, on the one hand, how many AEDS are needed in the urban area or in the municipality as a whole to achieve appropriate coverage and, on the other hand, to determine their optimal locations, ensuring that they are publicly accessible, can be found without prior knowledge, and as fairly and evenly distributed as possible.

Schematic representation of the coverage by AEDs
© CardiLink
Schematic representation of the coverage by AEDs

From the current state to the optimal scenario

The locations of previously installed AEDs are determined and analyzed in terms of their availability and accessibility. Based on this, socio-demographic data and area clustering can be used to narrow down more precisely which areas do not yet have an AED in the vicinity. In addition, potential locations for defibrillators are identified based on various location factors such as visibility or maintainabilty. On the one hand, experience has shown that proven locations such as pharmacies or bus stops should be used. However, it may be necessary to identify additional locations for AEDS in order to ensure comprehensive coverage.

The data required for this, such as locations of already placed AEDs or points of interest (e.g. pharmacies or bus stops) as potential locations for newly placed AEDs, are often not freely available or are incomplete. This can be remedied by data imputation methods that derive the missing data from publicy available data sources, such as OpenStreetMaps. However, this data must also first be checked for quality and missing or incorrect data must be replaced with a suitable approach. Thus, one challenge is to create a complete, temporally and spatially accurate data basis by developing and applying suitable imputation methods. Depending on the quality of the available data, this imputation can range from simple, classical methods to complex, deep learning-based image classification algorithms. For a mostly complete dataset, for example, it may be sufficient to replace missing location data with their statistical mean. A more incomplete dataset, on the other hand, requires estimating the missing location data using complex algorithms from raw data such as images.

Mathematical optimization methods are then used to generate a recommendation for the smallest possible number of AEDS to be optimally placed, which ensures non-discriminatory, area-wide availability of the defibrillators on a mathematically sound basis. The integration of data regarding the status of the defibrillators guarantees that they are ready for use in an emergency.

Area-wide coverage of the city of Fürth graphically presented

The outcome of the project will be an interactive demo for optimal site placement of AEDs using the city of Fürth as an example. Through collaboration with various stakeholders in the field of health assurance in the city of Fürth, relevant location factors are considered from different points of view.

At the same time, however, special attention will be paid to transferability to ensure that the methodology can be applied in other cities.

Our project partner, CardiLink, plans to disseminate the developed optimization and imputation methods, both at the European level and in the USA or selected markets in Asia. This can lower barriers to heart safe city projects and ensure the increasing adoption of monitored AEDs.

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