The central aim of the final phase of the ‘AI-based mobility optimisation in non-urban regions’ project, KIMoNo for short, is to research and optimise medical transport and communication routes in rural regions. The use of drones is intended to shorten transport times for laboratory samples and thus enable faster diagnostics and medical care, especially in emergencies. 

Covering distances in less time with less energy expenditure 

MVZ Labor Passau analyses medical samples from the entire region of Lower Bavaria and, in some cases, beyond. While the actual analysis is already highly digitalised and runs efficiently, the pre-analysis and in particular the collection of samples is still a time-consuming and complex process with a direct impact on the quality of treatment: in most practices, samples are only collected once a day and emergency samples require expensive and time-consuming special trips, which are only possible if staff are still available. This is where the idea of expanding the collection system through the use of drones, which can cover many of the distances in less time and with less energy expenditure, comes in. To this end, sample logistics must first be analysed and modelled in order to then improve traditional logistics through simulation and optimisation and to determine the benefits of the additional means of transport, the drone. In addition, communication between the drone and the laboratory will also be investigated and improved, for example in the estimation of arrival times, and digitalised communication between the practice and the laboratory will be developed, through which the sample and the steps to be carried out with it are pre-announced.

‘By combining AI-based simulation and optimisation, we can determine the best possible transport routes for the samples and determine the added value of using drones,’ says Professor Tomas Sauer, KIMoNo project manager and head of the FORWISS Institute at the University of Passau. ‘However, there is still a long way to go before this means of transport can be used realistically, as flying a drone is a regulatory adventure. But we can show when it would really be worthwhile.’

Professor Harald Kosch, Vice President of the University of Passau, adds: ‘This project makes an innovative contribution to optimising the transport routes for medical samples in our region. The use of drones as a means of transport for medical samples is also being tested in practice.’  

Dr Volker Wissing, Federal Minister for Digital Affairs and Transport: ‘New technologies such as artificial intelligence and unmanned transport systems offer enormous potential for bringing healthcare closer to citizens, making it more individual and more efficient. In an emergency, there should be no differences in healthcare provision in urban and rural areas. The project demonstrates how digital applications can help shape our modern healthcare system and ensure that people receive the best possible medical care.’

Questions and initial results

1. analysing workflows and processes and processing the data: Partially sensitive medical data was extensively anonymised and pseudonymised. The methods developed in the process can also be used to transfer future data into the system and thus update it sustainably. 
2. data analysis and AI-based prediction: An AI system was trained that predicts the time until the laboratory result for given postcodes, dates and sample types. 
3. modelling and optimisation of logistics: transport systems were carefully modelled and several optimisation options for the routes were developed and investigated. 
4. web-based information system: An existing software prototype that simulates flights can send a message by e-mail in the event of certain events, e.g. drone take-off and landing, using an integrated notification system. 
5. drone communication: An information system for recording and transmitting mission data and a fallback communication system were set up and successfully simulated.
6. first flight of the drone from Ortenburg (paediatric practice Dr Keller) to Passau (MVZ Labor).

Participants from science and practice 

Professor Harald Kosch, Vice President of the University of Passau for Academic Infrastructure and IT, is coordinating the project together with Professor Tomas Sauer, Head of the FORWISS Institute. The entire project consortium consists of

• University of Passau Institute FORWISS
• University of Passau Chair of Distributed Information Systems
• University of Passau Chair of Business Administration specialising in Management Science/Operations and Supply Chain Management
• Deggendorf Institute of Technology Institute for Applied Computer Science
• Quantum-Systems GmbH
• MVZ Labor Passau GmbH
• Paediatric Clinic Dritter Orden Passau gGmbH

About KIMoNo

Since 2020, the KIMoNo project (AI-based mobility optimisation in non-urban regions) has been dealing with mobility issues in the broader sense, which are geared towards the special circumstances of the Lower Bavaria region, which is partly urban and partly very rural in structure, does not have comprehensive transport systems and sometimes has to serve places that are very difficult to reach and limited by some means of transport. The first part of the project dealt with issues such as digitally networked transport, the coordinated use of various transport systems and logistics safety in the context of the Transport Ministers' Conference on 29 October 2020. As part of the project expansion, the focus shifted towards medical care, with the transport of samples from doctors to the laboratory and the possible use of drones emerging as key topics. To the project website (German)

The project is funded by the Federal Ministry for Digital and Transport Affairs. 

Text: Nicola Jacobi

This text was machine-translated from German.