In future, drones should be able to transport laboratory samples more quickly.

The central objective of the final phase of the project 'AI-based mobility optimisation in non-urban regions' (KIMoNo for short) is the research and optimisation of medical transport and communication routes in rural regions. Through the use of drones, transport times for laboratory samples are to be shortened, thus enabling faster diagnosis and medical care, especially in emergencies.

Covering distances with less energy expenditure in a shorter time

The MVZ Labor Passau examines medical samples from the entire region of Lower Bavaria and, in part, beyond. While the actual analysis is already highly digitalised and runs efficiently, pre-analysis and, in particular, the collection of samples is still a complex and costly process with a direct impact on the quality of treatment. In most practices, samples are collected only once a day; emergency samples require expensive and complex special trips, which are only possible if staff are available. The idea is to expand the collection system by using drones, which can cover many of these routes with less energy expenditure in a shorter time. To this end, the sample logistics must first be analysed and modelled in order to then improve traditional logistics through simulation and optimisation and to determine the benefit of the additional transport mode of drones. In addition, the communication between drone and laboratory is to be investigated and improved – for example, in estimating arrival times – and digitalised communication between practice and laboratory is to be developed, through which the sample and the steps to be carried out with it can be pre-notified.

'By combining AI-based simulation and optimisation, we can determine the best possible transport routes for the samples and quantify the added value of using drones,' said Prof. Dr Tomas Sauer, KIMoNo project leader 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, because a drone flight is a regulatory adventure. But we can show when it would really be worthwhile.'

Prof. Dr Harald Kosch, Vice-President of the University of Passau, added: 'This project makes an innovative contribution to optimising 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 and Transport, commented: 'New technologies such as artificial intelligence and unmanned transport systems offer enormous potential for making healthcare more citizen-centred, more individual and more efficient. In an emergency, there must be no differences in healthcare provision between the city and the countryside. The project demonstrates how digital applications can help shape our modern healthcare system while ensuring optimal medical care for people.'

Research questions and initial results

1. Analysis of workflows and processes and preparation of data: partly sensitive medical data were anonymised and pseudonymised at great effort. The methods developed in the process can also be used to incorporate future data into the system and thus update it on a sustainable basis.
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 already existing software prototype that simulates flights can, by means of an integrated notification system, send a message by email for certain events, e.g. drone take-off and landing.
5. Drone communication: an information system for recording and transmitting mission data as well as a fallback communication system were set up and successfully simulated.
6. First flight of the drone from Ortenburg (Dr Keller's paediatric practice) to Passau (MVZ Labor).

Participants from academia and practice

Prof. Dr Harald Kosch, Vice-President of the University of Passau for Academic Infrastructure and IT, coordinates the project together with Prof. Dr Tomas Sauer, head of the FORWISS Institute. The entire project consortium comprises:

• University of Passau, FORWISS Institute
• University of Passau, Chair of Distributed Information Systems
• University of Passau, Chair of Business Administration with a focus on Management Science / Operations and Supply Chain Management
• Deggendorf Institute of Technology, Institute for Applied Computer Science
• Quantum-Systems GmbH
• MVZ Labor Passau GmbH
• Kinderklinik 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, oriented towards the specific circumstances of the Lower Bavaria region, which is partly urban and partly very rural in structure, does not have comprehensive transport systems, and must serve locations that are sometimes very difficult to reach and accessible only by certain means of transport. In the first part of the project, for example, in the context of the Conference of Transport Ministers on 29 October 2020, the focus was on issues of digitally networked transport, the coordinated use of a wide variety of transport systems and logistics security. As part of the project extension, 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.

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