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Information Systems, Socio-Technical Systems Design (WISTS)

Photo: WISTS Team

Research

Current Projects

RESCUE-MATE

Current Situation

The creation of a digital twin with the continuous integration of real-time data is a crucial step in today's interconnected world. This process involves the collection, integration, and interpretation of real-time data from various established data sources, including information from rescue functions, environmental sensors, and traffic sensors. These data sources are merged into a comprehensive situational overview, serving as an orientation and assessment basis for emergency responders and decision-makers. Furthermore, social media data and information from reconnaissance drone flights are also integrated into this digital twin. This enables an even more precise and comprehensive representation of the current situation. These diverse data sources ensure that the digital twin is always up to date, providing valuable support to those who must make quick and well-informed decisions in emergency situations.

Objective of the Project

Within the scope of the research project Rescue-Mate, the challenge of situational awareness and optimization of information flows in the security scenario of a storm surge in Hamburg is investigated. This challenge arises against the backdrop of rising sea levels, more frequent extreme weather events, and a growing number of residents who need to be evacuated and provided for in disaster situations. The involved stakeholders in this scenario include authorities and downstream entities such as the fire department, police, the port staff, and various relief organizations. They urgently require a shared situational overview for mission planning and real-time information on the current status. This is particularly relevant in disaster situations such as a storm surge, which involves aspects such as drowning individuals, drifting ships, and road closures. The geographic focus is on the Hamburg harbor and the neighborhoods of Wilhelmsburg and Hafencity, as these areas are particularly affected and have a high number of potentially vulnerable residents. The urgency of this project is underscored by increasing population figures, the vulnerability of specific neighborhoods, higher storm surge levels, and outdated analog information and communication flows. Currently, there is a lack of digital processing of real-time data that would enable a comprehensive situational assessment.

The solution lies in the creation of a shared data platform for all participating stakeholders. This platform allows the inclusion, analysis, and consolidation of sensor data such as water levels and traffic flows, as well as social media content and information from drone-based aerial reconnaissance. The main objective of this project is to minimize risks for emergency responders, facilitate the evacuation and care of citizens, enable tailored mission planning, and ensure the efficient utilization of available resources.

Within the project, the AG WISTS is responsible for the area of citizen engagement and is in charge of developing the Rescue-Mate app. This app is designed to proactively facilitate the collection of data from hazard areas and support decision-making both preventively and during crises, thus enhancing the situational overview.

Funded Partners

  • Universität Hamburg (UHH)
    • Arbeitsgruppe Wirtschaftsinformatik, Sozio-Technische Systemgestaltung (WISTS)
    • Arbeitsgruppe Human-Computer Interaction (HCI)
    • Arbeitsgruppe Rechnernetze (NET)
    • House of Computing and Data Science (HCDS)
  • Behörde für Inneres und Sport (BIS)
  • Absolute Software (AS)
  • Bundesanstalt Technisches Hilfswerk (THW)
  • Eurocommand (EC)
  • HafenCity Universität (HCU)
  • Hamburg Port Authority (HPA)
  • Hanseatic Aviation Solution GmbH (HAS)
  • Hochschule für Angewandte Wissenschaften (HAW)
  • Hamburger Informatik Technologie-Center (HITeC)
  • Landesbetrieb Straßen, Brücken und Gewässer (LSBG)

Associated Partners

  • Artificial Intelligence Center (ARIC)
  • Bezirksamt Hamburg-Mitte
  • Bundesrettungshundestaffel Hamburg & Harburg e.V (RHS)
  • Deutsche Telekom AG (DTAG)
  • Deutsche Lebensrettungsgesellschaft (DLRG)
  • Deutsche Rote Kreuz (DRK)
  • Esri Deutschland GmbH
  • Freiwillige Feuerwehr Pinneberg
  • Hamburg Aviation
  • Innovations Kontaktstelle Hamburg (IKS)
  • Landesbetrieb Geoinformation und Vermessung (LGV)
  • Lufthansa Industry Solutions (LHIND)
  • NMS New Mobility Solutions Hamburg GmbH
  • Stadtreinigung Hamburg
  • UAM-InnoRegion-SH

Project Details

  • Duration: 01.10.2023 – 30.09.2027
  • Project Management: Behörde für Inneres und Sport (BIS)
  • Project Website: https://www.rescue-mate.de/
  • Funding: The SifoLIFE funding initiative is supported by the Federal Ministry of Education and Research (BMBF) as part of the German government's "Research for Civil Security" program (funding codes 13N15596 and 13N15597).

Toward intelligent assistance systems for the smart utilization of participation data for urban planning and design

Current Situation

Urbanization has led to strong city growth in recent decades. In Europe, for example, about 70 % of the population already live in cities, which is comparable to global development. Advancing digitalization and increasing efforts to manage existing resources sustainably and reduce environmental pollution have shaped the term "Smart City" among other factors. In this context, urban planning enables aim-oriented urban planning, which is becoming increasingly participatory. Various research projects have already tested initial applications in practice and explored initial processes for participatory urban planning, on which we are now building.

Objective of the project

Within the scope of the project, artifacts for a digital assistance system to support urban planning will be developed to support urban planning processes, improve the quality of the results and simplify the participation of citizens. For this purpose, the corresponding requirements of citizens and urban planners will be collected, and different prototypes will be developed and evaluated. The focus will be on the use of artificial intelligence (AI) and machine learning (ML) approaches to support the interactions between people and machines and to automate analyses.

Project Partners

  • Universität Hamburg (UHH) – Research Group Information Systems, Socio-Technical Systems design (WISTS)
  • HafenCity Universität (HCU) – Research Group Digital City Science

Project Details

Hybridisation of human and artifical intelligence in knowledge work (HyMeKI)

Background

Advances in the field of artificial intelligence, (especially machine learning and speech recognition), offer new design options for reorganizing knowledge work at the interface between humans and AI. AI systems not only provide potential in the automation of routine tasks, but can also support the solution of complex tasks of employees as new "team members", since they contribute complementary skills to humans in many areas. People perceive AI-based systems as social actors, but therefore have similar expectations regarding the quality of their solution contributions and their communication behavior. These expectations are often not met and can lead to dissatisfaction, rejection or non-use of the systems. The differences in the abilities and skills of humans (i.e. human intelligence) and machines (i.e. artificial intelligence) create new design challenges in collaboration and learning processes for human and machine learning.

Aim of the project

The goal of the junior research group is the development, testing and validation of socio-technical design requirements and patterns for the development of AI systems in knowledge work. These implement collaborative working practices of human-AI collaboration, in particular for the division of labor, for the transparent and comprehensible transfer of tasks and work statuses, and for the promotion of learning between humans and AI systems according to their respective strengths.

In order to achieve the objectives, representative collaboration scenarios in the field of knowledge work are first of all surveyed and modelled in an application-oriented manner by empirical requirements elicitation with companies. Based on this, the junior research group develops a taxonomy for the division of labor between people and AI systems. Based on this, techniques for transfer orchestration between humans and AI as well as techniques for the promotion of AI-(or human-) supported human (or machine) learning are explored and transferred into design patterns. The developed techniques and design patterns are prototypically instantiated and socio-technically evaluated in laboratory, field and online studies. The project thus follows a design-oriented multi-method approach of iterative development and evaluation.

Participation of the WISTS working group

The focus of WISTS in the joint project is on the development and testing of design patterns for task sharing, transfer and work orchestration between knowledge workers and learning systems (e.g. decision templates through AI system, human feedback for machine learning, etc.). Based on the analysis of practical use cases from user organizations, relevant transfer scenarios from human to AI will first be identified and modeled, and socio-technical solution approaches will be prototypically instantiated in the form of design patterns for transfer prerequisites, transfer contents and their preparation, and for transfer orchestration. Solution approaches for the handover from AI to human are analyzed, modeled and developed. These approaches are then piloted and evaluated experimentally and on the basis of user evaluations in the team laboratory in Hamburg and in the user organizations.

Project partners

  • University of Kassel - Department of Information Systems
  • University of Kassel - Scientific Center for Information Technology Design (ITeG)
  • aiconix.ai
  • IHK Hessen innovative
  • smarttransfer

Project homepage

https://hymeki.informatik.uni-hamburg.de/en/

Project details

  • Duration: 01.10.2020 - 30.09.2024
  • Project management: Prof. Dr. Eva Bittner, Dr. rer. pol. Sarah Oeste-Reiß
  • Funding reference number: 01IS20057