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Focus Topics

We invite “Call for Participations” in all areas of data-based value creation. We especially foster the following four focus topics, since we believe they come with a large untapped potential.

Industry 4.0

The Focus Topic “Industry 4.0” includes multiple innovative technologies in the area of industrial production. The focus is on intelligent and digitally connected systems. The full value chain from purchasing over logistics to manufacturing, are affected. However, two main areas of application are emerging: the smart factory and data-based services. In the smart factory, Industry 4.0 encompasses three levels of process automation: (1) condition monitoring of a machine or process, (2) data-based optimization through predictive intervention, and (3) self-organization of a system through self-diagnosis and autonomous machine decisions. Industry 4.0 also consists of a variety of other technologies such as augmented reality, digital twins, and mobile/collaborative robots.
A big driver in Switzerland is online quality control as well as full traceability down to lot size one. Swiss industry is very well placed to play an efficient role in the developments surrounding Industry 4.0.
The greatest challenges currently lie not in the technology, but in access to sufficient and qualitatively useful data. This is particularly important for the use of latest AI technologies such as deep neural networks.
The Industry 4.0 group is focusing on multidisciplinary exchange and getting the right stakeholders onboard.

Smart Services

The Focus Topic “Smart Service Concepts” provides a platform to share best practice to support the development and commercialization of smart services that are enabled by the use of data.

Smart services focus on the design of new innovative services in both a range of industries, from pure services such as banking to services associated with products or capital goods in both the B2B and B2C segments. We often focus on understanding the challenges of the ecosystem, the actors, their roles and their individual tasks. From this, we work to find new innovative value propositions and design new business models to support value creation within the ecosystem. Data can be transformed into information to assist with the development of new services as well as during the delivery of services.

Our partners and members benefit from getting access to this knowledge and experience through a structured innovation process that guides them from the initial challenge to a project proposal to apply for Innosuisse support.

Responsible AI

The Focus Topic Responsible AI supports innovation for making data-based services and applications socially responsible and ethical.

New regulations, such as the EU Artificial Intelligence Act or the Digital Services Act, pose new requirements on fairness, transparency, explainability, and robustness. A commitment to Responsible AI allows companies to create trust and confidence, avoid reputational damage, and achieve a competitive advantage. This does not come for free: Innovative approaches to reconcile algorithms and intelligent systems with ethical principles are needed.

The Focus Topic Responsible AI is dedicated to support companies and organizations in developing innovative solutions, based on an established network of data scientists, ethicists, and specialists for legal questions, management, governance and organization.

Please see the flyer for more information about this topic:
Flyer (EN)
Flyer (D)

Spatial Data Analytics

Mining companies strive to explore new and monitor existing sites, insurance companies need to evaluate claims, and financial service companies have to check on potential investment locations and monitor their assets. These use cases represent only the top of the iceberg, and the full potential of spatial data is only just being unlocked. But the analysis of spatial data depends on high-quality, homogeneous and up-to-date geo datasets – ranging from satellite, airborne or drone images to information about foot or road traffic. The compilation, actualization and analyzing of these datasets is tough and often inefficient. In this context, there is a need to overcome big data challenges, exploiting machine learning algorithms and utilizing cloud computing facilities to carry out advanced data processing and analysis on local to global scales. The Focus Topic “Spatial Data Analytics” will promote, support, and accompany innovative projects in this field – from idea generation to implementation.