Innovation projects between Data+Service members are the core of our activities. Leverage your innovation ideas by launching an innovation project within the Alliance. Data+Service members profit from different options in our innovation initiative for shaping their own innovation process.

Call for participation makes your projects better. With trusted partners in the community you can develop new ideas. If you are an Academic Member you could find the right business partner, if you are an Industrial Member you can find the right research partner. Please contact us.

Here are some of the ongoing projects under the umbrella of the Alliance.

Adaptive scheduling algorithms for sheet metal shop production planning are devised with unprecedented level of detail to support operations and to quickly answer requests for quotations, thus increasing reliability and competitiveness.


Partners: Bystronic and IDP ZHAW

Partial discharge (PD) is the most reliable monitoring for generator stator insulation health status, and has been applied in industry since the 1990's. This project aims to merge experience and knowledge from GE with state of the art methods in machine learning to improve the data analysis of PD.

Duration: Feb 2018 - Jan 2020

Partners: GE and IDP, ZHAW

In der interdisziplinären Studie werden Chancen und Risiken von neuen Anwendungen der Roboter, die Empathie simulieren und Emotionen wecken, abgeschätzt, insbesondere in den Bereichen Einsatzpotenziale, Akzeptanz, Ethik, Recht und Volkswirtschaft. Der Untersuchungsgegenstand der Studie umfasst vor allem psycho-soziale, ethische, rechtliche, volkswirtschaftliche Auswirkungen und politischen Aspekte dieser Technologie. Die Ergebnisse sind in einem Bericht darzustellen, der wissenschaftlichen Anforderungen genügt und der auch als Basis zur Information einer breiteren Öffentlichkeit dient. Die Situation soll auf Grund der in der Studie gewonnen Erkenntnisse in einer Gesamtbeurteilung bewertet werden. Der Bericht soll Empfehlungen zum weiteren Umgang mit dieser Thematik enthalten, die an Entscheidungsträger insbesondere in der Politik und an Stakeholder in den erwähnten Anwendungsbereichen gerichtet sind.


Partners: F&P Robotics and APS FHNW

We develop and implement a cloud-based revenue optimization system for wind plant operators. By combining data analysis of real-time plant data with revenue schemes, revenue losses due to failures and sub-optimum control can be avoided, and profit can be increased by improved bidding strategies.


Partner: WinJi AG, ZHAW

The goal is the development of an application that enables the statistical comparison of risk and insurance profiles. This allows the users of the e-Broker platform to compare themselves with other customers (peers) and to automatically identify coverage gaps and overinsurance.

Duration: Mar 2018 - Nov 2019

Partner: Optimatis and Dept of Banking Finance & Insurance, ZHAW

With technologies of data science, Skillue develops a digital marketplace, which makes, based on the demanded and offered skills, the benchmarking of talents, jobs and companies possible. Skillue creates a new encounter zone for candidates and companies.

Duration: Jun 2018 - Dec 2019

Partner: Skillue AG, ZHAW

The project aims to prototype Digital Twins in six different industrial environments to explore how the Digital Twins can designed to improve business outcomes over the whole lifecycle. The lessons learnt will be shared openly with all partners from the innovation approach taken, and business models.


Partners: Siemens Mobility, ZHAW, HSLU, FHNW and SUPSI

Im Rahmen des Innovationsschecks wird untersucht, mittels welchem Verhaltensrepertoire und welchen Features humanoide soziale Roboter der Klasse Nao/Pepper die Kontaktaufnahme sowie den Start in ein Gespräch erfolgreich und mit sozialer Akzeptanz durch die menschlichen lnteraktionspartner bewältigen können. Die Firma Avatarion ist ein von Saftbank Ltd. (Hersteller der Roboter Nao und Pepper) lizensierter Distributor der humanoiden Nao- und Pepperroboter für die Schweiz. Avatarion stellt mit der Yeo-Suite eine Programmier-schnittstelle bereit und bietet Programmierdienstleistungen an. Avatarion beobachtet immer wieder, dass der Start einer Interaktion mit einem sozialen Roboter für viele Kunden eine kritische Herausforderung darstellt. Dies weil der Roboter überschätzt wird oder weil zu wenig Wissen über die Funktionsweise existiert. In der Folge kommt es auf Seiten von Usern zu Frustration und zu ablehnendem Verhalten. Ein sozial akzeptiertes, proaktives Annäherungs- und Kontaktaufnahmeverhalten von Nao und Pepper stellt einen notwendigen Grundbaustein dar, auf den weitergehende Nutzungsszenarien aufsetzen wie z.B. in Rezeptions-, und Guidanceanwendungen.


Partners: Avatarion Technology and APS FHNW

DAA operates in industrial data logistics. We provide digital accessibility of industrial data to com-panies and realize multi-stakeholder use cases such as real-time risk assessment for insurers of industrial assets. In course of the business, we establish an API-based platform for inter-company data exchange or direct data monetization. An important and growing risk for insurers of commercial property and assets are natural hazards. geo7 is a leading geospatial analytics office, focused on natural hazard modelling and quantifica-tion in Switzerland and abroad. As part of the business, geo7 collects, cleans and augments geo-spatial data from various sources. These activities result in higher-value data sets than the raw data sourced, in terms of information content and in-house accessibility. This project aims on making geo7’s natural hazard data sets available to external customers through DAA’s APIs and a standardized ontology. This requires scalable harmonization of the data, the integration into DAA’s knowledge graph and the provisioning of an API. The project brings the following, not exhaustive, added value to the participating organizations: • geo7: Possibility to provide natural hazard data sets for direct monetization (pay-per-use sale) and for business development activities. Possibility to add more data in a cost-efficient way, once this project delivered an initial infrastructure. • DAA: Possibility to upgrade the existing data base with new, high-quality data to augment own modeling capacity. Possibility to increase the existing API pool and data ontology by the very topic of Swiss natural hazards data.


Partners: dataaheadanalytics and geo7

In Zusammenarbeit mit der Zürcher Hochschule für angewandte Wissenschaft (ZHAW) und der Hochschule Luzern (HSLU) hat die IDEE SEETAL für die Seetaler KMUs das Projekt «InnoEco» entwickelt. Das Projekt zielt darauf hin, die Unternehmen in der Entwicklung digitaler kundenzentrierter Dienstleistungen zu befähigen, unterstützen und zu fördern. Das Projekt will für Seetaler-KMU anwendbare Möglichkeiten und Instrumente schaffen, die Digitalisierung für innovative Dienstleistungen für Ihre Kunden zu nutzen. Das Projekt stärkt die Position der KMU im Standortwettbewerb.



Entwicklung einer "Lifestyle Change Toolbox", die die Dienstleistungsqualität von Interventionsprogrammen zur Prävention oder Behandlung von metabolischem Syndrom, Diabetes und Cholesterin verbessert. Dies wird durch personalisierte Interventionen und die Vernetzung der Leistungsanbieter erreicht.


Partners: Lucullinary, HSLU and FHNW

There is a huge amount of valuable information hidden in a company's database which is not easily accessible to business people. To query these databases, end users need to know the technical query language SQL as well as the database structure. However, typical end users do not have enough SQL skills to formulate complex queries. Even more so, higher-level analytics, e.g. "trend analysis over last month" or "detect outliers in the price fluctuation of product X over the last year" are hard to formulate even for SQL experts. Hence, the majority of non-expert users are basically not able to explore the available knowledge of their company.

Veezoo currently provides a system that can answer natural language queries against databases, with the goal of empowering all users inside a company to become data-driven and benefit from the available information. However, feedback from existing users shows that a wide range of customers completely lack familiarity with their own company's databases. In practice, this leads to a severely limited adoption of systems that provide a natural language interface for databases, given that most users are not aware apriori which questions to ask or on which regions of data to focus, in order to get the most added value from the large amounts of knowledge made available to them. Therefore, in the lack of proactive suggestions, recommended insights, as well as data exploration guidance, only translating natural language questions to equivalent database queries is simply not enough.

In this project we tackle this important open issue to make natural language interfaces to databases more suitable for widespread adoption by designing novel algorithms on top of the current Veezoo system, through a service that proactively guides users in exploring the data and augmenting the company's knowledge base. The service, called NQuest, will provide analytics mechanisms that empower a wide range of users to discover new insights in existing databases.

Duration: Jul 2019 - Jul 2021

Partners: Veezoo, University of Zurich and InIT ZHAW

Im Rahmen des Innovationsschecks sollen die Machbarkeit und die Belastbarkeit von Methoden zur virtuellen Bemusterung empirisch nachgewiesen werden. Konkret wird die Güte von Entscheidungen in einem realen Setting mit derjenigen in einem virtuellen Setting verglichen. Die Ergebnisse der Studie dienen dazu, die Potenziale und Risiken einer Bemusterung in VR Räumen auf Basis experimentell ermittelter Daten fundiert einschätzen zu können. Im Zentrum steht der Nachweis von Nutzenpotenzialen und Einsatzmöglichkeiten virtueller Methoden zur Bemusterung.



ScorePad's sheet music scanning service works for highquality input; to scale up business, it should work as well for smartphone pictures, used sheets etc. Project RealScore enhances the successful predecessor project by making deep learning adapt to unseen data through unsupervised learning.


Partners: ScorePad and InIT ZHAW

Complex global systems, like water cycles, agriculture, forestry, and many others, affect billions but are still poorly understood. Understanding these systems is crucial not only for the well-being of humanity, but also for companies that need to adapt to a changing environment. For decades, Earth observation (EO) satellites have been collecting data about our planet - providing valuable information on the impact of climate change on our environment. In particular, agriculture it is highly susceptible to environmental changes, as rising temperatures and reduced precipitation, for example, have a major impact on yields. Within SAMBA we assess the value of operational EO data for monitoring and assessing crop resources. In this proof-of-concept, the added value of the synergistic use of multiple satellite missions as base for an operational and scalable monitoring of agricultural areas at the national level (using Brazil as an example) is demonstrated. Within the framework of classification, up-to-date methods of data mining and machine learning are used. The results are maps of agricultural areas in a spatial and temporal resolution that had hardly been achieved up to then. SAMBA is implemented based on a cloud infrastructure using Amazon Web Services as well as a stand-alone application for internal use, which allows to demonstrate transferability and robustness of the methods developed in SAMBA.


Partners: ExoLabs and SwissRe

More and more manufacturing companies are switching from product to service revenue and evaluating with new, outcome-based, business models. Many of these companies, however, are struggling to establish a clear business case in order to justify the investments in IoT . This project aims to identify the most attractive business models with regards to anticipated added value and implementation efforts, with focus on industrial companies within the MEM industry. In addition, we want to identify the main drivers to increase customer’s willingness-to-share data, as a basis for developing new data-based services.

Duration: April 2019 – April 2021

Partners: Ferrum and SML ZHAW

Projects completed

Ada - the Artificial Data Analyst - raises the productivity of data science endeavours by applying data science to itself: we apply empirical optimization also to algorithm and feature selection. Recent developments, e.g. from the MIT, are thus made available as a data product for Swiss industry.

Duration: Oct 2017 - Apr 2019

Partners: PwC and Datalab, ZHAW

Chatbot implementation which get in touch and fill out automatically all missing customer details

Duration: Feb 2018 - Feb 2019

Partner: Comparis and InIT, ZHAW

Leveraging data and analytics is essential for companies to keep up with competition, in particular for manufacturing companies. For small organizations, building up the appropriate resources as well as the knowledge and skills represents a major challenge. Specific approaches are required. This project investigates this topic.

Duration: Jan 2018 - June 2019

Partner: Several SMEs and FH St. Gallen, FH Vorarlberg and HTWG Konstanz

QualitAI provides research and development towards a machine for automatic quality control of industrial goods like balloon cathethers. This is enabled by recent innovations in the area of artificial intelligence (AI), specifically the analyis of images via so-called deep learning.

Duration: Jul 2017 - Jan 2019

Partners: BW-TEC and Datalab, ZHAW