In this short presentation, examples of applications of data in manufacturing companies will be shown along with some concrete examples together with the approach of how data was used to improve products and processes. Key Speakers
Dr. Sebastian Domaschke Managing Consultant
Dr. Christof Niemann-Mall Senior Consultant
Registration is open until Thursday, September 28. Participants will receive an access link after registration. See also the flyer for more information.
In this challenge, we provide you with a dataset containing consumption/production profiles. Your task is to develop a predictive model that can accurately forecast energy consumption/production patterns. The model needs to be deployed on a resource-constrained edge device, simulating real-world constraints. The targeted edge device is CLEMAP. For sake of simplicity, a virtual machine (VM) could be used to emulate the edge device with limited resources.
To make the deployment process simple, we ask you to use NuvlaEdge technology. The main goal is to deploy the developed forecasting module using NuvlaEdge, a powerful edge computing platform. The objective is to optimize and efficiently use resources while achieving accurate predictions.
The evaluation of your solution will be based on the following criteria:
Model Performance: The accuracy of your predictive model will be assessed using the Mean Squared Error (MSE) score. We are looking for models that can effectively capture the energy consumption/production patterns and generate accurate forecasts.
Overhead: Your solution must be deployed on a limited resources device. It must also “cohabit” with NuvlaEdge. Avoiding overload and efficiently using the available resources will be crucial. It is therefore paramount that the footprint (CPU and memory) of your solution is as low as possible.
Optimisation: We encourage you to take into account optimization concerns. This includes strategies to minimize resource contention, reduce computational complexity, and optimize memory usage, all while maintaining accurate predictions.
Summary steps for the challenge:
Develop the forecasting module as a Docker container: Create a predictive model for energy consumption/production based on the provided dataset, and encapsulate it along with its dependencies into a Docker container.
Deploy the forecasting container: Use the NuvlaEdge platform to deploy the developed forecasting module.
Monitor/Optimise resource usage
Evaluate model performance: Assess the performance of your deployed model using evaluation metrics such as the Mean Squared Error (MSE) score.
By participating in this challenge, you will gain valuable experience in addressing the resource constraints and optimization challenges inherent in edge computing environments. Your contributions will drive advancements in energy forecasting and pave the way for efficient deployment of predictive models on edge devices.
Databooster: How can you make the most of your data?
The aim of the Innovation booster “Databooster”, funded by Innosuisse, is to support innovation linked to data based value creation. Its main mission is to support SMEs (1) in identifying their technological and economic challenges, (2) in turning their innovative ideas into real concrete products/services (through the development of prototypes), and (3) in identifying funding instruments for their research and development programmes. This workshop will present the Databooster’s approach through concrete examples of SME support. SMEs involved in the program will talk about their experience.
L’objectif du réseau Innovation booster «Databooster» national thématique Databooster, financé par Innosuisse, est de soutenir l’innovation liée à la création de valeur ajoutée basée sur les données. Sa mission principale est d’accompagner les PMEs dans l’identification de leurs défis technologiques et économiques, la concrétisation de leurs idées innovantes (via le développement de prototypes), et l’identification d’instruments de financement de leurs programmes de recherche et développement. Ce workshop se propose de présenter la démarche de Databooster à travers des exemples concrets d’accompagnement de PMEs. Des entreprises viendront témoigner et partager leur expérience.
Vom 25. – 26. Oktober 2023 findet die 15. Ausgabe der maintenance Schweiz in Zürich statt. Die Schweizer Leitmesse für industrielle Instandhaltung ist ein fixer Bestandteil für Alle, die sich mit Anlagenwartung, Ersatzteilen, Smart Maintenance, Arbeitssicherheit und technischen Lösungen auseinandersetzen. Die Messe präsentiert Lösungen und Trends für die gesamte Schweizer Industrie.
Der Databooster organisiert gemeinsam mit vier Firmen einen 2.5-tägigen Workshop zum Thema “Wie können Unternehmen mit ihren Partnern und Kunden mit neuen und bestehenden Services resilienter und gleichzeitig nachhaltiger werden?”
Es ist deutlich geworden, dass Business Ökosysteme widerstandsfähiger werden müssen. Durch Smart Service Systeme können vorhandene Ressourcen neu ausgerichtet und verwendet werden. Dies ermöglicht Unternehmen, robuster gegenüber Störungen zu werden oder sich nach solchen rascher wieder zu erholen.
Herzlichen Dank an das Mobiliarforum Thun für die Mithilfe bei der Organisation.
How do I use AI and data management to add value to my company? Join Business Focus Day in Aarau on Thursday, 28.09 at 13.00. Big Data, Industry 4.0, ethics, and more, with the databooster innovation workshop, the cherry on top! Find all information on the official page!
Registration is required but participation is free for everyone.
Abschätzung des Sterblichkeitsrisikos durch Smartphone -Daten? Die Zerstörung von gefährdeten Lebensräume durch geo-tagged Social Media – Kommunikation? Diskriminierung aufgrund räumlicher Autokorrelationen?
In diesem Webinar geht es um das aktuelle Thema der ethisch-moralischen Herausforderungen bei der Erhebung, Verarbeitung und Anwendung/Interpretation von räumlichen Daten. Dabei werden nicht nur Fragestellungen um Data Privacy thematisiert, sondern auch die Schwierigkeiten rund um Qualität und Bias in den Daten an sich und den daraus resultierenden Limitationen in der Entwicklung und Anwendung von Algorithmen, insbesondere im Bereich von Machine Learning-Methoden. Dabei steht vor allem die Verknüpfung verschiedener Datenquellen und der daraus resultierenden Zusammenhänge im Fokus. Es werden sowohl Einblicke aus der aktuellen Forschung zur Ethikdebatte als auch in spezifische Anwendungs- und Umsetzungsbeispiele aus der Industrie vorgestellt.
Finden Sie alle Informationen auch auf der offiziellen Webseite (Link)!
Organisation: Christoph Heitz (ZHAW), Karin Lange (dieMobiliar), tbd (CLAIRE), Stefan Keller (OST), Reik Leiterer (data innovation alliance)
We would like to cordially invite you to our 8th European COST Conference on Artificial Intelligence in Finance – Sept 29, 2023, online and at Bern Business School.
This year, the event will be joint with our Annual Meeting for the COST Action on Fintech and Artificial Intelligence in Finance as well as the European Marie Sklodowska-Curie Action Industrial Doctoral Network on Digital Finance. We will welcome participants from more than 20 European countries in Bern.
We would like to invite you to the GEOSummit open innovation workshop on “Open Data Value Creation”, hosted by ERNI in Zurich.
Creating value based on open data is difficult, as topics such as harmonization of data formats, automatic data lineages or the standardization of data linkage processes are technically challenging and also not unproblematic from a regulatory point of view. But even supposedly simpler steps such as contextualized data search and raising awareness of the availability of open data in general have only been implemented to a very limited extent. In this workshop, we would like to invite stakeholders from research, industry, NGOs and the public sector to work on solutions and to define concrete steps on how to improve value creation through open data. Dr. Jürg Meierhofer (ZHAW) will be our moderator and guarantees a result-oriented, structured approach to the workshop.
Free participation, but registration is necessary: Link
Wir möchten Sie zum GEOSummit Open Innovation Workshop “Open Data Value Creation” einladen, der von ERNI in Zürich veranstaltet wird.
Die Wertschöpfung auf der Basis offener Daten ist schwierig, denn Themen wie die Harmonisierung von Datenformaten, automatische Datenabgleiche oder die Standardisierung von Datenverknüpfungsprozessen sind technisch anspruchsvoll und auch aus regulatorischer Sicht nicht unproblematisch. Aber auch vermeintlich einfachere Schritte wie die kontextualisierte Datensuche und die Sensibilisierung für die Verfügbarkeit offener Daten im Allgemeinen wurden bisher nur in sehr geringem Umfang umgesetzt.
In diesem Workshop möchten wir Akteure aus Forschung, Industrie, Nichtregierungsorganisationen und dem öffentlichen Sektor einladen, an Lösungen zu arbeiten und konkrete Schritte zu definieren, wie die Wertschöpfung durch offene Daten verbessert werden kann. Dr. Jürg Meierhofer (ZHAW) ist unser Moderator und garantiert einen ergebnisorientierten, strukturierten Ansatz für den Workshop.
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