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Schlagwort: Public Event

Energy Data Hack Days

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:

  1. 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.
  2. Deploy the forecasting container: Use the NuvlaEdge platform to deploy the developed forecasting module.
  3. Monitor/Optimise resource usage
  4. 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.

Challenge Owner: HES-SO

  • Mohamad Moussa
  • Nabil Abdennadher
  • Philippe Glass

Swiss IT Forum

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.

Find more information about the presentation here or on the official website!

Databooster : Comment valoriser vos données ?

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.

Plus d’informations sur la présentation ici ou sur le site officiel!

Smart Data Forum

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.

Finden Sie alle Informationen auf der offiziellen Webseite!

Digital Days 23 Aarau – Business Focus Day

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.

Ethic and Geoinformation Webinar

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)

8th European COST Conference on Artificial Intelligence in Finance

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.

The topics will cover amongst others

  • Asset Management and Large Language Models
  • Artificial Intelligence in Finance
  • Peer-to-Peer Lending
  • Share Buybacks – A multi-billion dollar question
  • Recent industry developments

Website
Registration (free, but mandatory)

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.

See the FLYER here.

Looking forward to your participation.

Best regards

Jörg Osterrieder, Branka Hadji Misheva, Christian Hopp and the entire organization team

GEOSummit – Open Data Value Creation

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.

As thematic use-case we will focus on the energy sector. This includes, for example, the analysis of consumption data collected by sensors and smart meters – or, more generally, exploiting the potential of energy management systems due to the increasing electrification. Especially with regard to energy savings (e.g. usage-specific lighting scenarios), these so-called IoT recommender systems have the potential to deliver great added value. These areas are not detached from the building shell, which brings us back to the various smart building & construction technologies and of course to the electricity providers (e.g. with regard to dynamic tariffs). in this context, we discuss topics such as data protection, data infrastructure and data management, open platform ideas for data sharing and trading and the smart services that could be built on them. 

The workshop is co-organized by the data innovation alliance and the SGPF.

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.

Als ein mögliches Anwendungsgebiet steht hierbei der Energiesektor im Fokus. Dazu gehört z.B. die Analyse von Verbrauchsdaten, die durch Sensoren und Smart Meter gesammelt werden – oder ganz allgemein die Nutzung des Potenzials von Energiemanagementsystemen aufgrund der zunehmenden Elektrifizierung. Gerade im Hinblick auf Energieeinsparungen (z.B. nutzungsspezifische Beleuchtungsszenarien) haben diese sogenannten IoT-Recommender-Systeme das Potenzial, einen großen Mehrwert zu liefern. Diese Bereiche sind nicht losgelöst von der Gebäudehülle, womit wir wieder bei den verschiedenen intelligenten Gebäude- und Bautechnologien und natürlich bei den Stromanbietenden Organisationen sind (z. B. im Hinblick auf dynamische Tarife) sind. In diesem Zusammenhang diskutieren wir Themen wie Datenschutz, Dateninfrastruktur und Datenmanagement, Ideen für offene Plattformen zum Datenaustausch und -handel und mögliche, darauf aufbauende „intelligente“ Dienste.

Der Workshop wird gemeinsam von der Data Innovation Alliance und der SGPF organisiert.

Die Teilnahme ist kostenlos, aber eine Anmeldung ist erforderlich: Link

Shaping Workshop – BFH meets Practice: Digital Onboarding for Small and Medium-Sized Companies: A Toolbox Approach

In today’s rapidly evolving business landscape, the onboarding process has emerged as a crucial
aspect of organizational success. With the advent of remote work and virtual teams, new challenges
have arisen, necessitating the development of structured onboarding processes that incorporate digital
tools. However, the integration of analog and digital tools to effectively assimilate new hires
remains a persistent challenge for organizations.

Effective onboarding of new hires has long been recognized as a critical factor in organizational
success. It ensures a smooth transition for new employees and facilitates their assimilation into the
organizational culture and workflow. However, with the paradigm shift towards remote work and virtual
teams, the traditional onboarding process has encountered new hurdles, necessitating the adoption of
novel strategies and digital tools. New work arrangements offer flexibility and access to talent pools
beyond geographical boundaries. However, they also present unique challenges in terms of team
collaboration, communication, and fostering a sense of belonging. Addressing these challenges
requires a reimagining of the onboarding process.

Leveraging digital technologies for employee onboarding creates complexities that differ from
traditional in-person onboarding. The absence of physical presence makes it challenging to establish
personal connections (commitment and organizational citizenship behaviour) and convey the
organizational culture effectively. The challenges posed by the combination of analog and digital tools
necessitate innovative strategies. By implementing a structured onboarding process that incorporates
digital tools effectively, organizations can foster a sense of connection, enhance employee
engagement, and lay the foundation for long-term success in a digital-first era.

A research Team of the BFH aims to develop a toolbox of digital solutions in order to empower
SMEs to effectively integrate new hires. Through empirical research and a focus on specific SME
needs, this study seeks to enhance the onboarding experience and promote organizational success. 

We are inviting companies interested in participating in a shaping workshop to share their
knowledge and insights
regarding the use of digital tools in the onboarding processes. This
workshop will provide an opportunity for participants to discuss the challenges they face and generate
initial ideas on how to effectively address these challenges. We encourage companies to join us
in this collaborative session to foster knowledge sharing and collectively enhance the onboarding
experience. 

The workshop will take place on 02.10.2023 from 16.30 – 18.00 at Haslerstrasse 30, 3008 Bern
followed by an Apèro.

The language of the workshop will be chosen depending on the number of registered participants
(German/English).

Registration is requested by 18.09.2023 to Sabrina.Schell@bfh.ch

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