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Let’s Hack

- April 6, 2021 in Energie, event, food, hackathon, Hackday

Spring is waking us up from our winter-lockdown-sleep and our minds are ready for action. Join us for one (or more) of our hackdays. Whether you’re interested in culture, tourism, journalism, energy, climate, farming, or sports, or if you’re just a fan of open data, we have a hackathon planned for you.

GLAMhack 2021 hosted by the ETH Library in Zurich – Fri. 16th to Sat. 17th of April (online)

Once a year, the GLAMhack experiments how cultural data and content can be used for research purposes, for web and mobile apps, in the context of Wikipedia, for artistic re-mixes, or for other forms of re-use. This year, our hackathon will take place online. There will be an onboarding session on 9 April (evening) and an opening event with presentations, workshops, and a poetry slam performance on April 15th. Sign up now!

HSLU Open Data Tourism Hackdays – Wed. 28th to Thu. 29th of April

During this event, the tourism industry takes the chance to tackle its structural issues and to recognize unexploited potentials. We would be delighted to see you there and build upon the findings of the past years. So please take part! The challenge presentations & Team building session will be hosted on Wednesday 21st of April at 17.00. Sign up now!

The Rethink Journalism Hackathon – Fri. 7th to Sat. 8th of May (online)

Over the past decades, journalism has been continuously reinventing itself. Small and innovative media establishments charge into battle for attention and users. Come and join us in the quest to stimulate and promote progressive journalism. Help us in the fight against fake news and hate speech. Be part in overturning information monopolies and join to re-shape the future of journalism. Sign up now!

The “Energy & Climate Hacks”Tue. 31st August to Wed. 1st of September 2021.

Cities are responsible for 70% of the planet’s carbon dioxide emissions and they play a central role when it comes to efforts on global decarbonisation and pushing forward the local energy transition. In the lead-up to the global climate conference COP26 in Glasgow, a two-day hackathon will bring together young talents, pioneers, innovators, and companies from Switzerland and the UK to tackle these important challenges. Sign up now!.

….Save the dates

– The Open Farming Hackdays 2021 will take place from Fri. 3rd to Sat. 4th of September 2021 – The Open Energy Data Hackdays 2021 are announced from Fri. 24th to Sat. 25th of September 2021 – The Smart City/Region Lab – Lenzburg –  2021 is very likely to take place in October 2021 – The HSLU – Open Data Sports Hackdays are scheduled from Fri. 26th to Sat. 27th of November 2021

Shape My City – Lucerne, the Results!

- January 19, 2021 in Bildung, Daten, Energie, event, Forschung, hackathon, Luzern, smart city

Almost in the same breath, following the Smart city Lab Lenzburg, we were happy to support the student team of the Master of Applied Information and Data Science at the HSLU in their organization of the Shape My City Hackdays – Luzern, a Hackathon revolving around smart city projects for Lucerne and its inhabitants. Around 110 participants gathered online, ready to hear about the 15 so-called challenges awaiting for a solution. Those issues opened by either the industry, civil society or city of Lucerne itself, were prepared in collaboration with group of students who helped defining the framework of the question and to gather and prepare relevant datasets, providing the Hackdays-teams with the material to solve the challenge itself. This event being a fully virtual workshop was not as vividly alive as what we are used to during the HSLU-student Hackdays, (melancholy…), still, the very funny slides and the clear engagement of the teams made for a very good event. Two inputs by Stefan Metzger CDO of the city of Luzern and by Benjamin Szemkus, Program manager of Smart City Switzerland, provided for background information about the strategies and perspective in the field. A lot of open data on the topic of smart cities was gathered, and last but not least and as always astonishing, the plethora of good results convinced us once again of the relevance of such collaborative endeavours. The challenge topics nicely completed or confirmed those issues addressed a few weeks before in Lenzburg. There too it was obvious that those location and user-specific solutions are actually relevant for a much broader public and regions. Nevertheless, implementing them locally still seems to be a meaningful and challenging enough step before exploring those broader fields. Most teams are willing and ready to keep on exploring the challenges with their challenge owners, we are curious to see how far the projects go from there on! Solar Energy in the City of Lucerne
Identifying similar buildings in terms of solar characteristics facilitates the approach to building owners to promote the installation of solar panels. The project group gathered over 15 different datasets, cleaning, preprocessing, analyzing and converting the datasets into desired shapes and Geospatial data formats. The prototype is as desired simply an excel file, containing the necessary information.  Disclaimer: data about the buildings are not publicly available and are to be considered as strictly confidential. Therefore, this part is private, however, the code is public. Consumer Behavior in the City of Lucerne
The project group worked on identifying Personas that will help to address the target groups on the topic of environmentally friendly behaviours. They also worked on analysing datasets to find interesting correlations and patterns concerning existing consumer behaviour. Quantification of Visitors of Cultural Events
The number of visitors from the surrounding municipalities attending events at cultural venues in Lucerne is not available yet. The project-team created a measurement tool that easily and efficiently registers the place of residence of the attendees of a cultural event. Drug Sharing Ecosystem Driven by Blockchain
This group implemented a Blockchain technology to visualizes exchanges and flows of drugs between main health stakeholders, in order to increase transparency, security and automation of drug exchanges. Open Social Spaces
Through the use of a web AR Application, locals can give a shape to their ideas. Users can place and visualize objects directly in a chosen location and vote for creations by others. 360° Stakeholder Feedback Analysis
Large urban transformation projects require thorough analysis of the needs and requirements of all stakeholders involved. This project-team therefore worked on a Dashboard allowing grouping, qualification and prioritization of the stakeholders-related needs and information, in order to make more of the available data and provide decision-makers with a fast overview by project.
2000 Watt Site – Reduction of Energy Consumption
This project-team worked on a gamification model and an app to inform and incentivize the reduction of energy consumption of households and help achieve the 2000 Watt Society goals. The system aims to compares households’ consumption as awareness is one of the motivations for new energy consumption strategies. Reduce Car Rides at Traffic Peak Hours
The project-team worked with an Agent-Based Traffic Modelling and Simulation Approach to predict and analyse the forseeable changes in traffic load for an area in planning.
They produced a SUMO file with a modeled traffic flow integrating the new conditions on the project site, as well as reflected on the tools and incentives for future traffic regulation on the area. Find Energy Inefficient Buildings in the City of Lucerne
As about 45 % energy usage is for buildings this team worked on a building-images database to identify potentially energy-intensive buildings, as well as on a gamified app-prototype to improve the quality oft he image collection, labelling and identifying thanks to collective intelligence. Interactive Visualizationfor Neighbourhood Residents
This team worked on visualizing existing data of small sub-quarters to gain insights about the facts, needs and participation interests of the residents in those neighbourhoods. The insights and visualisation will be integrated in the website to make the findings accessible to all residents. 3D Geovisualization of building energy demands
In order to identify strategic leverage areas of high energy consumption, this team combined 3D data with energy demand data and revealed regions and buildings with potential for energy optimisation. Flat finder for seniors:
This team tackled the issue of the specific needs of the elderly when it comes to finding a suitable house or apartment. They created a housing platform that analyses housing advertisements from existing platforms and filters out those fitting the needs of seniors. Netto- Null in den Quartieren?
The demo created by this group allows to determine the current CO-2 emissions in the districts of Lucerne and to visualise which heating methods the buildings are using. This is a strategic information for decision makers for energy production methods and for the inhabitants to visualize the impact of one or the other heating system on the environment.

Quality of Life in Lucerne
This working group focussed on generating new insights from an online questionnaire about Life quality in Lucerne for the city administration. They identified personas, expectations and new variables from the citizens answers.

Energy Data Hackdays 2020, the results!

- October 6, 2020 in 2020, Brugg, Daten, Energie, Energy, event, Forschung, hackathon, Hackdays, machine learning, Optimization

The excitement of the new edition of the Energy Hackdays in Brugg was a bit special this year. Besides the usual sweet little heart pinch of the leap into a new group, the discovery of the challenges and the satisfaction of seeing this particular event repeating for the second time in Brugg, there was happiness but also respect about having the Energy Hackdays taking place mostly on site at the Hightech Zentrum Aarau. So we met in person and as far as we can say, it has been worth it! 13 really ambitious and technical challenges met 85 participants who were nonetheless ambitious and highly qualified! Two big themes emerged this year and predictions based on machine learning was one of them. Predicting performance, usage patterns, anomalies or even failure, in order to plan, use and maintain infrastructure more accurately.  Reaching these goals of course allows a much better resource and production management. The other big topic covered by several challenges was the question of visualization and interfaces, especially for smart-meters: How to help users, scientists, producers or end-consumers to read flows of data and allow them to interpret and decide or react appropriately to a given data supported information? How can they analyse and control different aspects of their infrastructure or installation? Tangent to this topic were challenges that attempted to allow a market overview for the consumer, in this case the market of E-Car charging stations, or to visualize the overall live electricity consumption of Switzerland. As far as I can judge and from what I heard from the challenge owners, the results blew us away! While the project descriptions might be a bit less accessible to the public than some from past hackdays, the approaches and results certainly correspond to a present need in the energy industry and comfort us in the conviction that hackathons and collaborative work with Open Data do support high-end innovation.
We were also very lucky to welcome the team of Campus 21 who harvested the visions of some of the participants for the future of Open Energy Data. See you all next year!
The 13 projects developed during the hackdays District Heating Optimisation   Decrease gas peak boiler runtime due to better storage operation: heat demand forecast, improved storage control, better storage operation. PV self-consumption optimization Evaluate and optimize trade-offs in the design of battery storage for PV systems, so our customer can select, whether they want the most economical battery solution or maximise their autarky. Our tools calculate the maximized economic benefit over lifetime. Read your own Smart Meter Read your Smart Meter through the local Customer Information Interface (CII) and visualize your consumption. Design a dashboard with the most useful information. Cheapest Charging around In order to develop the GIS platform of the Swiss Federal Office of Energy (SFOE) further: Add price information to the charging stations and find the cheapest option around for electric car drivers. Energy Data Visualization     Creating a platform for strategic decision making based on data from the Energy Science Center of ETH Zürich. e-mobility behavior analysis We analysed the charging patterns of private vs public e-cars charging stations. This could provide good hints for a further automated customer segmentation, help prediction of behavior changes for the load-curve vs renewable electricity production & help customers optimize their charging habits. Empower the People with Smart Meter Data Smart Meter Additional Use Cases: Novel energy certificate assesses where and how strongly building / user behaviour causes deviation from theoretical / optimum behaviour. ML Wind Power-Prediction Machine Learning Wind Turbine Power Curve Prediction: we compared constructor provided production projections with actual production curves with the goal to improve site-specific  performance prediction of wind turbines. – Development of machine learning algorithms  (or tools/aps) for improved site-specific  performance prediction of wind turbines. – Development of alternative algorithms e.g. Artificial Neural Networks – Inputs: wind velocity, turbulence intensity, shear factor (alpha) Put CH on the Electricity Map Help meet the Paris Convention goals to achieve net 0 by 2050, less than 2 tonnes CO2 per person! We want to raise awareness around energy use and consumption by putting Switzerland on the map at and put its open data API to use. Distributed analytics for asset management The goal is to create a decision support tool for asset managers, using AI to predict how power transformers will fail, and what to watch out for. Anomaly Detection in Smart Meter Data We developed EDA and algorithms for the Anomaly Detection in Smart Meter Data challenge. We developed several approaches for detecting anomalous days based on mean and std of the readings during the day and for detecting single anomalous readings. These models can be integrated in the second part  of the challenge MeterOS: Smart Meter Anomaly Detection Create a model for Smartmeter Anomaly detector and their visualization. Unleashing the Swiss Smartmeter’s CII Empower citizens to use their energy data. Using the smartmeter’s CII beyond visualisation to steer local consumption.We developed a concept and PoC roadmap to provide a “universal” adapter from smart meters to home IoT platforms.