Demo Data from SIGIR 2026 / reviewers in the wild / expert
Markus Weiss
dblp:84/7576
· DBLP profile ↗
6ranked-venue papers
5as first author
0since 2021 · last 2012
0000-0002-5822-9591ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 5 · 5 first-authorSystems, architecture and hardware · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Energy systems and smart grids · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Ubiquitous computing and smart environments · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Energy systems and smart grids
energy disaggregation |
0.1 | 1 | 2012 | Leveraging smart meter data to recognize home appliances · PerCom 2012 |
Energy systems and smart grids › smart metering
smart meter data analysis |
0.1 | 1 | 2012 | Leveraging smart meter data to recognize home appliances · PerCom 2012 |
Ubiquitous computing and smart environments
smart home |
0.0 | 1 | 2012 | Leveraging smart meter data to recognize home appliances · PerCom 2012 |
Methods — techniques the papers use, named apart from their topics
signature recognition · 0.3signal filtering · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | Leveraging smart meter data to recognize home appliancesabstractThe worldwide adoption of smart meters that measure and communicate residential electricity consumption gives rise to the development of new energy efficiency services. Several particularly promising applications involve the disaggregation of individual appliances within a particular household in terms of their energy demand. In this paper we present an infrastructure and a set of algorithms that make use of smart meters together with smartphones to realize new energy efficiency services (such as itemized electricity bills or targeted energy saving advice). The smartphones, together with a novel filtering approach, much simplify the training process for appliances signature recognition. We also report on the performance of our system that was tested with 8 simultaneous devices, achieving recognition rates of 87%. Markus Weiss, Adrian Helfenstein, Friedemann Mattern, Thorsten Staake |
PerCom | 1 |
| 2012 | PowerPedia: changing energy usage with the help of a community-based smartphone application
Markus Weiss, Thorsten Staake, Friedemann Mattern, Elgar Fleisch |
Pers. Ubiquitous Comput. | 1 |
| 2010 | Embedding internet technology for home automationabstractAs more and more digital appliances populate our homes, networking them to form a home automation (HA) system not only becomes an option, but almost a necessity. While comfort, security, and energy efficiency can be provided by many existing systems, they all remain complex islands that are difficult to expand and customize. We propose Internet technology to remedy the situation and to become the future solution for HA. For this, we analyze the feasibility of today's Internet technology with regard to traditional HA solutions. Furthermore, we present two case studies that substantiate the benefits of our proposal. As we will show, with IPv6 and 6LoWPAN, a single network serves the classical as well as emerging aspects of HA while concepts from the Web provide benefits for both, developers and users. Matthias Kovatsch, Markus Weiss, Dominique Guinard |
ETFA | 2 |
| 2010 | Evaluating Mobile Phones as Energy Consumption Feedback Devices
Markus Weiss, Claire-Michelle Loock, Thorsten Staake, Friedemann Mattern, Elgar Fleisch |
MobiQuitous | 1 |
| 2010 | Increasing energy awareness through web-enabled power outletsabstractRising global energy demand, increasing electricity prices, and the limitation of natural resources has led to increased thoughts on residential energy consumption. A necessary step towards energy conservation is to provide timely and fine-grained consumption information. This allows for users to identify energy saving opportunities and possibly adjust their behavior to conserve energy. In this paper, we present a device-level energy monitoring system that is based on off-the-shelf components and enables users to monitor, control, and compare the electricity consumption of their appliances. By providing a RESTful API, we seamlessly integrate the smart power outlets into the web and facilitate the development of extensions and novel features. We demonstrate this through the implementation of a web user interface and a mobile phone interface. We further confirm the suitability of our approach with the help of a 12 months pilot deployment. The results of a questionnaire provide insights into additional user features and the interviews conducted with developers who used our open sourced system illustrate the usefulness of the RESTful approach for the smart energy domain. Markus Weiss, Dominique Guinard |
MUM | 1 |
| 2009 | Handy feedback: connecting smart meters with mobile phonesabstractReducing their energy consumption has become an important objective for many people. Consumption transparency and timely feedback are essential to support those who want to adjust their behavior in order to conserve energy. In this work, we propose an interactive system that provides instantaneous feedback concerning the energy usage on household and device level. For that, we used and extended the capabilities of a smart electricity meter, built a web-based API to enable interoperability with other applications, and developed a mobile phone interface that allows users to monitor, control, and measure the consumption of single appliances. Our system illustrates a way how usage barriers can be lowered and how high user involvement can be created. By providing users the electricity feedback needed -- in real-time and on device level -- the system allows for identifying the biggest energy guzzlers and helps users decrease their energy consumption. Markus Weiss, Friedemann Mattern, Tobias Graml, Thorsten Staake, Elgar Fleisch |
MUM | 1 |