Demo Data from SIGIR 2026 / reviewers in the wild / expert
Aida Olaru
dblp:141/1945
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 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 |
Smart cities and intelligent transportation · 62% Energy systems and smart grids · 19% Environmental and earth informatics · 19% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Smart cities and intelligent transportation
route planning |
0.2 | 1 | 2013 | eWARPE - Energy-efficient weather-aware route planner for electric bicycles · ICNP 2013 |
Energy systems and smart grids
electric vehicle |
0.0 | 1 | 2013 | eWARPE - Energy-efficient weather-aware route planner for electric bicycles · ICNP 2013 |
Methods — techniques the papers use, named apart from their topics
survey · 0.2numerical analysis · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | eWARPE - Energy-efficient weather-aware route planner for electric bicyclesabstractCycling, as a very attractive green form of transportation, is also one of the most sustainable. Electric bicycles, the most popular electric vehicles, subscribe to this type of transportation, being highly environmentally friendly. They have several advantages when compared to traditional bicycles, but also a weak point in terms of long battery (re)charging duration. Consequently power-saving solutions for electric bicycles are of high research interest. In this context, this paper proposes a novel energy-efficient weather-aware route planner (eWARPE) for electric bicycles. The solution makes use of the weather information in order to recommend the optimal departure time that allows the cyclist to avoid the adverse weather conditions and to maximize the energy savings of the electric bicycle. Note that the departure time is in a user-configurable time interval. The departure time can be recommended for a preferred route introduced by the user or for a route built in eWARPE based on user input. The proposed solution was validated through numerical analysis. Moreover, a survey was conducted in order to assess the impact of the adverse weather conditions on cyclists and to measure how the cyclists will benefit from the proposed solution. Irina Tal, Aida Olaru, Gabriel-Miro Muntean |
ICNP | 2 |