Publications de Julien Eberle | EPFL Graph Search

Toward Self-monitoring Smart Cities: the OpenSense2 Approach

Karl Aberer, Jean Paul Calbimonte Perez, Julien Eberle

2017

Tree-structured Classifier for Acceleration-based Activity and Gesture Recognition on Smartwatches

Karl Aberer, Julien Eberle, Dipanjan Chakraborty

This paper proposes a new method for recognizing both activities and gestures by using acceleration data collected on a smartwatch. While both activity recognition techniques and gesture recognition techniques employ acceleration data, these techniques are ...

Ieee2016

Energy-efficient Continuous Context Sensing on Mobile Phones

Julien Eberle

With the ever increasing adoption of smartphones worldwide, researchers have found the perfect sensor platform to perform context-based research and to prepare for context-based services to be also deployed for the end-users. However, continuous context se ...

EPFL2015

Online Unsupervised State Recognition in Sensor Data

Karl Aberer, Julien Eberle, Tri Kurniawan Wijaya

Smart sensors, such as smart meters or smart phones, are nowadays ubiquitous. To be "smart", however, they need to process their input data with limited storage and computational resources. In this paper, we convert the stream of sensor data into a stream ...

2015

Semantic Data Layers in Air Quality Monitoring for Smarter Cities

Karl Aberer, Jean Paul Calbimonte Perez, Julien Eberle

Air pollution is one of the key indicators for quality of life in urban environments, and is also the subject of global health concern, given the number of mortal diseases associated to exposure to pollutants. Assessing and monitoring air quality is an imp ...

2015

XGSN: An Open-source Semantic Sensing Middleware for the Web of Things

Karl Aberer, Sofiane Sarni, Jean Paul Calbimonte Perez, Julien Eberle

2014

From big smartphone data to worldwide research: The Mobile Data Challenge

Olivier Dousse, Imad Aad, Julien Eberle, Daniel Gatica-Perez

This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we r ...

Elsevier Science Bv2013

Energy-Efficient Opportunistic Collaborative Sensing

Karl Aberer, Julien Eberle, Zhixian Yan

This paper studies mobile sensing in a complete distributed and opportunistic scheme. We present a novel sensing strategy for sensing nodes without movement constraints. This strategy offers information sharing and sensor scheduling that maximizes the bene ...

IEEE2013

Mobile observatory: an exploratory study of mobile air quality monitoring application

Karl Aberer, Julien Eberle, Yongsung Kim, Erol Can Ün, Riikka Maria Vilhelmiina Hänninen

We present Mobile Observatory, a mobile air quality monitoring application that provides evaluation of air quality of the city of Zurich, Switzerland. As Mobile Observatory utilizes air quality data gathered by sensors mounted on around 10 trams in Zurich, ...

ACM Press2013

ExposureSense: Integrating Daily Activities with Air Quality using Mobile Participatory Sensing

Karl Aberer, Julien Eberle, Zhixian Yan, Dragan Stojanovic

With an increasing number of rich embedded sensors, like accelerometer and GPS, smartphone becomes a pervasive people-centric sensing platform for inferring user’s daily activities and social contexts. Alternatively, wireless sensor network offers a compre ...

2013

A model-based back-end for air quality data management

Karl Aberer, Julien Eberle, Yongsung Kim, Erol Can Ün

In this paper we present a hybrid model for real-time query processing over data stream collected by mobile air quality sensors. First, we introduce a novel indexing scheme for representing air quality and use it for generating and evaluating a static mode ...

ACM Press2013

Symbolic Representation of Smart Meter Data

Karl Aberer, Julien Eberle, Tri Kurniawan Wijaya

Currently smart meter data analytics has received enormous attention because it allows utility companies to analyze customer consumption behavior in real time. However, the amount of data generated by these sensors is very large. As a result, analytics per ...

ACM2013

OptiMoS: Optimal Sensing for Mobile Sensors

Karl Aberer, Julien Eberle, Zhixian Yan

Both sensor coverage maximization and energy cost minimization are the fundamental requirements in the design of real-life mobile sensing applications, e.g., (1) deploying environ- mental sensors (like CO2, fine particle measurement) on public transports t ...

2012