Publications by Zhixian Yan | EPFL Graph Search

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Thanks to the rapid development of mobile sensing technologies (like GPS, GSM, RFID, accelerometer, gyroscope, sound and other sensors in smartphones), the large-scale capture of evolving positioning data (called mobility data or trajectories) generated by ...

Focus on movement data has increased as a consequence of the larger availability of such data due to current GPS, GSM, RFID, and sensors techniques. In parallel, interest in movement has shifted from raw movement data analysis to more application-oriented ...

With the prevalence of GPS-embedded mobile devices, enormous amounts of mobility data are being collected in the form of trajectory - a stream of (x,y,t) points. Such trajectories are of heterogeneous entities - vehicles, people, animals, parcels etc. Most ...

Location data generated from GPS equipped moving objects are typically collected as streams of spatio-temporal (x,y,t) points that when put together form corresponding {\em trajectories}. Most existing studies focus on building ad-hoc querying, analysis, a ...

GPS devices allow recording the movement track of the moving object they are attached to. This data typically consists of a stream of spatio-temporal (x,y,t) points. For application purposes the stream is transformed into finite subsequences called {\em tr ...

With increasing availability of mobile sensing devices including smartphones, online mobile data segmentation becomes an important topic in reconstructing and understanding mobile data. Traditional approaches like online time series segmentation either use ...

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 ...

With the large-scale adoption of GPS equipped mobile sensing devices, positional data generated by moving objects (e.g., vehicles, people, animals) are being easily collected. Such data are typically modeled as streams of spatio-temporal (x,y,t) points, ca ...

Complex activities are activities that are a combination of many simple ones. Typically, activities of daily living (ADLs) fall in this category. Complex activity recognition is an active area of interest amongst sensing and knowledge mining community toda ...

DIII-D research is addressing critical challenges in preparation for ITER and the next generation of fusion devices through focusing on plasma physics fundamentals that underpin key fusion goals, understanding the interaction of disparate core and boundary ...

Power consumption on mobile phones is a painful obstacle towards adoption of continuous sensing driven applications, e.g., continuously inferring individual’s locomotive activities (such as ‘sit’, ‘stand’ or ‘walk’) using the embedded accelerometer sensor. ...

We investigate the problem of online detection of complex activities (such as cooking, lunch, work at desk), i.e., recognizing them while the activities are being performed using parts of the sensor data. In contrast to prior work, where complex activity r ...

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 ...

The increasing development of social networks provides a unique source for analyzing human dynamics in the modern age. In this paper, we analyze the top-one Internet forum in China ("Tianya Club") and identify the statistical properties of hotspots, which ...

The richness of user-centric information gathered by modern devices can be used to keep track of memorable events, therefore acting as a prosthesis of the prone-to-forget human memory. We propose to combine virtual and physical sensors from mobile devices ...

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 ...

In this paper, we propose a hybrid spatio-semantic model and a computing platform for trajectories of moving objects. Our hybrid model can represent trajectories in terms of both spatio and semantic mobility characteristics, supporting different levels of ...

Zhixian Yan

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Semantic Trajectories : Computing and Understanding Mobility Data

Semantic Trajectories Modeling and Analysis

Automatic Construction and Multi-level Visualization of Semantic Trajectories

SeTraStream: Semantic-Aware Trajectory Construction over Streaming Movement Data

SeMiTri: A Framework for Semantic Annotation of Heterogeneous Trajectories

An Adaptive Approach for Online Segmentation of Multi-Dimensional Mobile Data

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

Semantic trajectories: Mobility data computation and annotation

Mining Complex Activities in the Wild via a Single Smartphone Accelerometer

DIII-D research towards establishing the scientific basis for future fusion reactors

Energy-Efficient Continuous Activity Recognition on Mobile Phones: An Activity-Adaptive Approach

An exploration with online complex activity recognition using cellphone accelerometer

Semantic Trajectories: Mobility Data Computation and Annotation

OptiMoS: Optimal Sensing for Mobile Sensors

A Hybrid Human Dynamics Model on Analyzing Hotspots in Social Networks

MemorySense: Reconstructing and Ranking User Memories on Mobile Devices

Deriving Semantic Sensor Metadata from Raw Measurements

Energy-Efficient Opportunistic Collaborative Sensing

A Hybrid Model and Computing Platform for Spatio-Semantic Trajectories

Memo-it: Don’t write your diary, Sense it