Publications by Saket Sathe | EPFL Graph Search

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In recent years we are experiencing a dramatic increase in the amount of available time-series data. Primary sources of time-series data are sensor networks, medical monitoring, financial applications, news feeds and social networking applications. Availab ...

As the Sensor Internet starts to become reality, increasingly heterogeneous sensor networks are becoming interconnected into federated sensor networks and provide huge volumes of sensor data for a variety of applications to large user communities, such as ...

Participatory sensing has emerged as a new data collection paradigm, in which humans use their own devices (cell phone accelerometers, cameras, etc.) as sensors. This paradigm enables to collect a huge amount of data from the crowd for world-wide applicati ...

Although efficient processing of probabilistic databases is a well-established field, a wide range of applications are still unable to benefit from these techniques due to the lack of means for creating probabilistic databases. In fact, it is a challenging ...

Modern positioning technologies enable collecting trajectories from moving objects across different locations over time, typically containing time-varying measurement errors of positioning systems. Unfortunately, current models on uncertain trajectories ar ...

Computing statistical measures for large databases of time series is a fundamental primitive for querying and mining time-series data [1]–[6]. This primitive is gaining importance with the increasing number and rapid growth of time series databases. In thi ...

Efficiently querying data collected from Large-area Communitydriven Sensor Networks (LCSNs) is a new and challenging problem. In our previous works, we proposed adaptive techniques for learning models (e.g., statistical, non-parametric, etc.) from such dat ...

Effectively managing the data generated by community-driven mobile geo-sensor networks is a new and challenging problem. One important step for managing and querying sensor network data is to create abstractions of the data in the form of models. These mod ...

This paper outlines a vision for community-driven sensing of our environment. At its core, community sensing is a dynamic new form of mobile geosensor network. We believe that community sensing networks, in order to be widely deployable and sustainable, ne ...

Effectively managing the data generated by Large-area Community driven Sensor Networks (LCSNs) is a new and challenging prob- lem. One important step for managing and querying such sensor network data is to create abstractions of the data in the form of mo ...

A method of data retrieval from a data repository in response to a query having either list of keywords and/or list of attribute-value pairs, the method comprising the steps of: providing an inverted index generated from the data repository, the inverted i ...

Crowdsensing applications are increasing at a tremendous rate. In crowdsensing, mobile sensors (humans, vehicle-mounted sensors, etc.) generate streams of information that is used for inferring high-level phenomena of interest (e.g, traffic jams, air pollu ...

The dramatic rise of time-series data in a variety of contexts, such as social networks, mobile sensing, data centre monitoring, etc., has fuelled interest in obtaining real-time insights from such data using distributed stream processing systems. One such ...

Saket Sathe

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Statistical Models for Querying and Managing Time-Series Data

Effective Metadata Management in Federated Sensor Networks

Towards Enabling Probabilistic Databases for Participatory Sensing

Creating Probabilistic Databases from Imprecise Time-Series Data

Managing Evolving Uncertainty in Trajectory Databases

A FFINITY: Efficiently Querying Statistical Measures on Time-Series Data

EnviroMeter: A Platform for Querying Community-Sensed Data

ConDense: Managing Data in Community-driven Mobile Geosensor Networks

OpenSense: open community driven sensing of environment

Effectively Modeling Data from Large-area Community Sensor Networks

Method of data retrieval, and search engine using such a method

On crowdsensed data acquisition using multi-dimensional point processes

Fast Distributed Correlation Discovery Over Streaming Time-Series Data