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User-Driven Distributed Pervasive Sensing: Themes: High Tech, Software Technology & Intelligent Systems

This project develops an algorithm for user-driven distributed pervasive sensing that collects environmental data without a central data collector. The algorithm is tuned by users and delivers timely and reliable information. It uses distributed convex optimization and will be tested on real devices and data within 10 years, when environmental information will be widely available from user devices. The lead researcher is Dr. Andrea Simonetto.

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Agustin A.
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108 views4 pages

User-Driven Distributed Pervasive Sensing: Themes: High Tech, Software Technology & Intelligent Systems

This project develops an algorithm for user-driven distributed pervasive sensing that collects environmental data without a central data collector. The algorithm is tuned by users and delivers timely and reliable information. It uses distributed convex optimization and will be tested on real devices and data within 10 years, when environmental information will be widely available from user devices. The lead researcher is Dr. Andrea Simonetto.

Uploaded by

Agustin A.
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Download as PDF, TXT or read online on Scribd
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9/12/2018 Pervasive Sensing

Technology Transfer Projects 

User-Driven Distributed Pervasive Sensing


Themes: High Tech, Software technology & Intelligent systems

Technology Readiness Level (TRL) Description TRL

Proof of principle
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Why?

Our algorithm senses the environment without the need for a central data collector. It is tuned by
the users and delivers the requested environmental information timely and reliably.

How?

The algorithm is designed using the analytical tools of distributed convex optimisation. Then, it will
be embedded on real devices and tested on real environmental data.

When?

In less than 10 years, environmental information will available in any location, at any time, and will
be generated, aggregated, and processed by the user's devices.

Contact

dig-it@tudelft.nl

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Lead researcher

Dr. Andrea Simonetto

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