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Andrea Molino

Researcher at Polytechnic University of Turin

Publications -  38
Citations -  283

Andrea Molino is an academic researcher from Polytechnic University of Turin. The author has contributed to research in topics: Field-programmable gate array & Software-defined radio. The author has an hindex of 10, co-authored 38 publications receiving 264 citations. Previous affiliations of Andrea Molino include Concordia University (Saint Paul, Minnesota) & University of California.

Papers
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Journal ArticleDOI

Participatory patterns in an international air quality monitoring initiative

TL;DR: Results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution indicate that direct involvement can enhance learning and environmental awareness.
Book ChapterDOI

The Use of Micro-UAV to Monitor Active Landslide Scenarios

TL;DR: A procedure to use micro-UAV (Unmanned Aerial Vehicles) to perform photogrammetry survey and monitoring analysis in landslide scenarios to show the results and the potential of this methodology in real landslide scenarios.
Proceedings Article

N-Gene GNSS software receiver for acquisition and tracking algorithms validation

TL;DR: The solutions adopted for the signal acquisition and tracking tested on N-Gene, a GNSS receiver completely designed in software, able to run in real-time on a common Personal Computer, are presented.
Journal ArticleDOI

Monitoring and managing of a micro-smart grid for renewable sources exploitation in an agro-industrial site

TL;DR: In this article, the authors presented a monitoring and managing procedure of an electricity micro-smart grid in a small agro-food enterprise in order to minimize the energy exchange between the local grid and the public utility grid and optimize the exploitation of renewable sources.
Journal ArticleDOI

FPGA implementation of time-frequency analysis algorithms for laser welding monitoring

TL;DR: This work presents the FPGA implementation of time-frequency analysis algorithms as an effective solution compared with pure software implementation based on different modern processors.