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PATH SIGNED

PAssive Tracking of people and things for physical beHavior analysis

Total Cost €

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EC-Contrib. €

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Partnership

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Project "PATH" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITA DEGLI STUDI DI FERRARA 

Organization address
address: VIA ARIOSTO 35
city: FERRARA
postcode: 44121
website: www.unife.it

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Italy [IT]
 Project website https://www.stefaniabartoletti.info/path
 Total cost 244˙269 €
 EC max contribution 244˙269 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2015
 Funding Scheme MSCA-IF-GF
 Starting year 2016
 Duration (year-month-day) from 2016-06-01   to  2019-05-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITA DEGLI STUDI DI FERRARA IT (FERRARA) coordinator 244˙269.00
2    MASSACHUSETTS INSTITUTE OF TECHNOLOGY US (CAMBRIDGE) partner 0.00

Map

 Project objective

The main goal of passive tracking of people and things (PATH) is to define a new paradigm for physical behavior inference, where the dynamics of physical entities are tracked with minimal implementation cost, maximal privacy preservation, and intrinsically protected secrecy. PATH relies on the detection, tracking, and behavior analysis of targets without active devices, by integrating such capabilities in infrastructures for the Internet of things (IOT) that are already present in a monitored environment. This enables several applications including visitor counting and flow monitoring. The objectives of PATH are: (i) to develop a framework for system design and analysis, as well as to derive fundamental limits; (ii) to devise advanced techniques for detection and exploitation of networks of opportunity; (iii) to develop inference techniques based on wireless networks properties for intrinsically secure tracking; (iv) to recognize new patterns related to targets dynamics based on signal feature extraction; (v) to establish a proof-of-concept for an industrial-driven use case.

PATH will enhance the potential of the experienced researcher (ER) by relying on: (i) the solid experience of the successful Ph.D. completed by the young ER, which included a year as a visiting student in the USA; (ii) a challenging, interdisciplinary, and multi-sectorial work program; (iii) a genuine mobility program with an outgoing phase at a top tier university, supervised by a world-renowned expert in the field, and with an incoming phase at a high ranked and growing research group; (iv) a secondment program at a leading industry in the field, which confirms the industrial interest and that is tailored to the ER, with an evident commitment in terms of supervision and infrastructures; (v) a rich, five-fold training program, not limited to training through research; (vi) an implementation plan agreed with an advisory board for an efficient achievement of the ambitious objectives.

 Publications

year authors and title journal last update
List of publications.
2019 Andrea Conti, Santiago Mazuelas, Stefania Bartoletti, William C. Lindsey, and Moe Z. Win
Soft-information for Localization-of-things
published pages: , ISSN: 0018-9219, DOI:
Proceedings of the IEEE 2019-09-02
2018 Stefania Bartoletti, Andrea Conti, Wenhan Dai, Moe Z. Win
Threshold Profiling for Wideband Ranging
published pages: 873-877, ISSN: 1070-9908, DOI: 10.1109/LSP.2018.2815692
IEEE Signal Processing Letters 25/6 2019-06-13
2018 Stefania Bartoletti, Nicolo Decarli, Davide Dardari, Marco Chiani, Andrea Conti
Order-of-Arrival of Tagged Objects
published pages: 185-196, ISSN: 2469-7281, DOI: 10.1109/JRFID.2018.2881708
IEEE Journal of Radio Frequency Identification 2/4 2019-08-05
2017 Stefania Bartoletti, Andrea Conti, Moe Z. Win
Device-Free Counting via Wideband Signals
published pages: 1163-1174, ISSN: 0733-8716, DOI: 10.1109/JSAC.2017.2680978
IEEE Journal on Selected Areas in Communications 35/5 2019-06-13
2018 Moe Z. Win, Florian Meyer, Zhenyu Liu, Wenhan Dai, Stefania Bartoletti, Andrea Conti
Efficient Multisensor Localization for the Internet of Things: Exploring a New Class of Scalable Localization Algorithms
published pages: 153-167, ISSN: 1053-5888, DOI: 10.1109/msp.2018.2845907
IEEE Signal Processing Magazine 35/5 2019-08-05

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The information about "PATH" are provided by the European Opendata Portal: CORDIS opendata.

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