PIR Probability Model for a Cost/Reliability Tradeoff Unobtrusive Indoor Monitoring System

Fabio Veronese; Sara Comai; Simone Mangano; Matteo Matteucci; Fabio Salice

Smart Objects and Technologies for Social Good. Second International Conference, GOODTECHS 2016, Venice, Italy, November 30 – December 1, 2016, Proceedings

Research Article

PIR Probability Model for a Cost/Reliability Tradeoff Unobtrusive Indoor Monitoring System

Download

207 downloads

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1007/978-3-319-61949-1_7,
    author={Fabio Veronese and Sara Comai and Simone Mangano and Matteo Matteucci and Fabio Salice},
    title={PIR Probability Model for a Cost/Reliability Tradeoff Unobtrusive Indoor Monitoring System},
    proceedings={Smart Objects and Technologies for Social Good. Second International Conference, GOODTECHS 2016, Venice, Italy, November 30 -- December 1, 2016, Proceedings},
    proceedings_a={GOODTECHS},
    year={2017},
    month={7},
    keywords={Pyroelectric infrared sensors PIR sensor model Presence detection},
    doi={10.1007/978-3-319-61949-1_7}
}

Fabio Veronese
Sara Comai
Simone Mangano
Matteo Matteucci
Fabio Salice
Year: 2017
PIR Probability Model for a Cost/Reliability Tradeoff Unobtrusive Indoor Monitoring System
GOODTECHS
Springer
DOI: 10.1007/978-3-319-61949-1_7

Fabio Veronese¹^,*, Sara Comai¹^,*, Simone Mangano¹^,*, Matteo Matteucci¹^,*, Fabio Salice¹^,*

1: Politecnico di Milano, Polo Territoriale di Como

*Contact email: fabio.veronese@polimi.it, sara.comai@polimi.it, simone.mangano@polimi.it, matteo.matteucci@polimi.it, fabio.salice@polimi.it

Abstract

PIR (Pyroelectric InfraRed) sensors can be used to detect the presence of humans without the need for them to wear any device. By construction, the fields of view of the sensors are not uniform both in terms of vision space and of sensitivity. The aim of this work is twofold: to provide a probabilistic model of the sensors’ detection sensitivity with respect to the movement of the person and of his/her emission surface, and to identify the probability of detection within an area covered by multiple PIR sensors. This allows the computation of the coverage of the PIRs and their optimal arrangement that maximizes the probability of detection of the person.

Keywords: Pyroelectric infrared sensors PIR sensor model Presence detection

Published: 2017-07-28
Appears in: SpringerLink

: http://dx.doi.org/10.1007/978-3-319-61949-1_7