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Author

Oliveri

Bio: Oliveri is an academic researcher. The author has contributed to research in topics: Wireless sensor network & Object detection. The author has an hindex of 1, co-authored 2 publications receiving 5 citations.

Papers
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Proceedings Article
01 Jan 2009
TL;DR: This paper addresses the real-time localization of transceiver-free targets is addressed by means of learning by example methodology that exploits the received signal strength indicator available at the nodes of a wireless sensor network as input data.
Abstract: The increasing demand in homeland security speeds up the development of innovative and non-invasive systems to localize and track moving objects in complex environments. In this paper the real-time localization of transceiver-free targets is addressed by means of learning by example methodology that exploits the received signal strength indicator available at the nodes of a wireless sensor network as input data. This approach uses neither dedicated sensors nor active devices put on the target to localize both idle and moving objects. The definition of a customized classifier during an offline training procedure enables the real-time generation of a probability map of presence by processing the output of the support vector machine. Some selected experimental results validate the effectiveness of the proposed methodology applied in real scenarios.

4 citations

Proceedings Article
Viani, Oliveri, Donelli, Lizzi, Rocca, Massa 
01 Jan 2010

1 citations


Cited by
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Proceedings ArticleDOI
17 Oct 2011
TL;DR: In this article, a WSN-based system for the prevention of road incident because of wildlife road crossing is presented, composed by a network of sensors and actuators in order to detect wildlife approaching the road and to warn the driver in real-time by means of light signal devices.
Abstract: In this paper a preliminary study of applying a WSN-based system for the prevention of road incident because of wildlife road crossing is presented. The proposed system is composed by a network of sensors and actuators in order to detect wildlife approaching the road and to warn the driver in real-time by means of light signal devices. The nodes of the network are installed on the road sides and wirelessly interconnected in order to share the sensed data. A remote control unit deals with the storage and the processing of the collected information. Starting from the detection events, the proposed system identifies the areas with higher probability of wildlife crossing by means of customized classification approaches. The capabilities of the proposed system have been preliminarily assessed by means of an experimental setup installed in a controlled environment located in Alps regions strongly affected by the problem of wildlife-vehicle collisions.

28 citations

Journal ArticleDOI
03 Jun 2021
TL;DR: An analysis of Wireless Sensor Network (WSN) security issues that take place due to eavesdropping using cumulative distribution, optimal sensors and round robin scheduling scheme to decrease the probability of interception and to equip secure connection between the nodes.
Abstract: This paper presents an analysis of Wireless Sensor Network (WSN) security issues that take place due to eavesdropping. The sensor-eavesdropper channels and the sensor sinks are exposed to generalized K-fading. Based on the physical layer security framework we use cumulative distribution, optimal sensors and round robin scheduling scheme to decrease the probability of interception and to equip secure connection between the nodes. For identifying the interception probability, a novel analytical methodology is present with simple analytical expressions. Moreover, diversity orders of scheduling schemes and asymptotic closed-form expressions are evaluated. Numerical results show the crucial result of shadowing and fading parameters of wiretap and main links, selected schemes on WSN security and network size. We have analyzed the output using Monte Carlo simulation and conclusions show the validation of the proposed work.

18 citations

Proceedings Article
11 Apr 2011
TL;DR: In this paper, a learning-by-example strategy was proposed to estimate the unknown relation between the input data and the target position inside the monitored domain, and the real-time capabilities of the proposed approach have been experimentally verified when dealing with heterogeneous target movements in standard indoor areas.
Abstract: In this work, the exploitation of wireless systems for non-cooperative target localization and tracking is investigated. The information about wireless links quality is available on most of commercially available network devices and represents the input of the proposed methodology. A real-time probability of presence is generated by means of a learning by example strategy that estimates the unknown relation between the input data and the target position inside the monitored domain. The real-time capabilities of the proposed approach have been experimentally verified when dealing with heterogeneous target movements in standard indoor areas.

10 citations

Journal ArticleDOI
TL;DR: In this paper idea of passive radar system based on popular wireless networks commonly named WIFI is presented and it is assumed, that all transmitters operate on the same band frequency and the passive radar receiver has to couple each transmission burst with transmitter position by decoding the physical address of transmitter from captured data stream.
Abstract: In this paper idea of passive radar system based on popular wireless networks commonly named WIFI is presented. In such an networks many transmitters operates in the same channel using multiple access. Wireless networks operating on frequencies 2.4GHz and 5GHz are very common today (IEEE 802.11 a/b/g/n). Classic passive radar determines bistatic distance and velocity by using cross-ambiguity function. To seek target position in XYZ space at least illumination of 3 different transmitters is required. In that paper it was assumed, that all transmitters operate on the same band frequency and the passive radar receiver has to couple each transmission burst with transmitter position by decoding the physical address of transmitter from captured data stream. Having most of the signal sources in our passive radar environment it is possible to detect and to localize objects of interest.

9 citations

Proceedings Article
08 Apr 2013
TL;DR: The experimental validation of a WSN-based smart system for the prevention of road incidents due to wildlife road crossing is presented and a selected set of results are reported to assess the capabilities and potentialities of the system.
Abstract: In this paper, the experimental validation of a WSN-based smart system for the prevention of road incidents due to wildlife road crossing is presented. The proposed wireless architecture integrates a multisensory hardware platform for the detection of movement patterns of wildlife along the monitored road sides. The adopted sensing technologies enable the extraction of heterogeneous movement features to be processed in real-time. The integration of data fusion strategies provides robust detection of warning events and the output triggers dedicated light signals when required. An experimental setup has been installed in real scenarios where the wildlife presence is detected. A selected set of results are reported to assess the capabilities and potentialities of the system.

6 citations