Efficient Traffic Simulation Using Busses as Active Sensor Network

Catani, Ludovico; Frontoni, Emanuele; Zingaretti, Primo; Pasquale, Guido Di

doi:10.1115/detc2011-49013

Cited by 8 publications

(3 citation statements)

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“…The system is described as a wireless sensor network (WSN) consisted of spatially distributed autonomous sensors. The star topology of WSN allows to achieve a high degree of scalability and a high level of controllability, as already verified in previous studies [15,16]. Inside a point of sale, several different RF boards can be installed interconnected to the wireless control gear via the 433/868/915 radio frequency communication that is actually unused by the other monitoring systems already in stores.…”

Section: Shelf Detector Hardwarementioning

confidence: 70%

Information Management for Intelligent Retail Environment: The Shelf Detector System

et al. 2014

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Shelf-out-of-stock is one of the leading motivations of technology innovation in the shelf of the future. The Shelf Detector project described in this paper aims to solve the problem of data knowledge in the shelf-out-of-stock problem. This paper is mainly focused on the information layer of the system and main novelties illustrated in this work are in the information field demonstrating the huge number of insights that can be derived from the use of such a tool able to gather data in real time from the store. The tool presented is the first being installed for a long time in a high number of stores and products, demonstrating the ability to gather data and extract interesting insights. This paper aims to demonstrate the feasibility and the scalability of our system in providing a high number of data and interesting insights for store and marketing teams. The cloud based architecture developed and tested in this project is a key feature of our system together with the ability to collect data from a distributed sensor network.

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Section: Shelf Detector Hardwarementioning

confidence: 70%

Information Management for Intelligent Retail Environment: The Shelf Detector System

et al. 2014

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“…2) made of distributed autonomous sensors controlled from a RF trasmitter that embeds the logic part of the low level software. The topology of the network allows to achieve a high degree of scalability and a high level of controllability, as already verified in previous studies of our research group Catani et al (2010Catani et al ( , 2011. In a point of sale, several RF boxes can be installed, each connected to the control gear via radio frequency communication.…”

Section: Shelf Detector Sensormentioning

confidence: 74%

Design and test of a real-time shelf out-of-stock detector system

et al. 2016

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“…The first part of the activity recognition method is based on the water filling algorithm to identify people from a vertical depth image even when they are moving in group inside the home. Details of the tracking algorithm can be found in [21] and other aspects and applications of this approach in different scenarios are detailed in [22][23][24]. This last aspect of group behaviors will be better investigated in future tests in real scenario and the results on this side are not reported in this paper even if the methodology will be the same described here following.…”

Section: Users Tracking and Behaviorsmentioning

confidence: 96%

RGBD Sensors for Human Activity Detection in AAL Environments

Frontoni

Mancini

Zingaretti

2014

Ambient Assisted Living

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This paper aims to propose a novel idea of an embedded intelligent system where a low cost embedded vision system can analyze human behaviors to obtain interactivity and statistical data, mainly devoted to human behavior analysis in Ambient Assisted Living environments. We construct a system that uses vertical RGBD sensor for people tracking and interaction analysis, where the depth information has been used to remove the affect of the appearance variation and to evaluate users activities inside the home and in front of the fixtures. Also group interactions are monitored and analyzed with the main goal of having a better knowledge of the users activities, using real data in real time. All information coming from this human behavior analysis tool can be used to provide basic data gathered in real time for an Ambient Assisted Living environment. Even if preliminary, the results are convincing and most of all the general architecture is affordable in this specific application, robust, easy to install and to maintain and low cost.

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Efficient Traffic Simulation Using Busses as Active Sensor Network

Cited by 8 publications

References 0 publications

Information Management for Intelligent Retail Environment: The Shelf Detector System

Information Management for Intelligent Retail Environment: The Shelf Detector System

Design and test of a real-time shelf out-of-stock detector system

RGBD Sensors for Human Activity Detection in AAL Environments

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