RGBD Sensors for Human Activity Detection in AAL Environments

Frontoni, Emanuele; Mancini, Adriano; Zingaretti, Primo

doi:10.1007/978-3-319-01119-6_13

Cited by 9 publications

(4 citation statements)

References 24 publications

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“…The main goal of this measure is to offer back to retailer or producers an exact measure of SOOS to consider, with real data coming from a real store, how many hours products are not available for customers. Preliminary research in intelligent retail environments allowed to test the system (Frontoni et al , 2014aMancini et al (2013), considering also other aspects and applications of this approach in different situations. In Frontoni et al (2014b) a detailed description of data gathered from the system and their semantic is presented.…”

Section: Soos Characterizationmentioning

confidence: 99%

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

et al. 2016

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Section: Soos Characterizationmentioning

confidence: 99%

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

et al. 2016

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“…The system is installed and functioning in six countries, in 50 stores and detects OOS of 4000 products performing a continuous monitoring. Preliminary studies in intelligent retail environments allowed to test the system [12][13][14], considering also other aspects and applications of this approach in different situations.…”

Section: Oos Extentmentioning

confidence: 99%

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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“…For this purpose, Ambient Assisted Living (AAL) applications have attracted a growing attention in the scientific community since they involve emerging and innovative technological solutions, providing embedded systems in the home environment. The aim of AAL is to improve the quality of life, to reduce costs for independent living [ 5 , 6 , 7 , 8 ], to increase the self-confidence and the autonomy of elderly or ill people while enhancing their security.…”

Section: Introductionmentioning

confidence: 99%

HDOMO: Smart Sensor Integration for an Active and Independent Longevity of the Elderly

Frontoni

Pollini

Russo

et al. 2017

Sensors

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The aim of this paper is to present the main results of HDOMO, an Ambient Assisted Living (AAL) project that involved 16 Small and Medium Enterprises (SMEs) and 2 research institutes. The objective of the project was to create an autonomous and automated domestic environment, primarily for elderly people and people with physical and motor disabilities. A known and familiar environment should help users in their daily activities and it should act as a virtual caregiver by calling, if necessary, relief efforts. Substantially, the aim of the project is to simplify the life of people in need of support, while keeping them autonomous in their private environment. From a technical point of view, the project provides the use of different Smart Objects (SOs), able to communicate among each other, in a cloud base infrastructure, and with the assisted users and their caregivers, in a perspective of interoperability and standardization of devices, usability and effectiveness of alarm systems. In the state of the art there are projects that achieve only a few of the elements listed. The HDOMO project aims to achieve all of them in one single project effectively. The experimental trials performed in a real scenario demonstrated the accuracy and efficiency of the system in extracting and processing data in real time to promptly acting, and in providing timely response to the needs of the user by integrating and confirming main alarms with different interoperable smart sensors. The article proposes a new technique to improve the accuracy of the system in detecting alarms using a multi-SO approach with information fusion between different devices, proving that this architecture can provide robust and reliable results on real environments.

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RGBD Sensors for Human Activity Detection in AAL Environments

Cited by 9 publications

References 24 publications

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

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

Information Management for Intelligent Retail Environment: The Shelf Detector System

HDOMO: Smart Sensor Integration for an Active and Independent Longevity of the Elderly

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