Indoor people localization and tracking using an energy harvesting smart floor

Contigiani, Marco; Frontoni, Emanuele; Mancini, Adriano; Gatto, Andrea

doi:10.1109/mesa.2014.6935623

Cited by 8 publications

(4 citation statements)

References 9 publications

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“…In their work, the authors have considered fall detection using specially adapted carpets with piezo-resistive pressure sensors embedded within them. Similar study was also done by Contigiani et al [24], which used piezo-electric wire lattice, inside the carpet, as a tracking modality.…”

Section: Other Modalitiessupporting

confidence: 58%

Sensor Modalities and Fusion for Robust Indoor Localisation

Kozłowski¹,

Santos-Rodríguez²,

Piechocki³

2019

ICST Transactions on Ambient Systems

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The importance of accurate and efficient positioning and tracking is widely understood. However, there is a pressing lack of progress in the standardisation of methods, as well as generalised framework of their evaluation. The aim of this survey is to discuss the currently prevalent and emerging types of sensors used for location estimation. The intent of this review is to take account of this taxonomy and to provide a wider understanding of the current state-of-the-art. To that end, we outline various sensor modalities, as well as popular fusion and integration techniques, discussing how their combinations can help in various application settings. Firstly, we present the fundamental mechanics behind sensors employed by the localisation community. Furthermore we outline the formal theory behind prominent fusion methods and provide exhaustive implementation examples of each. Finally, we provide points for future discussion regarding localisation sensing, fusion and integration methods.to user's preference and experience. This makes the relative selection space large, and frequently open to interpretation with regard to available resources and constraints.Whilst the survey literature pertaining to localisation systems and methods is large [54,171,181], there exists very little in the way of localisation-centric sensor utilisation. This encompasses the use of bespoke [39] or off-the-shelf [13,118] sensors, specifically for the use of location estimation, robustification and optimisation. This area is extensive [20,35,57,83,136,146], yet very often bundled along with localisation technology surveys, without subsequent scrutiny. We aim to close this gap, by reviewing sensors, their fusion and utilisation as applied to localisation, in contrast to localisation methods, technologies and implementations themselves.Most of the existing localisation surveys include technology-specific reviews [30,54,92,181]. They concentrate upon the methods and algorithms related to indoor localisation [30,92], techniques and technologies [181]. Some work also addresses localisation from the perspective of the device itself, such as smartphones [171]. Xiao et al. study [171] is the most closely related work to our proposed examination. The main difference is, that instead of reviewing the devices as

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Section: Other Modalitiessupporting

confidence: 58%

Sensor Modalities and Fusion for Robust Indoor Localisation

Kozłowski¹,

Santos-Rodríguez²,

Piechocki³

2019

ICST Transactions on Ambient Systems

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“…Smart flooring allows for such a purpose without requiring the adoption of intrusive video technologies [ 28 , 29 , 30 ]. To deal with power consumption constraints, the triboelectric effect can be leveraged as well: triboelectrification, which is increasingly exploited for energy harvesting [ 31 ], has been shown to be suitable for footstep recognition and fall detection [ 32 , 33 ] and indoor localization as well [ 34 ]. In Ref.…”

Section: Methodsmentioning

confidence: 99%

IoT Smart Flooring Supporting Active and Healthy Lifestyles

Cocconcelli

Matrella

Mora

et al. 2023

Sensors

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The lack of physical exercise is among the most relevant factors in developing health issues, and strategies to incentivize active lifestyles are key to preventing these issues. The PLEINAIR project developed a framework for creating outdoor park equipment, exploiting the IoT paradigm to build “Outdoor Smart Objects” (OSO) for making physical activity more appealing and rewarding to a broad range of users, regardless of their age and fitness. This paper presents the design and implementation of a prominent demonstrator of the OSO concept, consisting of a smart, sensitive flooring, based on anti-trauma floors commonly found in kids playgrounds. The floor is equipped with pressure sensors (piezoresistors) and visual feedback (LED-strips), to offer an enhanced, interactive and personalized user experience. OSOs exploit distributed intelligence and are connected to the Cloud infrastructure by using a MQTT protocol; apps have then been developed for interacting with the PLEINAIR system. Although simple in its general concept, several challenges must be faced, related to the application range (which called for high pressure sensitivity) and the scalability of the approach (requiring to implement a hierarchical system architecture). Some prototypes were fabricated and tested in a public environment, providing positive feedback to both the technical design and the concept validation.

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“…It was decided to operate with sinusoidal load, with frequency 1 Hz avoiding the original peak since the shoes are suitable for normal walking and not for running. The shoe was mounted on a form with a joint that allows a rotation between the front and rear of the foot further details can be found in [ 34 ]). The contact angle between the abutment plane of the sole and the floor was 20

; by proceeding with the application of the load, the contact plane (ground) is lowered rotating around a pivot axis coinciding with intersection between the ground plane and the sole.…”

Section: Smart Objectsmentioning

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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Indoor people localization and tracking using an energy harvesting smart floor

Cited by 8 publications

References 9 publications

Sensor Modalities and Fusion for Robust Indoor Localisation

Sensor Modalities and Fusion for Robust Indoor Localisation

IoT Smart Flooring Supporting Active and Healthy Lifestyles

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

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