The Design of a Portable Kit of Wireless Sensors for Naturalistic Data Collection

Tapia, Emmanuel Munguia; Intille, Stephen; Lopez, Louis; Larson, Kent

doi:10.1007/11748625_8

Cited by 72 publications

(51 citation statements)

References 12 publications

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“…In particular, we focus on work using object usage (motion) detectors placed on large objects and furniture [1], body-worn accelerometers [5,4], magnetic reed switches [6,2], water/power system monitors [10] and wrist-worn RFID readers [8]. Prior work shows promising results for these methods.…”

Section: Related Workmentioning

confidence: 99%

“…The environment contains the following built-in wired sensors that were used in this work: 101 reed switch sensors installed on doors, cabinets, drawers and windows, electrical current flow sensors on 37 residential circuits, 36 temperature sensors, 10 humidity sensors, 6 light sensors, 1 barometric pressure sensor, 1 gas sensor and 14 water flow sensors. We also used 277 wireless object usage (motion) detection sensors [1] of three types: 265 "stick-on" object usage sensors that measure when objects move, 2 3-axis accelerometer sensors that are worn on limbs and measure limb movement at 20+Hz, and 10 wireless infra-red motion sensors that detect when there is motion in various regions of the condominium. The object usage sensors were placed on nearly all objects that might be manipulated ranging from doors and cabinets to remote controls for appliances.…”

Section: Sensing Environmentmentioning

confidence: 99%

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A Long-Term Evaluation of Sensing Modalities for Activity Recognition

Logan

Healey

Philipose

et al.

UbiComp 2007: Ubiquitous Computing

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268

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Abstract. We study activity recognition using 104 hours of annotated data collected from a person living in an instrumented home. The home contained over 900 sensor inputs, including wired reed switches, current and water flow inputs, object and person motion detectors, and RFID tags. Our aim was to compare different sensor modalities on data that approached "real world" conditions, where the subject and annotator were unaffiliated with the authors. We found that 10 infra-red motion detectors outperformed the other sensors on many of the activities studied, especially those that were typically performed in the same location. However, several activities, in particular "eating" and "reading" were difficult to detect, and we lacked data to study many fine-grained activities. We characterize a number of issues important for designing activity detection systems that may not have been as evident in prior work when data was collected under more controlled conditions.

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Section: Related Workmentioning

confidence: 99%

Section: Sensing Environmentmentioning

confidence: 99%

A Long-Term Evaluation of Sensing Modalities for Activity Recognition

Logan

Healey

Philipose

et al.

UbiComp 2007: Ubiquitous Computing

Self Cite

268

262

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“…For instance, in [Tapia et al, 2006], a sensor rich environment has been set for the collection of signals from 72 environmental and body sensors aiming to evaluate complex activities in an indoor location. In this work, we employ accelerometers and gyroscopes for the sensing human body motion.…”

Section: Wearable Sensorsmentioning

confidence: 99%

“…For example, the Opportunity Project has recorded a set of ADL in a sensor-rich environment using 72 environmental and body sensors. Similarly, other works have provided datasets such as [Tapia et al, 2006] and [Dernbach et al, 2012].…”

Section: Experimental Data Collectionmentioning

confidence: 99%

Energy-Efficient Technologies in Device-to-Device Based Proximity Service

Wang¹,

Vasilakos²,

Jin³

et al. 2017

Device-to-Device Based Proximity Service

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ADVERTIMENT. La consulta d'aquesta tesi queda condicionada a l'acceptació de les següents condicions d'ús: La difusió d'aquesta tesi per mitjà del servei TDX (www.tesisenxarxa.net) ha estat autoritzada pels titulars dels drets de propietat intel·lectual únicament per a usos privats emmarcats en activitats d'investigació i docència. No s'autoritza la seva reproducció amb finalitats de lucre ni la seva difusió i posada a disposició des d'un lloc aliè al servei TDX. No s'autoritza la presentació del seu contingut en una finestra o marc aliè a TDX (framing). Aquesta reserva de drets afecta tant al resum de presentació de la tesi com als seus continguts. En la utilització o cita de parts de la tesi és obligat indicar el nom de la persona autora.ADVERTENCIA. La consulta de esta tesis queda condicionada a la aceptación de las siguientes condiciones de uso: La difusión de esta tesis por medio del servicio TDR (www.tesisenred.net) ha sido autorizada por los titulares de los derechos de propiedad intelectual únicamente para usos privados enmarcados en actividades de investigación y docencia. No se autoriza su reproducción con finalidades de lucro ni su difusión y puesta a disposición desde un sitio ajeno al servicio TDR. No se autoriza la presentación de su contenido en una ventana o marco ajeno a TDR (framing). Esta reserva de derechos afecta tanto al resumen de presentación de la tesis como a sus contenidos. En la utilización o cita de partes de la tesis es obligado indicar el nombre de la persona autora. WARNING.On having consulted this thesis you're accepting the following use conditions: Spreading this thesis by the TDX (www.tesisenxarxa.net) service has been authorized by the titular of the intellectual property rights only for private uses placed in investigation and teaching activities. Reproduction with lucrative aims is not authorized neither its spreading and availability from a site foreign to the TDX service. Introducing its content in a window or frame foreign to the TDX service is not authorized (framing). This rights affect to the presentation summary of the thesis as well as to its contents. In the using or citation of parts of the thesis it's obliged to indicate the name of the author The first stage to accomplish HAR requires to make observations from ambient or wearable sensor technologies. However, in the second case, the search for pervasive, unobtrusive, low-powered, and low-cost devices for achieving this challenging task still has not been fully addressed. In this thesis, we explore the use of smartphones as an alternative approach for performing the identification of physical activities. These self-contained devices, which are widely available in the market, are provided with embedded sensors, powerful computing capabilities and wireless communication technologies that make them highly suitable for this application.This work presents a series of contributions regarding the development of HAR systems with smartphones. In the first place we propose a fully operational system that recognizes in real...

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“…The sensor nodes transmit the sensed data three times (default ZigBee protocol value that could be increased, but was found to be sufficient for our purpose considering the probability of correctly receiving 113488 packets at the receiver node) to the receiver node before a time-out. According to [21], the probability of correctly receiving packet at the receiver node increases with the number of retransmissions. This is important to consider since channel noise and collisions are issues that exist in real world scenarios and need to be handled.…”

Section: A Wireless Personal Area Networkmentioning

confidence: 99%