PHAT: Physical Human Activity Tester

Campillo-Sánchez, Pablo; Gómez-Sanz, Jorge J.; Botía, Juan A.

doi:10.1007/978-3-642-40846-5_5

Cited by 10 publications

(7 citation statements)

References 8 publications

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“…An interesting project that also used multiple sensors from Android devices is Social Ambient Assisted Living or SociAAL (), where virtual living labs were created using a framework specifically designed for this purpose, called PHAT (Physical Human Activity Tester) [17]. The devices in the project used Android and were able to take advantage of all sensors that can be found on such devices, including camera, microphone, accelerometer, user input, etc.…”

Section: Related Workmentioning

confidence: 99%

Human Physical Activity Recognition Using Smartphone Sensors

Voicu

Dobre

Băjenaru

et al. 2019

Sensors

136

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Because the number of elderly people is predicted to increase quickly in the upcoming years, “aging in place” (which refers to living at home regardless of age and other factors) is becoming an important topic in the area of ambient assisted living. Therefore, in this paper, we propose a human physical activity recognition system based on data collected from smartphone sensors. The proposed approach implies developing a classifier using three sensors available on a smartphone: accelerometer, gyroscope, and gravity sensor. We have chosen to implement our solution on mobile phones because they are ubiquitous and do not require the subjects to carry additional sensors that might impede their activities. For our proposal, we target walking, running, sitting, standing, ascending, and descending stairs. We evaluate the solution against two datasets (an internal one collected by us and an external one) with great effect. Results show good accuracy for recognizing all six activities, with especially good results obtained for walking, running, sitting, and standing. The system is fully implemented on a mobile device as an Android application.

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Section: Related Workmentioning

confidence: 99%

Human Physical Activity Recognition Using Smartphone Sensors

Voicu

Dobre

Băjenaru

et al. 2019

Sensors

136

View full text Add to dashboard Cite

show abstract

“…Other social simulation environments can assist in the development of IoT systems by simulating artificial societies of users immersed into the intelligent environment and generating sensors events [ 95 ]. Although social simulation has been used for testing a number of closed systems, mainly in the emergency management scope, the general use of this technology for providing general AmI systems with automatic testing is still a novel field with few contributions such as UbikSim [ 96 ] and Phat [ 97 ] simulators.…”

Section: State Of the Artmentioning

confidence: 99%

A Methodology for the Design of Application-Specific Cyber-Physical Social Sensing Co-Simulators

Bordel

Sánchez-Picot

2017

Sensors

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Cyber-Physical Social Sensing (CPSS) is a new trend in the context of pervasive sensing. In these new systems, various domains coexist in time, evolve together and influence each other. Thus, application-specific tools are necessary for specifying and validating designs and simulating systems. However, nowadays, different tools are employed to simulate each domain independently. Mainly, the cause of the lack of co-simulation instruments to simulate all domains together is the extreme difficulty of combining and synchronizing various tools. In order to reduce that difficulty, an adequate architecture for the final co-simulator must be selected. Therefore, in this paper the authors investigate and propose a methodology for the design of CPSS co-simulation tools. The paper describes the four steps that software architects should follow in order to design the most adequate co-simulator for a certain application, considering the final users’ needs and requirements and various additional factors such as the development team’s experience. Moreover, the first practical use case of the proposed methodology is provided. An experimental validation is also included in order to evaluate the performing of the proposed co-simulator and to determine the correctness of the proposal.

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“…Experts and engineers design the solution, then the code and relevant hardware is produced, and finally it is tested. Research [5] has already discussed the problems regarding the high costs and failures of projects following these approaches. The use of VLLs tries to mitigate them.…”

Section: Related Workmentioning

confidence: 99%

“…The research on Virtual LLs (VLLs) [5] addresses these issues through the development of very accurate software simulations of LL. The AAL system is deployed in the VLL as it would be in a LL.…”

Section: Introductionmentioning

confidence: 99%

Development of Simulations for Ambient Assisted Living through Pattern Repositories

Fuentes-Fernández¹,

Gómez-Sanz²

2017

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

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Abstract-Ambient Assisted Living (AAL) pursues providing an autonomous and satisfactory life to people through technology, independently of their actual conditions. Its developments usually require testing protoypes with real users in Living Labs (LL). This makes projects expensive. Virtual LLs (VLLs) try to address theses issues by using simulations for requirements elicitation and the initial testing of solutions. These simulations frequently require considering social aspects, e.g. relationships, culture, or decision making. These are recurrent and quite applicationindependent aspects for AAL. Our work proposes social properties as patterns that represent these aspects and that can be plugged-in in simulations. The knowledge for these properties is extracted following the Activity Theory (AT) paradigm from Social Sciences. Their specification uses models and transformations (e.g. to generate other models or code) following Model-Driven Engineering (MDE) practices. This faciliates their understading and use in simulation development. A case study on AAL for ageing illustrates the approach.

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PHAT: Physical Human Activity Tester

Cited by 10 publications

References 8 publications

Human Physical Activity Recognition Using Smartphone Sensors

Human Physical Activity Recognition Using Smartphone Sensors

A Methodology for the Design of Application-Specific Cyber-Physical Social Sensing Co-Simulators

Development of Simulations for Ambient Assisted Living through Pattern Repositories

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