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Selected Papers from UCAmI 2017 – the 11th International Conference on Ubiquitous Computing and Ambient Intelligence

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (25 April 2018) | Viewed by 67533

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Special Issue Editors

Dr. José Bravo

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Guest Editor

Department of Information Systems and Technologies, University of Castilla–La Mancha, 13071 Ciudad Real, Spain
Interests: ubiquitous computing; ambient intelligence; AAL & m-Health
Special Issues, Collections and Topics in MDPI journals

Dr. Gabriela Marín-Raventós

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Guest Editor

Programa de Posgrado en Computación e Informática (PPCI) y Centro de Investigaciones en Tecnologías de la Información y Comunicación (CITIC), Universidad de Costa Rica, San Jose, Costa Rica
Interests: Smart Cities; Human Computer Interaction; Decision Support Systems; Gender in IT; Digital Equity

Special Issue Information

Dear Colleagues,

The 11th International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2017) will take place in Philadelphia (Pennsylvania, USA), 7–10 November, 2017.

Over the years, the UCAmI conference has dedicated a significant part of its background and scope to promote the last research efforts and advances in Sensor Technologies. This trend continues growing in UCAmI 2017, as confirmed by the increasing number of related contributions and topics. Authors of the selected papers are invited to submit the extended versions of their original papers and contributions regarding the following topics:

Design and implementation of wearable sensors and embedded technologies in ambient assisted living contexts.
Sensors for environmental monitoring.
Mobile Ad-Hoc and wireless sensor networks.
Use of sensors and actuator devices in ubiquitous environments and other technological solutions.
Implementation, deployment, and evaluation of sensor systems.
Tangible and natural user interfaces.
Internet of Things. Technological implementations using smart devices for sensing or actuation.
mHealth. Smart environments for health.

Dr. José Bravo
Dr. Gabriela Marín-Raventós
Guest Editors

Manuscript Submission Information

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Keywords

Ambient Intelligence
Smart devices
Smart Environments
Sensor-based Interactions
Ambient Assisted Living
Wearable Sensors
Sensor Networks
mHealth

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Published Papers (10 papers)

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Research

14 pages, 5180 KiB

Open AccessArticle

A Distributed Model for Stressors Monitoring Based on Environmental Smart Sensors

by Alberto De Ramón-Fernández, Daniel Ruiz-Fernández, Diego Marcos-Jorquera and Virgilio Gilart-Iglesias

Sensors 2018, 18(6), 1935; https://doi.org/10.3390/s18061935 - 14 Jun 2018

Cited by 3 | Viewed by 3132

Abstract

Nowadays, in many countries, stress is becoming a problem that increasingly affects the health of people. Suffering stress continuously can lead to serious behavioral disorders such as anxiety or depression. Every person, in his daily routine, can face many factors which can contribute to increase his stress level. This paper describes a flexible and distributed model to monitor environmental variables associated with stress, which provides adaptability to any environment in an agile way. This model was designed to transform stress environmental variables in value added information (key stress indicator) and to provide it to external systems, in both proactive and reactive mode. Thus, this value-added information will assist organizations and users in a personalized way helping in the detection and prevention of acute stress cases. Our proposed model is supported by an architecture that achieves the features above mentioned, in addition to interoperability, robustness, scalability, autonomy, efficient, low cost and consumption, and information availability in real time. Finally, a prototype of the system was implemented, allowing the validation of the proposal in different environments at the University of Alicante. Full article

(This article belongs to the Special Issue Selected Papers from UCAmI 2017 – the 11th International Conference on Ubiquitous Computing and Ambient Intelligence)

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25 pages, 8242 KiB

Open AccessArticle

Sensing and Storing the Blood Pressure Measure by Patients through A Platform and Mobile Devices ^†

by Vladimir Villarreal, Mel Nielsen and Manuel Samudio

Sensors 2018, 18(6), 1805; https://doi.org/10.3390/s18061805 - 3 Jun 2018

Cited by 6 | Viewed by 5073

Abstract

In this article, we present a platform that allows for the integration of different applications for the follow-up of patients with chronic diseases. We developed two elements: a mobile and a web application. The mobile application allows the capture and processing of vital signs for patients with high blood pressure (hypertension). This application allows for the patient to store the data obtained, provides historical information and trends of the stored measures, and provides alerts and recommendations according to ranges of measures that were obtained. The web application allows the doctor and patients to obtain updated information of the disease behavior through the measures obtained. We used different biometric devices including an efimomanometer, glucometer, scale, and a thermometer with a wi-fi connection. Through this web application, we also generated information about average measures at a given time, by age, by region, and by a specific date. The developed system was evaluated in a medical center with different types of patients. Full article

(This article belongs to the Special Issue Selected Papers from UCAmI 2017 – the 11th International Conference on Ubiquitous Computing and Ambient Intelligence)

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21 pages, 5659 KiB

Open AccessArticle

Precision Agriculture Design Method Using a Distributed Computing Architecture on Internet of Things Context

by Francisco Javier Ferrández-Pastor, Juan Manuel García-Chamizo, Mario Nieto-Hidalgo and José Mora-Martínez

Sensors 2018, 18(6), 1731; https://doi.org/10.3390/s18061731 - 28 May 2018

Cited by 172 | Viewed by 20290

Abstract

The Internet of Things (IoT) has opened productive ways to cultivate soil with the use of low-cost hardware (sensors/actuators) and communication (Internet) technologies. Remote equipment and crop monitoring, predictive analytic, weather forecasting for crops or smart logistics and warehousing are some examples of these new opportunities. Nevertheless, farmers are agriculture experts but, usually, do not have experience in IoT applications. Users who use IoT applications must participate in its design, improving the integration and use. In this work, different industrial agricultural facilities are analysed with farmers and growers to design new functionalities based on IoT paradigms deployment. User-centred design model is used to obtain knowledge and experience in the process of introducing technology in agricultural applications. Internet of things paradigms are used as resources to facilitate the decision making. IoT architecture, operating rules and smart processes are implemented using a distributed model based on edge and fog computing paradigms. A communication architecture is proposed using these technologies. The aim is to help farmers to develop smart systems both, in current and new facilities. Different decision trees to automate the installation, designed by the farmer, can be easily deployed using the method proposed in this document. Full article

(This article belongs to the Special Issue Selected Papers from UCAmI 2017 – the 11th International Conference on Ubiquitous Computing and Ambient Intelligence)

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18 pages, 6518 KiB

Open AccessArticle

Collaborative Working Architecture for IoT-Based Applications

by Higinio Mora, María Teresa Signes-Pont, David Gil and Magnus Johnsson

Sensors 2018, 18(6), 1676; https://doi.org/10.3390/s18061676 - 23 May 2018

Cited by 22 | Viewed by 7059

Abstract

The new sensing applications need enhanced computing capabilities to handle the requirements of complex and huge data processing. The Internet of Things (IoT) concept brings processing and communication features to devices. In addition, the Cloud Computing paradigm provides resources and infrastructures for performing the computations and outsourcing the work from the IoT devices. This scenario opens new opportunities for designing advanced IoT-based applications, however, there is still much research to be done to properly gear all the systems for working together. This work proposes a collaborative model and an architecture to take advantage of the available computing resources. The resulting architecture involves a novel network design with different levels which combines sensing and processing capabilities based on the Mobile Cloud Computing (MCC) paradigm. An experiment is included to demonstrate that this approach can be used in diverse real applications. The results show the flexibility of the architecture to perform complex computational tasks of advanced applications. Full article

(This article belongs to the Special Issue Selected Papers from UCAmI 2017 – the 11th International Conference on Ubiquitous Computing and Ambient Intelligence)

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21 pages, 2953 KiB

Open AccessArticle

Strategies to Improve Activity Recognition Based on Skeletal Tracking: Applying Restrictions Regarding Body Parts and Similarity Boundaries

by Carlos Gutiérrez-López-Franca, Ramón Hervás and Esperanza Johnson

Sensors 2018, 18(5), 1665; https://doi.org/10.3390/s18051665 - 22 May 2018

Cited by 3 | Viewed by 4034

Abstract

This paper aims to improve activity recognition systems based on skeletal tracking through the study of two different strategies (and its combination): (a) specialized body parts analysis and (b) stricter restrictions for the most easily detectable activities. The study was performed using the Extended Body-Angles Algorithm, which is able to analyze activities using only a single key sample. This system allows to select, for each considered activity, which are its relevant joints, which makes it possible to monitor the body of the user selecting only a subset of the same. But this feature of the system has both advantages and disadvantages. As a consequence, in the past we had some difficulties with the recognition of activities that only have a small subset of the joints of the body as relevant. The goal of this work, therefore, is to analyze the effect produced by the application of several strategies on the results of an activity recognition system based on skeletal tracking joint oriented devices. Strategies that we applied with the purpose of improve the recognition rates of the activities with a small subset of relevant joints. Through the results of this work, we aim to give the scientific community some first indications about which considered strategy is better. Full article

(This article belongs to the Special Issue Selected Papers from UCAmI 2017 – the 11th International Conference on Ubiquitous Computing and Ambient Intelligence)

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20 pages, 1808 KiB

Open AccessArticle

Flying Real-Time Network to Coordinate Disaster Relief Activities in Urban Areas

by Matias Micheletto, Vinicius Petrucci, Rodrigo Santos, Javier Orozco, Daniel Mosse, Sergio F. Ochoa and Roc Meseguer

Sensors 2018, 18(5), 1662; https://doi.org/10.3390/s18051662 - 22 May 2018

Cited by 23 | Viewed by 5343

Abstract

While there have been important advances within wireless communication technology, the provision of communication support during disaster relief activities remains an open issue. The literature in disaster research reports several major restrictions to conducting first response activities in urban areas, given the limitations of telephone networks and radio systems to provide digital communication in the field. In search-and-rescue operations, the communication requirements are increased, since the first responders need to rely on real-time and reliable communication to perform their activities and coordinate their efforts with other teams. Therefore, these limitations open the door to improvisation during disaster relief efforts. In this paper, we argue that flying ad-hoc networks can provide the communication support needed in these scenarios, and propose a new solution towards that goal. The proposal involves the use of flying witness units, implemented using drones, that act as communication gateways between first responders working at different locations of the affected area. The proposal is named the Flying Real-Time Network, and its feasibility to provide communication in a disaster scenario is shown by presenting both a real-time schedulability analysis of message delivery, as well as simulations of the communication support in a physical scenario inspired by a real incident. The obtained results were highly positive and consistent, therefore this proposal represents a step forward towards the solution of this open issue. Full article

(This article belongs to the Special Issue Selected Papers from UCAmI 2017 – the 11th International Conference on Ubiquitous Computing and Ambient Intelligence)

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18 pages, 6054 KiB

Open AccessArticle

Traceability in Patient Healthcare through the Integration of RFID Technology in an ICU in a Hospital

by María Martínez Pérez, Carlos Dafonte and Ángel Gómez

Sensors 2018, 18(5), 1627; https://doi.org/10.3390/s18051627 - 19 May 2018

Cited by 27 | Viewed by 6389

Abstract

Patient safety is a principal concern for health professionals in the care process and it is, therefore, necessary to provide information management systems to each unit of the hospital, capable of tracking patients and medication to reduce the occurrence of adverse events and therefore increase the quality of care received by patients during their stay in hospital. This work presents a tool for the Intensive Care Unit (ICU), a key service with special characteristics, which computerises and tracks admissions, care plans, vital monitoring, the prescription and medication administration process for patients in this service. To achieve this, it is essential that innovative and cutting-edge technologies are implemented such as Near Field Communication (NFC) technology which is now being implemented in diverse environments bringing a range of benefits to the tasks for which it is employed. Full article

(This article belongs to the Special Issue Selected Papers from UCAmI 2017 – the 11th International Conference on Ubiquitous Computing and Ambient Intelligence)

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27 pages, 24496 KiB

Open AccessArticle

m-Health: Lessons Learned by m-Experiences

by José Bravo, Ramón Hervás, Jesús Fontecha and Iván González

Sensors 2018, 18(5), 1569; https://doi.org/10.3390/s18051569 - 15 May 2018

Cited by 25 | Viewed by 6943

Abstract

m-Health is an emerging area that is transforming how people take part in the control of their wellness condition. This vision is changing traditional health processes by discharging hospitals from the care of people. Important advantages of continuous monitoring can be reached but, in order to transform this vision into a reality, some factors need to be addressed. m-Health applications should be shared by patients and hospital staff to perform proper supervised health monitoring. Furthermore, the uses of smartphones for health purposes should be transformed to achieve the objectives of this vision. In this work, we analyze the m-Health features and lessons learned by the experiences of systems developed by MAmI Research Lab. We have focused on three main aspects: m-interaction, use of frameworks, and physical activity recognition. For the analysis of the previous aspects, we have developed some approaches to: (1) efficiently manage patient medical records for nursing and healthcare environments by introducing the NFC technology; (2) a framework to monitor vital signs, obesity and overweight levels, rehabilitation and frailty aspects by means of accelerometer-enabled smartphones and, finally; (3) a solution to analyze daily gait activity in the elderly, carrying a single inertial wearable close to the first thoracic vertebra. Full article

(This article belongs to the Special Issue Selected Papers from UCAmI 2017 – the 11th International Conference on Ubiquitous Computing and Ambient Intelligence)

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16 pages, 5155 KiB

Open AccessArticle

Distributed Fast Self-Organized Maps for Massive Spectrophotometric Data Analysis ^†

by Carlos Dafonte, Daniel Garabato, Marco A. Álvarez and Minia Manteiga

Sensors 2018, 18(5), 1419; https://doi.org/10.3390/s18051419 - 3 May 2018

Cited by 6 | Viewed by 3779

Abstract

Analyzing huge amounts of data becomes essential in the era of Big Data, where databases are populated with hundreds of Gigabytes that must be processed to extract knowledge. Hence, classical algorithms must be adapted towards distributed computing methodologies that leverage the underlying computational power of these platforms. Here, a parallel, scalable, and optimized design for self-organized maps (SOM) is proposed in order to analyze massive data gathered by the spectrophotometric sensor of the European Space Agency (ESA) Gaia spacecraft, although it could be extrapolated to other domains. The performance comparison between the sequential implementation and the distributed ones based on Apache Hadoop and Apache Spark is an important part of the work, as well as the detailed analysis of the proposed optimizations. Finally, a domain-specific visualization tool to explore astronomical SOMs is presented. Full article

(This article belongs to the Special Issue Selected Papers from UCAmI 2017 – the 11th International Conference on Ubiquitous Computing and Ambient Intelligence)

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22 pages, 1983 KiB

Open AccessArticle

Using Ontologies for the Online Recognition of Activities of Daily Living

by Alberto G. Salguero, Macarena Espinilla, Pablo Delatorre and Javier Medina

Sensors 2018, 18(4), 1202; https://doi.org/10.3390/s18041202 - 14 Apr 2018

Cited by 18 | Viewed by 4418

Abstract

The recognition of activities of daily living is an important research area of interest in recent years. The process of activity recognition aims to recognize the actions of one or more people in a smart environment, in which a set of sensors has been deployed. Usually, all the events produced during each activity are taken into account to develop the classification models. However, the instant in which an activity started is unknown in a real environment. Therefore, only the most recent events are usually used. In this paper, we use statistics to determine the most appropriate length of that interval for each type of activity. In addition, we use ontologies to automatically generate features that serve as the input for the supervised learning algorithms that produce the classification model. The features are formed by combining the entities in the ontology, such as concepts and properties. The results obtained show a significant increase in the accuracy of the classification models generated with respect to the classical approach, in which only the state of the sensors is taken into account. Moreover, the results obtained in a simulation of a real environment under an event-based segmentation also show an improvement in most activities. Full article

(This article belongs to the Special Issue Selected Papers from UCAmI 2017 – the 11th International Conference on Ubiquitous Computing and Ambient Intelligence)

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