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Über dieses Buch

This book constitutes the refereed proceedings of the International Summit on Applications for Future Internet, AFI 2016, held in Puebla, Mexico, in May 2016.
The 21 papers presented were carefully selected from 29 submissions and focus on the usage of Future Internet in the biological and health sciences as well as the increased application of IoT devices in fields like smart cities, health and agriculture.

Inhaltsverzeichnis

Frontmatter

SCiFI 2016

Frontmatter

Towards a Generic Ontology for Video Surveillance

Abstract
Video surveillance is an important problem that has been studied for several years. Nowadays, in the context of smart cities, intelligent video surveillance is an important topic which has several subproblems which need to be solved and then integrated. For example, on one side there are several algorithms for detection, recognition and tracking of objects and people. On the other side, it is necessary to recognize not only objects and persons but complex behaviors (fights, thefts, attacks). To solve these challenges, the use of ontologies has been proposed as a tool to reduce this gap between low and high level information. In this work, we present the foundations of an ontology to be used in an intelligent video surveillance system.
Pablo Hernandez-Leal, Hugo Jair Escalante, L. Enrique Sucar

Smart Cities for the Rest of Us

Abstract
More than half of the world’s population live in cities. Smart cities could help to solve the present and upcoming problems that affects the people’s well-being. However, developing regions face big challenges, like fighting poverty, jeopardizing the smart cities adoption. In this paper, we propose to design technologies for the problems of our developing regions. We describe our current work, designing and developing a wearable device for measuring poverty trough the analysis of social interaction and outlining its evaluation in the neighborhood of Camino Verde in Tijuana. We conclude by discussing our vision on the importance of designing technologies for our specific problems, culture and way of life.
Miguel Ángel Ylizaliturri-Salcedo, J. Antonio García-Macías, Raúl Cardenas-Osuna, Leocundo Aguilar-Noriega

Smart Disaster Response Through Localized Short-Term Cooperation

Abstract
As the information and communication technology (ICT) has advanced, research on smart cities that take advantage of ICT has been extensively conducted to improve resource management and enhance citizen’s quality of life. Disaster management is a critical component in smart cities to secure citizen’s safety. From experiences with recent disasters such as tsunamis, earthquakes, and hurricanes, we can easily find evidence that shows an urgent need for intelligent disaster management systems. In a disaster situation, a disaster response system must address not only long-term needs that require continuous disaster recovery, but also short-term needs that require ephemeral cooperation between people and smart devices nearby. However, existing disaster-responsive applications have been based on pre-established long-term relationships and focused on communication among human users. To address the limitation of disaster management, in this paper, the smart disaster response system (DRS) is proposed. The Smart DRS allows connectivity among users and sensing devices with short-term relationships based on geographical location within. The approach allows effective sharing of disaster information and immediate cooperation within communities in a manner that reconciles with requirements of security and privacy.
Youna Jung

Towards a Smart Highway Lighting System Based on Road Occupancy: Model Design and Simulation

Abstract
Energy saving is a major aspect of smart cities, so optimizing highway lighting is essential, as it consumes considerable amounts of energy. However, there is a remarkable potential for reducing this consumption through smart lighting techniques. This paper introduces preliminary design and simulation for a smart highway lighting management system based on road occupancy. Wireless Sensors Network (WSN) detects the presence of vehicles along the road, and controls lamps accordingly. The system is simulated and optimized using a realistic probabilistic model for vehicles traffic, taking the advantage of simulation to provide estimation for expected energy saving rates; in contrary to previous works depending only on rough calculations or real-time results after implementation. According to simulation results, the proposed system can save up to 57.4% of power consumption compared to conventional lighting systems.
Ahmad M. Mustafa, Omar M. Abubakr, Ahmed H. Derbala, Essam Ahmed, Bassem Mokhtar

FIoTA 2016

Frontmatter

Exploiting Data of the Twitter Social Network Using Sentiment Analysis

Abstract
Social Networks nowadays are producing an enormous quantity of data, this data transformed into information could be useful for the decision support systems. A new emerging technology denominated as Sentiment Analysis or Opinion Meaning extracts the opinion or sentiment of a particular text. The Twitter social network is a source of valuable information in simple text and appropriated to use this technology. In this paper is described the process used to select the most suitable algorithms to analyze tweets for particular words written in Spanish, also the results obtained by every algorithm are reported.
David Gonzalez-Marron, David Mejia-Guzman, Angelica Enciso-Gonzalez

Decentralized Control for Power Distribution with Ancillary Lines in the Smart Grid

Abstract
Energy management is a key topic for today’s society, and a crucial challenge is to shift from a production system based on fossil fuel to sustainable energy. A key ingredients for this important step is the use of a highly automated power delivery network, where intelligent devices can communicate and collaborate to optimize energy management.
This paper investigates a specific model for smart power grids initially proposed by Zdeborov and colleagues [12] where back up power lines connect a subset of loads to generators so to meet the demand of the whole network. Specifically, we extend such model to minimize \(CO_{2}\) emissions related to energy production.
In more detail, we propose a formalization for this problem based on the Distributed Constraint Optimization Problem (DCOP) framework and a solution approach based on the min-sum algorithm. We empirically evaluate our approach on a set of benchmarking power grid instances comparing our proposed solution to simulated annealing. Our results, shows that min-sum favorably compares with simulated annealing and it represents a promising solution method for this model.
Michele Roncalli, Alessandro Farinelli

An Experimental Evaluation of IoT Technologies in Precision Viticulture

Abstract
There is no doubt that the introduction of IoT-assisted applications will become an invaluable asset to optimize farm performance. Through the data collected by sensors deployed in the fields together with other sources of information and facilities, farmers will have at their disposal a set of tools allowing them to make informed decisions on the day-to-day operation. Since 2005, a multidisciplinary team of researchers from the Albacete Research Institute of Informatics and the School of Agronomical Engineers of the University of Castilla La Mancha (UCLM) has been exploring the use of information and communication technologies in the agricultural industry. This paper reports on the main findings acquired through the deployment and experimental evaluation of IoT technologies in a vineyard. Our results also provide insight into future directions on the use of IoT technologies in precision viticulture.
Luis Orozco-Barbosa, Francisco Montero García, Antonio Brasa Ramos, Francisco Montero Riquelme

GARMDROID: IoT Potential Security Threats Analysis Through the Inference of Android Applications Hardware Features Requirements

Abstract
Applications and services based on the Internet of Things (IoT) are increasingly vulnerable to disruption from attack or information theft. Developers and researchers attempt to prevent the growth of such disruption models, mitigate and limit their impact. Meeting these challenges requires understanding the characteristics of things and the technologies that empower the IoT since traditional protection mechanisms are not enough. Moreover, as the growth in mobile device market is pushing the deployment of the IoT, tools and mechanisms to evaluate, analyze and detect security threats in these devices are strongly required. In this context, this paper presents a web tool, named GARMDROID, aimed to help IoT software developers and integrators to evaluate IoT security threats based on the visualization of Android application hardware requests. This procedure is based on the static analysis of permissions requested by Android applications.
Abraham Rodríguez-Mota, Ponciano Jorge Escamilla-Ambrosio, Jassim Happa, Eleazar Aguirre-Anaya

Making the Intelligent Home Smart Through Touch-Control Trigger-Action Programming

Abstract
We introduces a new UI model of Trigger-Action Programming (TAP), that allows users to program through touch-control interfaces to create complicated tasks easily. We present three different user interfaces (UI), for each user interface, we analyze its advantages, limitations, and potential utility. We explain how our UIs can mitigate the problems of TAP caused by ambiguity and demonstrate why our UIs will benefit people without programming backgrounds.
Guan Wang, Michael L. Littman

Optimal Scheduling of On/Off Cycles: A Decentralized IoT-Microgrid Approach

Abstract
The current energy scenario requires actions towards the reduction of energy consumptions and the use of renewable resources. To this end, the energy grid is evolving towards a distributed architecture called Smart Grid (SG). Moreover, new communication paradigms, such as the Internet of Things (IoT), are being applied to the SG providing advanced communication capabilities for management and control. In this context, a microgrid is a self-sustained network that can operate connected to the SG (or in isolation). In such networks, the long-term scheduling of on/off cycles of devices is a problem that has been commonly addressed by centralized approaches. In this paper, we propose a novel IoT-microgrid architecture to model the long-term optimization scheduling problem as a distributed constraint optimization problem (DCOP). We compare different multi-agent DCOP algorithms using different window sizes showing that the proposed architecture can find optimal and near-optimal solutions for a specific case study.
Fernando Lezama, Jorge Palominos, Ansel Y. Rodríguez-González, Alessandro Farinelli, Enrique Munoz de Cote

CML-WSN: A Configurable Multi-layer Wireless Sensor Network Simulator

Abstract
Wireless Sensor Networks (WSNs) have large applications in environments where access to human cannot be constant or where reliable and timely information is required to support decisions. WSNs must show high reliability, robustness, availability of information, monitoring capabilities, self-organization, among other aspects. Also, engineering requirements, such as low-cost implementation, operation, and maintenance are necessary. In this context, a simulator is a powerful tool for analyzing and improving network technologies used as a first step to investigate protocol design and performance test on large-scale systems without the need of real implementation. In this paper, we present a Configurable Multi-Layer WSN (CML-WSN) simulator. The CML-WSN simulator incorporates a configurable energy model to support any sensor specification as a one of its main features. The CML-WSN simulator is useful because it allows exploring prototypes with much less cost and time compared to the requirements needed in real networks implementations.
Carolina Del-Valle-Soto, Fernando Lezama, Jafet Rodriguez, Carlos Mex-Perera, Enrique Munoz de Cote

Conceptual Model for the Explanation of the Phenomenon of Radical Innovation in the Disruption of the Internet of Things, on Scales of Smart Objects, Homes and Cities

Abstract
The Internet of Things is an emerging, mainly technology driven, field, seen as a radical modifier of the semantic relationships between people, objects and cities. Based on the empirical study of various products and systems within the Internet of Things environment, a conceptual model is proposed to explain the phenomenon of Design (Meaning) Driven Innovation and its particular variables, where the radical innovations, make sense in society. It is argued that the variables: Social Willingness to Change, Network of Visionaries, Technology and Meanings are four actors for the construction of new and radical meanings in products.
David Soasti Bareta, Gerardo Muñiz

MAIoT - An IoT Architecture with Reasoning and Dialogue Capability

Abstract
This paper describes MAIoT, a Multiagent-based Architecture which aims to coordinate Internet of Things (IoT) devices. MAIoT is distinguished by its capabilities for allowing dialogues between IoT devices. To support theses dialogue capabilities, the IoT devices are wrapped into rational agents with reasoning and dialogue capabilities.
Juan Carlos Nieves, Daniel Andrade, Esteban Guerrero

FI-eHealth 2016

Frontmatter

An Internet System to Self-monitoring and Assess Feeding in Young Mexicans

Abstract
Obesity and metabolic syndrome pave the way to type 2 diabetes and cardiovascular disease. Obesity and metabolic syndrome prevalence are high (39% and 13%, respectively) in young Mexican population where feeding habits are one of the main factors leading to these maladies. So, a plausible strategy to address the problem is to suggest young to review and control their feeding habits. We present an internet system to register, self-monitoring, and assess feeding habits for young Mexican to review and control them. This system is organized in eight questionnaires, one of them about food frequencies. Also anthropometrics data such as weight, height, waist and hip circumference are registered to assess and follow-up weight condition, through body mass index, and waist/hip ratio. The user could generate a pdf report that automatically summarizes all the data captured in the questionnaires in two pages. A follow up charts of some parameters are also available for monthly data collection once the user fills the system. More than 2,000 young students have used this system since 2013 and is open universally (www.​misalud.​abacoac.​org) to all young people wanting to self-monitoring her/his feeding habits, and obtaining general health recommendations.
Miguel Murguía-Romero, Bernardo Serrano-Estrada, Itzell A. Gallardo-Ortíz, J. Rafael Jiménez-Flores, Rafael Villalobos-Molina

A Conversational Agent for Use in the Identification of Rare Diseases

Abstract
This paper presents work in progress on implementing a conversational agent, Dr. Rachael, in the form of a virtual caregiver, for use in helping to identify rare diseases. The rationale for the system is grounded in the fact that rare disorders by their very nature are difficult to diagnose unless the caregiver or doctor is familiar with a wide range of these conditions. The conversational agent uses unstructured free-flowing natural language together with a large database of rare disorders, and is easily updatable by human caregivers without any technical expertise. Matching of users’ comments with database entries is performed using a general cognition engine; which is able to understand natural language regardless of specific wording or grammar. In this paper we give a comprehensive background to and an overview of the system, with a focus on aspects pertaining to natural language processing and user interaction. The system is currently only implemented for English.
Ana Olivia Caballero Lambert, Cesar Horacio Torres Montañez, Monica Bueno Martinez, Marcelo Funes-Gallanzi

Using Intermediate Models and Knowledge Learning to Improve Stress Prediction

Abstract
Motor activity in physical and psychological stress exposure has been studied almost exclusively with self-assessment questionnaires and from reports that derive from human observer, such as verbal rating and simple descriptive scales. However, these methods are limited in objectively quantifying typical behaviour of stress. We propose to use accelerometer data from smartphones to objectively quantify stress levels. Used data was collected in real-world setting, from 29 employees in two different organisations over 5 weeks. To improve classification performance we propose to use intermediate models. These intermediate models represent the mood state of a person which is used to build the final stress prediction model. In particular, we obtained an accuracy of 78.2 % to classify stress levels.
Alban Maxhuni, Pablo Hernandez-Leal, Eduardo F. Morales, L. Enrique Sucar, Venet Osmani, Angelica Muńoz-Meléndez, Oscar Mayora

Sensor Abstracted Extremity Representation for Automatic Fugl-Meyer Assessment

Abstract
Given its virtually algorithmic process, the Fugl-Meyer Assessment (FMA) of motor recovery is prone to automatization reducing subjectivity, alleviating therapists’ burden and collaterally reducing costs. Several attempts have been recently reported to achieve such automatization of the FMA. However, a cost-effective solution matching expert criteria is still unfulfilled, perhaps because these attempts are sensor-specific representation of the limb or have thus far rely on a trial and error strategy for building the underpinning computational model. Here, we propose a sensor abstracted representation. In particular, we improve previously reported results in the automatization of FMA by classifying a manifold embedded representation capitalizing on quaternions, and explore a wider range of classifiers. By enhancing the modeling, overall classification accuracy is boosted to 87% (mean: 82% ± 4.53:) well over the maximum reported in literature thus far 51.03% (mean: 48.72 ± std: 2.10). The improved model brings automatic FMA closer to practical usage with implications for rehabilitation programs both in ward and at home.
Patrick Heyer, Felipe Orihuela-Espina, Luis R. Castrejón, Jorge Hernández-Franco, Luis Enrique Sucar

FINE 2016

Frontmatter

A Platform for Creating Augmented Reality Content by End Users

Abstract
We present work in progress towards the development of a platform for the creation of augmented reality (AR) content by the end user. Based upon a review of existing AR authoring tools and scenarios we have envisioned in the context of smart cities, we have developed SituAR, an architecture for a platform in which the user is able to create AR content using multimedia elements. Our emphasis is on making augmented reality easier to put together and to empower users to become authors in AR scenarios. We also include social media elements for users to share, rank, and comment the content created in order to add new information and to facilitate interaction. This paper discusses the architecture of SituAR and its potential.
Fernando Vera, J. Alfredo Sánchez, Ofelia Cervantes

Strategic Learning Meta-model (SLM): Architecture of the Regulation Model (RM) Based on the Cloud Computing

Abstract
In this work we present the architecture of the Regulation Model (RM) as a third layer of the Strategic Learning Meta-model (SLM). The SLM conforms a personalized virtual learning environment that consists of three layers: The Intelligent Layer that includes a virtual learning environment, The Infrastructure Layer based on the Cloud Computing, and The Regulation Model. The RM is based on the Ned Herman’s Whole Brain Theory that divides the brain into four quadrants associated to thinking styles. The RM considers six components: (i) The teacher; (ii) The learner or student; (iii) The process facilitator; (iv) The emotional facilitator; (v) The didactic material; and (vi) The learning activities. Our experiments implement the RM and consider five test cases. The experimental results show an improvement in the final scoring of creative, logic and process thinking styles of undergraduate students.
Rafaela Blanca Silva-López, Oscar Herrera-Alcántara, Jalil Fallad-Chávez

Overview of a Framework for Ubiquitous User Models Interoperability

Abstract
Researchers in the user modeling community have been interested in sharing and reuse profile information from heterogeneous sources. Ubiquitous user model interoperability allows enrichment of adaptive systems obtaining a better understanding of the user, and decreases the effort associated with creating a user model. We present a framework that enables the interoperability between profile suppliers and consumers with a mixed approach that consist in central ubiquitous user model ontology and a process of concept alignment. The central ontology is a flexible representation of a ubiquitous user model to cope with the dynamicity of a distributed multi-application environment that provides mediation between profile suppliers and consumers. The process of concept alignment automatically discovers the semantic mappings in order to interpret the information from heterogeneous sources and integrate them into a ubiquitous user model.
María de Lourdes Martínez-Villaseñor, Miguel González-Mendoza

Backmatter

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