Ebook: Intelligent Environments 2017

Intelligent Environments (IEs) refer to physical spaces into which IT and other pervasive computing technology are woven and used to achieve specific goals for the user, the environment or both. IEs have the ultimate objective of enriching user experience, better manage, and increase user awareness of, that environment.

Imagination, invention and innovation are key ideas which mark the path of research and development in the field of Intelligent Environments. The accelerating pace of today's technological developments urges the materialization of IEs with such innovative ideas and the whole community, from scientists and researchers to the general public, yearns for this. As Albert Einstein says in “Einstein on Cosmic Religion and Other Opinions and Aphorisms” (pp. 49, Covici-Friede, Inc., New York, 1931),

“Imagination is more important than knowledge. For knowledge is limited, whereas imagination embraces the entire world, stimulating progress, giving birth to evolution. It is, strictly speaking, a real factor in scientific research.”

The 13th International Conference on Intelligent Environments focuses on the development of advanced intelligent environments, as well as newly emerging and rapidly evolving topics. In the present edition, we are pleased to include in this volume the proceedings of the following workshops, which emphasize multi-disciplinary and transversal aspects of IEs, as well as cutting-edge topics:

• 6th International Workshop on the Reliability of Intelligent Environments (WoRIE'17);

• 1st International Workshop on Intelligent Systems for Agriculture Production and Environment Protection (ISAPEP'17);

• 1st Workshop on Citizen Centric Smart Cities Solutions (CCSCS'17);

• 1st International Workshop on Advanced Multiple Access in Mobile Telecommunications (AMAMT'17).

As it can be understood from this list, these workshops, organized in conjunction with IE'17 main conference, provide a forum for researchers, scientists, engineers and developers to engage in many interesting, imaginative and active discussions that will engage further research in these key areas of Intelligent Environments.

The proceedings contain a series of contributions reflecting the latest research developments in IEs and related areas, focusing on stretching the borders of the current state of the art and contributing to an ever increasing establishment of IEs in the real world.

It is our aim to inspire readers in their own work, in the hope that reading these proceedings plants the seeds for new, interesting, and original ideas.

We would like to thank all the contributing authors, as well as the members of the Organizing Committees and Program Committees of the workshops for their highly valuable work, which contributed to the success of the Intelligent Environments 2017 event. We are also grateful to the conference organizers and local staff that worked thoroughly for the success of this event.

Thank you for your esteemed help, without which this event would not have been possible.

As a final note, the Workshops Chairs would like to take the opportunity to thank Professor Jason J. Jung and Professor Andrés Muñoz, the general chairs of IE'17, and Professor Paulo Novais and Professor Sangwook Kim, the program chairs of IE'17 for their trust in our work, and all the other members of the IE'17 organization for the confidence they placed on us.

We are looking forward to seeing you all in Seoul actively participating in these exciting workshops.

August 2017

Cesar Analide, University of Minho, Portugal

Pankoo Kim, Chosun University, Republic of Korea

Workshops Chairs of IE'17

Thanks to the significant achievement in IoT, artificial intelligence, and other computer technologies, we envision big changes in our everyday lives in the near future. However, before we accept such a new world, we should ensure that having intelligence around us is not harmful to human lives. Here, we focus on dark sides of technological achievement that would harm to our future, and share some technical insights on safety supports for reliable intelligent environments.

The development of capable smartphones and other portable devices has ushered new ways of communication and collaboration. For example, smartphones are widely used for sharing files with friends and colleagues at meeting or a conference. In this case, conventionally, short-range radio, such as Bluetooth or Wi-Fi are used. Encrypted data can be send via Bluetooth radio and be received by any devices in a 10m distance. In public places, this increases the likelihood of security breach and communication eavesdrop as the data may be intercepted by any device within range. In this paper, we propose to improve security by controlling the communication range via acoustic waves. Unlike radio waves, acoustic waves' propagation range can be controlled by modifying their amplitude; thus, it is possible to reduce the data sharing range specifically to a range of a specific device. Our preliminary tests by sharing data between two Nexus 5 smartphones indicate that it is possible to unidirectional control the sharing range while sharply reducing any possibility to eavesdrop on the communication. This increased the communication security since only devices within the specified range and direction were aware of the data sharing.

With the development of sensor network and embedded system, Cyber-Physical System (CPS) integrating computation, communication and control is becoming the focus of attention gradually. Obvious problems have emerged when CPS applying to various industries. It is crucial that the designed CPS can work as expect. A growing number of researchers are concerned about the property verification of CPS since verification technique has played a key role in improving the security and reliability of systems. It is a commonly used method that transforming generic model to formal model for verification. A formal method of theorem proving has well applied to verify CPS based on Differential Dynamic Logic (DDL) which operating model named Hybrid Program proposed by A. Platzer. This paper introduced HybridUML to model CPS, presented a method to verify CPS using DDL, where model was transformed from HybridUML to Hybrid Program, and verified a case study with the resulting model finally.

Visible and near infrared (Vis-NIR) spectroscopy is a non-destructive analytical method that can be used to complement, enhance or potentially replace conventional methods of soil analysis. The aim of this research was to predict the particle size distribution (PSD) of soils using a Vis-NIR) spectrophotometry in one irrigate field having a vertisol clay texture in the Karacabey district of Bursa Province, Turkey. A total of 86 soil samples collected from the study area were subjected to optical scanning in the laboratory with a portable, fiber-type Vis–NIR spectrophotometer (AgroSpec, tec5 Technology for Spectroscopy, Germany). Before the partial least square regression (PLSR) analysis, the entire reflectance spectra were randomly split into calibration (80%) and validation (20%) sets. A leave-one-out cross-validation PLSR analysis was carried out using the calibration set with Unscrambler® software, whereas the model prediction ability was tested using the validation (prediction) set. Models developed were used to predict sand and clay content using on-line collected spectra from the field. Results showed an “excellent” laboratory prediction performance for both sand (R² = 0.81, RMSEP = 3.84% and RPD = 2.32 in cross-validation; R² = 0.90, RMSEP = 2.91% and RPD = 2.99 in the prediction set) and clay (R² = 0.86, RMSEP = 3.4% and RPD = 2.66 in cross validation; R² = 0.92, RMSEP = 2.67% and RPD = 3.14 in the prediction set). Modelling of silt did not result in any meaningful correlations. Less accurate on-line predictions were recorded compared to the laboratory results, although the on-line predictions were very good (RPD = 2.24-2.31). On-line predicted maps showed reasonable spatial similarity to corresponding laboratory measured maps. This study proved that soil sand and clay content can be successfully measured and mapped using Vis-NIR spectroscopy under both laboratory and on-line scanning conditions.

This paper provides a bare-bone introduction to evolutionary and bio-inspired metaheuristic in the context of environmental greenhouse control. Besides presenting general evolutionary algorithm principles, specific details are provided regarding the genetic algorithm, particle swarm optimization and differential evolution techniques. A review of these algorithms within greenhouse control applications is presented, both for single and multiple objectives, as well as current trends.

Social media can serve to contribute to situation awareness, which involves the perception and comprehension of the reality around us, so that future actions can be projected. For example, Twitter can be used as a real-time channel of communication to report on environmentally-related problems. The goal of this paper is to describe a knowledge-based system that is able to detect such problems, so that a protocol of action can be developed. The evaluation of the system demonstrated that our symbolic approach to problem detection can outperform supervised classification methods.

Precision agriculture enables the dynamic use of technologies to boost up crop production, increase crop yield and at the same time decrease the input variables. Yield monitoring and estimation are considered to be the major steps to implement site-specific crop management or precision farming. Unmanned aerial vehicle (UAV) imaging based automatic rice yield estimation in different growing stages, could be a solution. In this work, we proposed a color-based segmentation algorithm that used Lab color space and k-mean clustering techniques to detect rice grain panicles area. Segmentation of grain from the image background was carried out in two steps. In the first step, a filter was applied to RGB (red, green and blue) images to remove noise and the image converted to Lab color space. The k-means clustering was applied to organize all colors contained in both a and b layers. The pixels were clustered based on their color and special features. In the second step, the variation between colors was measured and labelling of pixels was completed by cluster index. The clustering index was joined to a specific region and the images segmented using color information. The proposed method showed that rice grain can be segmented and that rice grains panicles numbers and area can be estimated from UAV images. The comparison provided significant results. The correlation between the ground truth measure and proposed method for rice grains panicles number and area were found to be around 0.931 and 0.842 respectively.

Soil libraries represent an invaluable resource in terms of research, management or planning. However, the access to such libraries and selection of soils is often tedious and time consuming thus limiting their usefulness. In this study we propose an ontology-based approach for an efficient and intuitive selection and classification of soils. For this test, a soil library of 458 soils from Australia was used. An ontology was then developed to model the fundamentals concepts and relationships found in the data. The basic capabilities of the ontology are shown to select samples with certain values for a number of attributes. In addition, an inference process known as realization is tested to automatically assign individuals to concepts, in our present case to a soil texture class or soil order (the latter known as soil classification). Results show the potential of ontology approaches to select samples from large libraries in an efficient and intuitive way. In addition, and through the use of reasoning processes, we were able to classify soils from different orders and textural classes with accuracy higher than 80% in most cases. This represents an additional application of ontology approaches to produce hidden data from the original data set.

The aim of this study is to design, implement and evaluate an image-based software solution for automatic detection of abnormal on paddy fields that damages by insects, diseases. The methodology of the proposed is composed of third phases. This content is a combined approach for the segmentation of images. In the first phase, watershed segmentation algorithm, second phases, using the K-means clustering algorithm and final in the third phases reducing noise in image gradients. We have taken paddy filed images as a case study and evaluated the proposed approach using abnormal area paddy field images for the pest prediction. In experimental results, indicate that the proposed approach can automatic detection and of abnormal area on paddy fields for the pest prediction. In conclusion, the proposed methods show that detect abnormal region efficiently.

The determination of carbon is one of the most important in soil analysis. However traditional techniques are costly and time consuming. In this manuscript we propose an alternative predictive approach based on portable mid-infrared spectroscopy data modeled by machine learning techniques. We evaluate the performance of different machine learning models and sample size to predict soil carbon in 457 Australian soils. The results show a good performance of the models. All models are validate by statistical tests. The best performing technique with a 99% of confidence level is the Gaussian Process providing a 98% of accuracy for the prediction of soil carbon. Moreover, this technique is the most robust for the different sample sizes tested. When compared with the commonly used Partial Least Squares Regression technique, the machine learning approaches provide more successful and balanced results.

This study aims to detect changes in vegetation and evaluate the geographic distribution of two different mangroves of Rio Grande do Norte, Brazil. Data were obtained through visual interpretation of high resolution satellite imagery (Astrium / QuickBird / DigitalGlobe / Landsat) available in Google EarthTM. The visual interpretation resulted in the demarcation of polygons representing vegetated area of mangroves. Data were compared to the images of global distribution of mangroves in 2011, provided by United Nations Environment Programme of Global Conservation Monitoring Centre using GIS. The mangrove forest present in Guaraíras lagoon complex had an increase in vegetated area over the last four years of 5.01 km (52.73%) while the mangrove forest located in Potengi estuary presented a 1.03km (6.06%) of forest gain in the same period. Anthropogenic activities such as shrimp farming, artificial construction, tourism and discharge of effluents are directly related with the conservation status of Brazilian mangroves. The mangrove ecosystem present in the metropolitan region of the Rio Grande do Norte (largest population area), showed a slow growth rate, while the mangrove located further away from urban centers, showed impressive growth of vegetated area.

The purpose of this research is to develop a collaborative approach to control the parking in a city using IoT (Internet of Things). This approach is based on Bluetooth Low Energy (BLE) beacons to control the parking process without having to investment in sensors. Parking violations can be easily detected through the proposed collaborative process among user's mobile devices. A reward mechanism incentives users' participation. This approach uses an ad hoc network of users who send information to a central system regarding georeferenced beacon information. Comparing with previous payments associated with a vehicle, the approach can identify parking violations, e.g. parking without associated payment.

Data science is a revolution that is already changing the way we do business, healthcare, politics, education and innovation. There is a great variety of online courses, masters, degrees, and modules that address the teaching of this interdisciplinary field, where is a growing demand of professionals. However, data science pedagogy has repeated a number of patterns that can be detrimental to the student. This position paper describes an ongoing educational innovation project for the study of methods, experiences, and tools for experiential learning in data sicience. In this approach, the student learns through reflection on doing instead of being a recipient of already made content.

Human-functioning models that describe human cognitive and psychological states have been developed and used to serve as a core component in creating intelligent and responsive systems. Endowing such systems with these human-functioning models, it gives them the ability to reason and intelligently acting to attain its ultimate design object which is to assist and support people. The process to integrate these models with new systems remains as a nontrivial challenging task. This paper pinpoints the initial steps of integrating an earlier developed agent-based model of cognitive load and reading performance with a robotic lamp. In regard to this matter, several algorithms that have been developed are also discussed and simulations that were performed to prove the applicability of the proposed algorithms are presented.

Anxiety can be defined as an unpleasant state of mental uneasiness or concern that causes physical and psychological discomfort. In this paper, we describe an interactive robot-based platform that is designed to be used to support of person with anxiety traits and states using non-medical treatments including mindfulness, relaxation, and muscle relaxation therapy. We describe CAKNA, whose design is based on theories in anxiety traits and states, social robots, and therapies, along with the results of a pilot study (with 24 respondents) exploring the effectiveness of our robot to support individuals with anxiety.

Recently, Tactile Internet has been proposed as a promising technology to innovate the human communication within a very short delay. But now it still cannot solve the problem of high delay, which leads to Tactile Internet cannot be widely applied. Therefore, the low-latency techniques, which guarantee an approximately 1ms round-trip delay, should be developed. This survey paper lists several low-latency technologies which can be considered and applied into Tactile Internet.