In Japan, Society 5.0 has been promoted by the government, which aims at integrating cyberspace and physical space to realize better and sophisticated societies, communities, industry and economy. Towards such a society, we need to acquire more information from the physical space for higher level of context recognition and understanding of real-world objects and phenomena, and consequently the number of such sensors will increase and the amount of information which they sense will also increase. Accordingly, the data analysis is conducted in remote locations (e.g. cloud servers) and the data collection cost might be a primary issue. Besides, it would not be ignorable as machine learning generally incurs significant workload at the cloud servers. In this talk, our smart sensing approaches that involve edge computing concept are introduced to show how these approaches address those issues in different smart city applications.
Taishi Nakazawa, Yasuhiro Kawahara, Hiroshi Yoshida
143 - 151
There are increasing numbers of Assist Suits in workplaces where heavy lifting is required. These suits are typically designed to reduce the stress applied to the lower back region. However, some of the workplaces have started to use more of the knee flexion in order to reduce the stress of the lower back. This led to the research on effective functions to reduce the stress applied to the knee. Through the maximum lifting test and measurement of EMG in the surface, the effect of the proposed device was investigated. In addition, testing with three different levels of assistance strengths and how it affects the wearer’s feeling of the assistance led to a finding that as the level of the assistance increases, the wearer feels more assistance accordingly. Furthermore, If the angle of the knee extension can be measured with the device using the IoH/IoT functions of the assisted suits, it could be used as an indication of fatigue accumulated through work by combining with other indicators such as changes in the duration between tasks.
Yuma Tsurugasaki, Katsuhiro Mori, Michael Hefenbrock, Yoshito Tobe
152 - 161
In social communication, recognizing the feelings of others has an important role. Computers can build better relationships between computers and human by recognizing human emotions. Due to depressed feeling, various negative effects such as shortage of sleep, loss of appetite, lowering of concentration ability are concerned. In order to prevent it and further depression, emotion recognition system is necessary. Electroencephalographs (EEGs) are inexpensive among devices that can measure brain activity and are effective in emotion recognition. Since the EEGs acquired from adjacent electrode site of EEG are similar, it is necessary to consider reduction of electrodes, in order to alleviate the complexity of calculation and to avoid overfitting. Previous research has shown valid electrode sites for emotion recognition of depression using an EEG. However, when using an EEG that can flexibly change the measurement sites or an EEG with a small number of electrodes, it is not clear what kind of electrode sites combination should be used to measure EEGs. In this study, we have examined the combination of EEG channels with high contribution to emotion of depression. We have used the dataset DEAP which has EEG data annotated emotion. Explanatory variables were chosen using LARS to identify the effective channels.
Recent years have seen a rise in ethical consumption, which includes not only reduced expenditures but also considerations regarding the environment and future benefits to humanity. This study investigates a method for encouraging ethical consumption via the use of a dongle interface with a smartphone. We have developed an application that presents information to smartphone users to motivate ethical consumption via a dongle interface and records information on ethical activity to a blockchain. This paper also presents considerations with respect to ethical consumption activity resulting from use by customers in an actual commercial establishment, with presentation of intended future developments.
Interoperability is an important topic in the Internet of Things (IoT), because this domain incorporates diverse and heterogeneous objects, communication protocols and data formats. Many models and classification schemes have been proposed to make the degree of interoperability measurable - however only on the basis of a hierarchical scale. In the course of this paper we introduce a novel approach to measure the degree of interoperability using a metric scaled quantity. We consider IoT as a distributed system, where interoperable objects exchange messages with each other. Under this premise, we interpret messages as operation calls and formalize this view as a causal model. The analysis of this model enables us to quantify the interoperable behavior of communicating objects.
In general, it is a complicated and time-consuming task for a tourist to plan a satisfactory sightseeing tour, because he/she must take into account various factors and constraints (e.g., budget, available time, etc) at the same time. This difficulty comes from the fact that there is a trade-off between the satisfaction/experience obtained by the sightseeing tour and the resource consumed for the tour, hence the optimal solution is not unique. To help decision making, it is desirable to show the tourist a variety of solutions (i.e., tours) considering the trade-off in various ways, but to the best of our knowledge, no existing methods/systems provide such a wide variety of solutions. In this paper, we formulate the sightseeing tour recommendation as a multi-objective optimization problem with money, time and stamina consumption of a tourist and satisfaction degree obtained by the tourist as independent variables. Since this problem is NP-hard, we propose a heuristic algorithm to quickly obtain semi-pareto optimal solutions based on genetic algorithm NSGA-II. We applied the proposed method to planning tours targeting 30 tourist spots in Higashiyama-area of Kyoto, Japan. As a result, our algorithm could output semi-pareto optimal solutions in reasonable time.
The data revolution in the tourism sector poses legal challenges that require rethinking administrative legal relations: administrative control on touristic sector, circulation of touristic data, provision of public services in smart destinations or computer security are new legal institutions that must be regulated in other terms than the conventional ones.
This paper discusses the difficulties to obtain valid consent for data processing activities executed by Artificial Intelligence (AI) systems. Although the European Union’s General Data Protection Regulation (GDPR) is one of the most updated and most comprehensive legal instruments ensuring the right to data protection, the so-called consent obligation is challenged by several technical and practical issues in the case of AI systems. Data controllers obligation to demonstrate transparent information and to ensure the right to be forgotten is being challenged by the technical capabilities of AI taken together with some opaque statements in the GDPR. More detailed explanations should be delivered by the EU Institutions on the implementation of the GDPR for data controllers offering AI systems.
Pedro Miguel Freitas, Laura Nunes, Feliz Gouveia, Maria Guerreiro, Ana Sani
216 - 221
According to the International CPTED Association, Crime Prevention Through Environmental Design (CPTED) is defined as a multi-disciplinary approach to deterring criminal behavior through environmental design. CPTED strategies rely upon the ability to influence offender decisions that precede criminal acts by affecting the built social and administrative environment. The web platform described in this paper uses information about the built and natural environment, geolocated in a map, to produce valuable information to statistical analysis and decision making. The platform will allow authorized users to input information, free text and pictures to classify geographical spots and to create different kinds of outputs. Due to the nature of the data stored, citizens, policy makers, and other stakeholders would need a clear ethical and legal framework to produce and make use of the data and of CPTED itself. This paper also discusses some of the legal issues that may arise.
Mastaneh Davis, Gordon Hunter, Lynn Thalaal, Vivien Tran Ba, Alice Wooding-Olajorin
227 - 238
We present the result of a small study where we investigate what types of resources current students of Mathematics and Mathematics for Engineering prefer for assisting them with their studies of those topics. We found that modern students seem to have a clear preference for on-line resources over traditional textbooks. However, there is currently a lack of good quality resources of that type which allow students to carry-out conventional mathematics exercises on-line and still get appropriate, meaningful and informative feedback on their answers. We then describe our efforts towards addressing this problem through the development of an “intelligent” tutorial system for Calculus which provides feedback tailored to the student’s responses, noting where and how they have made common errors.
Qiongli Zhu, Minjuan Wang, Ping Zou, Alfred Marquez
239 - 247
It is noteworthy that collaborative teamwork is still new and emerging in Chinese universities comparing to higher-educational classrooms in western countries. Team-based mobile learning is deemed an essential way to improve students’ learning in this interactive environment. This paper therefore introduces a new model for structuring team-based mobile learning in college classes. This Team-based Mobile Learning (TBML), ties together the multifaceted elements involved in the success of a mobile learning (mLearning) innovation in an interactive learning environment. In the TBML model, mobile learning is integrated into formal classroom teaching, so that it can support students with both their individual learning goal and performance goal when carrying out their teamwork.
Interest in using Web 2.0 tools to complement or replace learning management systems (LMS) in higher education has exploded in the past decade. Higher education institutions require legally compliant warehouses to track student learning and store its artifacts, while students prefer the engaging, collaborative, and personalized learning environments offered by Web 2.0. Social networking sites, blogs, wikis, and video streaming services enable learning and collaboration in contexts unreachable by learning management systems. Researchers have argued for various integrations of Web 2.0 in classrooms to bridge the divide between institutional and student needs, but questions about the most desirable features for such an integration remain. Furthermore, while models predicting endorsement and use of Web 2.0 for educational purposes exist, the extent to which factors impacting choice have yet to be examined in depth. In this paper, we will discuss (a) recent research trends on Web 2.0 integrations and predictive models in higher education; and (b) additional choice-making factors to consider in future models of endorsement and use of Web 2.0 for learning.
Mo Wang, Mengxue Ji, Yulu Cui, Luyao Yu, Hai Zhang
258 - 268
With the rapid development of artificial intelligence, big data, cloud computing and other technologies, educational environments must inevitably evolve. The smart classroom will become commonplace. Comprehensively and deeply analyzing the behaviors of teachers and students in the classroom will promote the reflection and evaluation of teachers and students. However, smart classroom teaching is a dynamic process; existing classroom observation systems such as Flanders Interactive Analysis System (FIAS) and Information Technology-based Interactive Analysis System (ITIAS) cannot adequately aid in the analysis of a smart classroom. This study proposes a Smart Classroom-based Interactive Analysis System (SCIAS) which will provide a framework for educators to analyze and study smart classrooms.
With the rapid development of informational technologies and mobile devices, blended learning is receiving more attention in higher educational learning environment. Based on the relevant literature review of blended learning and language learning and teaching, this paper explores learning and teaching when mobile phones were used in the BYOD (Bring Your Own Devices) model to implement blended learning in English as Foreign Language (EFL) language course at university level.
Khamssa Chouchane, Almaas Ali, Juan Carlos Augusto, Okba Kazar
280 - 289
Context-awareness is becoming a crucial component in the mobile learning systems due to the dynamic changing of the Mobile learning environment, a Context-aware mobile learning system senses mobile environment and reacts to changing context during the learning process. Some efforts have been made in the area of Context-aware Mobile learning systems in order to propose a user model, most of them are focusing on the technological context such as the network performances, mobile devices capabilities, others are focusing on the learners’ style and preferences, and no one tried to understand the learners’ needs. However, no one tried to study the Learning context from the point of view of the learners. For this purpose, we created a questionnaire, in which we tried to understand which learning contexts are important to the learners in the learning process, and we use it to understand their needs and preferences, to inform the design of a new Context aware Mobile Learning Approach.
Welfare technology is a growing area of research due to the increase in the ageing population. In Nordic countries, public authorities are the primary healthcare providers. Therefore, there is significant of investment to help older people to live as long as they wish at their own home. At the University of South-Eastern Norway, a current project on welfare technology is being developed for this purpose, with a focus on human behaviour modelling. Through the research, gaps were found between the technology and the healthcare aspect of it. Consequently, difficulties for the consumer (the older people) arise. This article presents an analysis of connection and gaps between technology and the healthcare area of welfare technology for the ageing.
Nidal Drissi, Sofia Ouhbi, Mohammed Abdou Janati Idrissi, Mohamed El Koutbi, Mounir Ghogho
307 - 316
The use of connected health solutions in the diagnosis and the monitoring of mental health issues is a promising field. However, in order for the connected mental health solutions to be effective, accurate data about the patient’s mental and physical state is required. Sensors can therefore be very helpful instruments to provide patient’s data needed for a good diagnosis and monitoring. This paper conducts a literature survey to present the current research involving connected health solutions using sensors in the treatment of mental health. Seventeen papers are selected following a search protocol and analyzed to present the publication trend of research on sensors used for mental health and to identify their research types and contribution types. This study may assist researchers interested in the use of sensors for mental health care, as it can serve as a starting point presenting an overview of the addressed topics and the weak areas of the research. The study may also assist patients and clinicians interested in the field to have an overview of the proposed solutions and uses of sensors in mental health care.