Adaptive and context-aware service composition for IoT-based smart cities

Smart Cities are advancing towards an instrumented, integrated, and intelligent living space, where Internet of Things (IoT), mobile technologies and next generation networks are expected to play a key role. In smart cities, numerous IoT-based services are likely to be available and a key challenge is to allow mobile users perform their daily tasks dynamically, by integrating the services available in their vicinity. Semantic Service Oriented Architectures (SSOA) abstract the environment’s services and their functionalities as Semantic Web Services (SWS). However, existing service composition approaches based on SSOA do not support dynamic reasoning on user tasks and service behaviours to deal with the heterogeneity of IoT domains. In this paper, we present an adaptive service composition framework that supports such dynamic reasoning. The framework is based on wEASEL, an abstract service model representing services and user tasks in terms of their signature, specification (i.e., context-aware pre-conditions, post-conditions and effects) and conversation (i.e., behaviour with related data-flow and context-flow constraints). To evaluate our composition framework, we develop a novel OWLS-TC4-based testbed by combining simple and composite services. The evaluation shows that our wEASEL-based system performs more accurate composition and allows end-users to discover and investigate more composition opportunities than other approaches.     

Enhanced traffic-adaptive slotted MAC for IoT-based smart monitoring grid

The Journal of Supercomputing - The implementation of a wireless sensor network has been utilized in many applications of urban and rural areas. One such application is smart-grid Internet of...     

Reconfigurable natural interaction in smart environments: approach and prototype implementation

The vision of sensor-driven applications that adapt to the environment hold great promise, but it is difficult to turn these applications into reality because device and space heterogeneity is an obstacle to interoperability and mutual understanding of the smart devices and spaces involved. Smart Spaces provide shared knowledge about physical domains and they inherently enable cooperative and adaptable applications by keeping track of the semantic relations between objects in the environment. In this paper, the interplay between sensor-driven objects and Smart Spaces is investigated and a device with a tangible interface demonstrates the potential of the ${\sl smart{\text -}space{\text -}based}$ and ${\sl sensor{\text -}driven}$ computing paradigm. The proposed device is named REGALS (Reconfigurable Gesture based Actuator and Low Range Smartifier). We show how, starting from an interaction model proposed by Niezen, REGALS can reconfigure itself to support different functions like Smart Space creation (also called ${\sl environment\,smartification}$ ), interaction with heterogeneous devices and handling of semantic connections between gestures, actions, devices, and objects. This reconfiguration ability is based on the context received from the Smart Space. The paper also shows how tagged objects and natural gestures are recognized to improve the user experience reporting a use case and the performance evaluation of REGALS’ gesture classifier.     

Designing smart artifacts for smart environments

Smart artifacts promise to enhance the relationships among participants in distributed working groups, maintaining personal mobility while offering opportunities for the collaboration, informal communication, and social awareness that contribute to the synergy and cohesiveness inherent in collocated teams. Two complementary trends have resulted in the creation of smart environments that integrate information, communication, and sensing technologies into everyday objects. We distinguish between two types of smart artifacts: system-oriented, importunate smartness and people-oriented, empowering smartness. The system-oriented and people-oriented approaches represent the end points of a line along which we can position weighted combinations of both types of smartness depending on the application domain. We developed the Hello.Wall, our version of an ambient display, for the Ambient Agoras environment. The Hello.Wall transmits organization-oriented information publicly and information addressed to individuals privately.     

Supporting social interaction with smart phones

The smart phone offers communication, connectivity, content consumption, and content creativity. Seven different systems exemplify its ability to support a wide range of social interactions, helping make pervasive computing a reality. For smart phones to become successful pervasive system components, they must support and enhance various user activities and offer useful, effective functionality. The systems the author have built focuses on augmenting and enhancing communication; they're communication devices first and computers second. The system supports social interaction between people n particular, interaction that would be difficult if not impossible to achieve without the smart phone technology. This dependency on the system endows them with a degree of utility that drives their effectiveness, which is key to increasing the use of pervasive systems.     

Location-aware communications in smart environments

We present a location-aware communication approach for smart home environments that is based on a symbolic location model that represents the containment relationships between physical objects, computing devices, and places. The approach enables people and devices to discover and connect with communication partners based on their co-locations. It also provides non-smart objects, including home appliances, everyday objects, and places, with virtual counterparts, which both represent them and work as proxies for their targets. We present the design for this approach and describe its implementation and applications.     

Face recognition for smart environments

Smart environments, wearable computers, and ubiquitous computing in general are the coming “fourth generation” of computing and information technology. But that technology will be a stillbirth without new interfaces for interaction, minus a keyboard or mouse. To win wide consumer acceptance, these interactions must be friendly and personalized; the next generation interfaces must recognize people in their immediate environment and, at a minimum, know who they are. In this article, the authors discuss face recognition technology, how it works, problems to be overcome, current technologies, and future developments and possible applications. Twenty years ago, the problem of face recognition was considered among the most difficult in artificial intelligence and computer vision. Today, however, there are several companies that sell commercial face recognition software that is capable of high-accuracy recognition with databases of more than 1,000 people. The authors describe the face recognition technology used, explaining the algorithms for face recognition as well as novel applications, such as behavior monitoring that assesses emotions based on facial expressions     

Enhancing biometric recognition with spatio-temporal reasoning in smart environments

We discuss smart environments that identify and track their occupants using unobtrusive recognition modalities such as face, gait, and voice. In order to alleviate the inherent limitations of recognition, we propose spatio-temporal reasoning techniques based upon an analysis of the occupant tracks. The key idea underlying our approach is to determine the identity of a person based upon information from a track of events rather than a single event. We abstract a smart environment by a probabilistic state transition system in which each state records a set of individuals who are present in various zones of the smart environment. An event abstracts a recognition step, and the transition function defines the mapping between states upon the occurrence of an event. We express two forms of spatio-temporal reasoning in the form of transition functions: a track-based transition function and an error-correcting transition function. We also define the concepts of ‘precision’ and ‘recall’ to quantify the performance of the smart environment and provide experimental results to clarify the performance improvements from spatio-temporal reasoning. Our conclusion is that the state transition system is an effective abstraction of a smart environment and the application of spatial-temporal reasoning enhances the overall performance of a biometric recognition system.     

Human knowledge acquisition from 3D interaction in virtual environments

Recently,virtual environment (VE) based design and planning,which is a kind of interaction intensive computing,has shown great potential.Most users of such systems are specialists or technicians and their 3D interactions with the system embed a great deal of knowledge and skills.Thus,how to integrate human knowledge and skills into VE is a great challenge to researchers in the human computer interaction field.This paper proposes a method for acquiring user knowledge from VE.The main ideas and work include,abstracting the interactive process and formalizing the interactive semantics,as well as providing a semantic model of an interactive information repository,from which user interactive processes can be retrieved and all kinds of application logics can be established.A virtual assembly planning system is introduced as an example of a practical application of this method.Experiments show that the related models can well capture user knowledge and retrieve the interaction process.     

A location model for smart environments

This paper presents a location model for location-aware and user-aware services in smart environments. It can be dynamically organized like a tree based on geographical containment, such as that in a user–room–floor–building hierarchy and each node in the tree can be constructed as an executable software component. The model is unique in existing approaches because it enables location-aware services to be managed without any database servers, it can be managed by multiple computers, and it can provide a unified view of the locations of not only physical entities and spaces, including users and objects, but also computing devices and services. A prototype implementation of this approach was constructed on a Java-based mobile agent system. This paper presents the rationale, design, implementation, and applications of the prototype system.     

Mixed reality participants in smart meeting rooms and smart home environments

Human–computer interaction requires modeling of the user. A user profile typically contains preferences, interests, characteristics, and interaction behavior. However, in its multimodal interaction with a smart environment the user displays characteristics that show how the user, not necessarily consciously, verbally and nonverbally provides the smart environment with useful input and feedback. Especially in ambient intelligence environments we encounter situations where the environment supports interaction between the environment, smart objects (e.g., mobile robots, smart furniture) and human participants in the environment. Therefore it is useful for the profile to contain a physical representation of the user obtained by multi-modal capturing techniques. We discuss the modeling and simulation of interacting participants in a virtual meeting room, we discuss how remote meeting participants can take part in meeting activities and they have some observations on translating research results to smart home environments.     

Multimodal identification and tracking in smart environments

We present a model for unconstrained and unobtrusive identification and tracking of people in smart environments and answering queries about their whereabouts. Our model supports biometric recognition based upon multiple modalities such as face, gait, and voice in a uniform manner. The key technical idea underlying our approach is to abstract a smart environment by a state transition system in which each state records a set of individuals who are present in various zones of the environment. Since biometric recognition is inexact, state information is inherently probabilistic in nature. An event abstracts a biometric recognition step, and the transition function abstracts the reasoning necessary to effect state transitions. In this manner, we are able to integrate different biometric modalities uniformly and also different criteria for state transitions. Fusion of biometric modalities is also supported by our model. We define performance metrics for a smart environment in terms of the concepts of ‘precision’ and ‘recall’. We have developed a prototype implementation of our proposed concepts and provide experimental results in this paper. Our conclusion is that the state transition model is an effective abstraction of a smart environment and serves as a good basis for developing practical systems.     

The value of handhelds in smart environments

The severe resource restrictions of computer-augmented everyday artifacts imply substantial problems for the design of applications in smart environments. Some of these problems can be overcome by exploiting the resources, I/O interfaces, and computing capabilities of nearby mobile devices in an ad-hoc fashion. We identify the means by which smart objects can make use of handheld devices such as PDAs and mobile phones, and derive the following major roles of handhelds in smart environments: (1) mobile infrastructure access point; (2) user interface; (3) remote sensor; (4) mobile storage medium; (5) remote resource provider; and (6) weak user identifier. We present concrete applications that illustrate these roles, and describe how handhelds can serve as mobile mediators between computer-augmented everyday artifacts, their users, and background infrastructure services. The presented applications include a remote interaction scenario, a smart medicine cabinet, and an inventory monitoring application.     

Monitoring user activities in smart home environments

Wireless sensor networks (WSNs) enable smart environments to create pervasive and ubiquitous applications, which give context-aware and scalable services to the end users. In this paper, we propose an architecture and design of a web application for a sensor network monitoring. Further, the variation in received signal strength indicator values is used for knowledge extraction. Experiments are conducted in an in-door room environment to determine the activities of a person. For instance, a WSN consisting of Moteiv’s Tmote Sky sensors is deployed in a bedroom to determine the sleeping behavior and other activities of a person.     

Meetings and meeting modeling in smart environments

In this paper we survey our research on smart meeting rooms and its relevance for augmented reality meeting support and virtual reality generation of meetings in real time or off-line. The research reported here forms part of the European 5th and 6th framework programme projects multi-modal meeting manager (M4) and augmented multi-party interaction (AMI). Both projects aim at building a smart meeting environment that is able to collect multimodal captures of the activities and discussions in a meeting room, with the aim to use this information as input to tools that allow real-time support, browsing, retrieval and summarization of meetings. Our aim is to research (semantic) representations of what takes place during meetings in order to allow generation, e.g. in virtual reality, of meeting activities (discussions, presentations, voting, etc.). Being able to do so also allows us to look at tools that provide support during a meeting and at tools that allow those not able to be physically present during a meeting to take part in a virtual way. This may lead to situations where the differences between real meeting participants, human-controlled virtual participants and (semi-) autonomous virtual participants disappear.

RETRACTED ARTICLE: IoT-based real-time patients vital physiological parameters monitoring system using smart wearable sensors

Neural Computing and Applications -     

Human centred design of 3-D interaction devices to control virtual environments

It is commonly acknowledged that user needs should drive design, but often technical influences prevail. Currently, there are no standard interaction devices or interfaces used in 3-D environments, and there is a lack of specific best practice guidelines to develop these. This paper discusses the process of collecting feedback on prototype designs for VR/VE interaction devices from both expert users and non-expert users, and demonstrates how the information gained from human centred evaluation can be used to further the design process. Experiment 1 examined the usability of two magnetically tracked interaction devices with three different types of menus (Sphere, Linear and Fan). Quantitative and qualitative analysis was carried out on the results, and usability problems with the menus and devices are discussed. The findings from this experiment were translated into general design guidance, in addition to specific recommendations. A new device was designed on the basis of some of these recommendations and its usability was evaluated in Experiment 2. Feedback from participants in Experiment 2 demonstrated that the design recommendations emerging from Experiment 1 were successfully applied to develop a more usable and acceptable device.     

Exploring factors influencing multitasking interaction with multiple smart devices

The intention of this study is to investigate multitasking interaction with multiple smart devices and to unveil factors that play important roles in multitasking scenarios. A survey was carried out and 240 respondents participated whose scores ultimately demonstrated the degree of influence of various items on multitasking interaction with multiple smart devices. Then an exploratory factor analysis was conducted and a seven-factor model named MINDCOS was derived, including Motivation, Input, Navigation and control, Display screen, Cognitive workload, Output, Spatial distribution. The model was utilized to describe the scenario of multitasking interaction with multiple smart devices and the top three factors which illustrated the total variance the most were used to analyze related applications. Then the relationship between the factors and perceived behavior intention of multitasking interaction was tested by regression analysis. This study also found whether users had multitasking experience had a significant impact on their perceived influence of two factors which are Navigation and control and Output.