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Limitations encountered with the models developed in the previous studies had occurrences of global minima; due to which this study developed a new intelligent ubiquitous computational model that learns with gradient descent learning rule and operates with auto-encoders and decoders to attain better energy optimization. Ubiquitous machine learning computational model process performs training in a better way than regular supervised learning or unsupervised learning computational models with deep learning techniques, resulting in better learning and optimization for the considered problem domain of cloud-based internet-of-things (IOTs). This study aims to improve the network quality and improve the data accuracy rate during the network transmission process using the developed ubiquitous deep learning computational model.

In this research study, a novel intelligent ubiquitous machine learning computational model is designed and modelled to maintain the optimal energy level of cloud IOTs in sensor network domains. A new intelligent ubiquitous computational model that learns with gradient descent learning rule and operates with auto-encoders and decoders to attain better energy optimization is developed. A new unified deterministic sine-cosine algorithm has been developed in this study for parameter optimization of weight factors in the ubiquitous machine learning model.

The newly developed ubiquitous model is used for finding network energy and performing its optimization in the considered sensor network model. At the time of progressive simulation, residual energy, network overhead, end-to-end delay, network lifetime and a number of live nodes are evaluated. It is elucidated from the results attained, that the ubiquitous deep learning model resulted in better metrics based on its appropriate cluster selection and minimized route selection mechanism.

In this research study, a novel ubiquitous computing model derived from a new optimization algorithm called a unified deterministic sine-cosine algorithm and deep learning technique was derived and applied for maintaining the optimal energy level of cloud IOTs in sensor networks. The deterministic levy flight concept is applied for developing the new optimization technique and this tends to determine the parametric weight values for the deep learning model. The ubiquitous deep learning model is designed with auto-encoders and decoders and their corresponding layers weights are determined for optimal values with the optimization algorithm. The modelled ubiquitous deep learning approach was applied in this study to determine the network energy consumption rate and thereby optimize the energy level by increasing the lifetime of the sensor network model considered. For all the considered network metrics, the ubiquitous computing model has proved to be effective and versatile than previous approaches from early research studies.

The developed ubiquitous computing model with deep learning techniques can be applied for any type of cloud-assisted IOTs in respect of wireless sensor networks, ad hoc networks, radio access technology networks, heterogeneous networks, etc. Practically, the developed model facilitates computing the optimal energy level of the cloud IOTs for any considered network models and this helps in maintaining a better network lifetime and reducing the end-to-end delay of the networks.

The social implication of the proposed research study is that it helps in reducing energy consumption and increases the network lifetime of the cloud IOT based sensor network models. This approach helps the people in large to have a better transmission rate with minimized energy consumption and also reduces the delay in transmission.

In this research study, the network optimization of cloud-assisted IOTs of sensor network models is modelled and analysed using machine learning models as a kind of ubiquitous computing system. Ubiquitous computing models with machine learning techniques develop intelligent systems and enhances the users to make better and faster decisions. In the communication domain, the use of predictive and optimization models created with machine learning accelerates new ways to determine solutions to problems. Considering the importance of learning techniques, the ubiquitous computing model is designed based on a deep learning strategy and the learning mechanism adapts itself to attain a better network optimization model.

The impact of Ubiquitous Computing on Learning is not confined within technical dimension. Besides its technical facilitation, this new computing paradigm also challenges human’s belief on learning, and compels us to rethink on the design of learning resources and environments. The paper explores the concept of Ubiquitous Learning, and proposes a conceptual framework for a Ubiquitous Learning Environment (ULE) design and implementation. A ULE is established on the combination between Real World and Virtual Space, Personal Space and Shared Space. Learning in a ULE is conducted in the interactions among three essential communicative elements: Social Human, Object in real world, and Artifact in virtual space. A learning process is a social transfer process between tacit and explicit knowledge. Context‐Awareness is indispensable to all kinds of interactions in a ULE. In particular, this paper gives a discussion to context‐awareness supported Interoperability and Adaptability in a ULE, and suggests a five‐dimensional (Who, What, How, When, Where) representation approach for modeling context and providing context‐awareness information. In the practical dimension, this paper presents a design framework for a ULE implementation by integrating the applications of present affordable learning devices, such as networked PCs (Personal Computer), PDAs (Personal Digital Assistant), mobile phones, sensors, and RFIDs. A basic learning system architecture in a ULE and a prototype ubiquitous language learning system are also addressed in this paper.

A cyber world (CW) is a digitized world created on cyberspaces inside computers interconnected by networks including the Internet. Following ubiquitous computers, sensors, e‐tags, networks, information, services, etc., is a road towards a smart world (SW) created on both cyberspaces and real spaces. It is mainly characterized by ubiquitous intelligence or computational intelligence pervasion in the physical world filled with smart things. In recent years, many novel and imaginative researches have been conducted to try and experiment a variety of smart things including characteristic smart objects and specific smart spaces or environments as well as smart systems. The next research phase to emerge, we believe, is to coordinate these diverse smart objects and integrate these isolated smart spaces together into a higher level of spaces known as smart hyperspace or hyper‐environments, and eventually create the smart world. In this paper, we discuss the potential trends and related challenges toward the smart world and ubiquitous intelligence from smart things to smart spaces and then to smart hyperspaces. Likewise, we show our efforts in developing a smart hyperspace of ubiquitous care for kids, called UbicKids.

In ubiquitous computing environments, not only programmers but also general users come to develop/customize applications. Therefore, the purpose of this paper is to propose a new application development environment for ubiquitous computing environments.

The paper clarifies the requirements for application development environments of ubiquitous computing environments. It then designs and implements a prototype of a development environment that fulfills these requirements.

It is found that the requirements for application development in ubiquitous computing environments are: easy programming, detection of current status, programming awareness of network connections between multiple ubiquitous devices, and debugging with cooperation among real/virtual environments.

This prototype of application development environment is designed for event‐driven ubiquitous devices.

A prototype development environment has been implemented to show the effectiveness of this approach, and is presented an example of an application development to show the effectiveness of the approach.

This paper proposes a new style of application development for ubiquitous computing environments

Active service is one of key problems of ubiquitous computing paradigm. Context‐aware computing is helpful to carry out this service. Because the context is changing with the movement or shift of the user, its uncertainty often exists. Context‐aware computing with uncertainty includes obtaining context information, forming model, fusing of aware context and managing context information. In this paper, we focus on modeling and computing of aware context information with uncertainty for making dynamic decision during seamless mobility. Our insight is to combine dynamic context‐aware computing with improved Random Set Theory (RST) and extended D‐S Evidence Theory (EDS). We re‐examine formalism of random set, argue the limitations of the direct numerical approaches, give new modeling mode based on RST for aware context and propose our computing approach of modeled aware context.In addition, we extend classic D‐S Evidence Theory after considering context’s reliability, time‐efficiency and relativity, compare relative computing methods. After enumerating experimental examples of our active space, we provide the evaluation. By comparisons, the validity of new context‐aware computing approach based on RST or EDS for ubiquitous active service with uncertainty information has been successfully tested.

This paper aims to demonstrate that a policy-based middleware solution which facilitates the development of context-aware applications and the integration of the heterogeneous devices should be provided for ubiquitous computing environments. Ubiquitous computing targets the provision of seamless services and applications by providing an environment that involves a variety of devices having different capabilities. These applications help transforming the physical spaces into computationally active and smart environments. The design of applications in these environments needs to consider the heterogeneous devices, applications preferences and rapidly changing contexts. The applications, therefore, need to be context-aware so that they can adapt to different situations in real-time.

In this paper, we argue that a policy-based middleware solution that facilitates the development of context-aware applications and the integration of the heterogeneous devices should be provided for ubiquitous computing environments. The middleware allows applications to track items and acquire contextual information about them easily, reason about this information captured using different logics and then adapt to changing contexts. A key issue in these environments is to allow heterogeneous applications to express their business rules once, and get the preferred data once they are captured by the middleware without any intervention from the application side.

Our middleware tackles this problem by using policies to define the different applications’ rules and preferences. These policies can specify rules about the middleware services to be used, type of data captured, devices used, user roles, context information and any other type of conditions.

In this paper, we propose the design of a flexible and performant ubiquitous computing, and context-aware middleware called FlexRFID along with its evaluation results.

It is essential for professionals to have flexible access to information sources and interaction with clients and colleagues. Mobile phones, e‐mail, pagers, laptops, and PCs all aim to facilitate the flexibility necessary for conducting their work. Ideally, professionals with intense demands on their time should not be supported by various information and interaction technologies, they should embed core domesticated technologies. This paper examines how the vision of iniquitous ICT support for professional work meets the harsh realities through interviews with 16 individual professionals from 16 different organisations. The paper aims to answer the question of the applicability and reality of ubiquitous computing in today's work environment and where technology is in terms of limitations for the professional. The study demonstrates that the joint life of professionals and their technologies is not one best characterised by the technical and the social merging seamlessly. It is instead one burdened by constant attention.

Ever since Mark Weiser coined the term “ubiquitous computing” (ubicomp) in 1988, there has been a general interest in proposing various solutions that would support his vision. However, attacks targeting devices and services of a ubicomp environment have demonstrated not only different privacy issues, but also a risk of endangering user’s life (e.g. by modifying medical sensor readings). Thus, the aim of this paper is to provide a comprehensive overview of security challenges of ubicomp environments and the corresponding countermeasures proposed over the past decade.

The results of this paper are based on a literature review method originally used in evidence-based medicine called systematic literature review (SLR), which identifies, filters, classifies and summarizes the findings.

Starting from the bibliometric results that clearly show an increasing interest in the topic of ubicomp security worldwide, the findings reveal specific types of attacks and vulnerabilities that have motivated the research over the past decade. This review describes most commonly proposed countermeasures – context-aware access control and authentication mechanisms, cryptographic protocols that account for device’s resource constraints, privacy-preserving mechanisms, and trust mechanisms for wireless ad hoc and sensor networks.

To the best of our knowledge, this is the first SLR on security challenges in ubicomp. The findings should serve as a reference to an extensive list of scientific contributions, as well as a guiding point for the researchers’ novel to the security research in ubicomp.

The purpose of this study is to examine a mobile delivery system as a working ubiquitous decision support system (UDSS) and determine whether it would improve decision quality.

Ubiquitous mobility and context awareness are the two core functions of the UDSS. Hence the authors examined how they might influence individual absorptive capacity and perceived usefulness. Moreover the authors investigated how individual absorptive capacity and perceived usefulness might be related to decision quality. A total of 174 completed questionnaires were collected from delivery workers, and a financial incentive was provided to participants. To test the hypotheses the research model was analysed with the partial least square method.

The results reveal that all paths are statistically valid. Individual absorptive capacity and perceived usefulness were positively influenced by ubiquitous mobility and context awareness. In addition individual absorptive capacity and perceived usefulness have positive effects on decision quality.

This research model did not consider all the capabilities enabled by the UDSS. Future study should pay attention to nomadicity, proactiveness, invisibility, and portability as relevant antecedents within the model.

In the field of IS studies the impact of the UDSS on users' decision quality has remained unclear to date. The authors adopted a mobile delivery system as a working UDSS and applied it in their study. Thereby the authors found the mediating effects of perceived usefulness and absorptive capacity under a ubiquitous environment.

The purpose of this paper is to investigate concepts that are used in depicting future visions of society, as afforded by technology, to map the extent of their use, examine the level of their dominance in different research areas and geographic boundaries, identify potential overlaps, analyse their longitudinal growth, and examine whether any of the identified concepts has assumed an overarching position.

In total, 14 concepts, each of which is used to depict visions of future information infrastructures, were identified. More than 20,000 scholarly documents related to 11 of these concepts (those with 20 or more documents) are analysed by various qualitative/quantitative methods.

The concepts most referred to are semantic web and ubiquitous computing (all years), and internet of things (Year 2013). Publications on some newer concepts (e.g. digital living, real world internet) are minimal. There are variations in the extent of use and preferred concepts based on geographic and disciplinary boundaries. The overlap in the use of these terms is minimal and none of these terms has assumed an overarching umbrella position.

This study is limited to scholarly publications; it would be relevant to also study the pattern of usage in governmental communications and policy documents.

By mapping multiplicity of concepts and the dispersion of discussions, the authors highlight the need for, and facilitate, a broader discussion of related social and societal implications.

This paper is the first to present a collective of these related concepts and map the pattern of their occurrence and growth.