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The objective of this paper is to present a comprehensive literature survey on dyslexic learners and to propose a model for integrated assistive technology of dyslexic learners.

The use of the proposed model through real-life scenarios categorized as “phonological, reading and writing scenarios”. We have also surveyed some systems for use with dyslexic learners currently in use and have compared them on the basis of number of barriers, technological innovation, age group and fostering.

Dyslexic learners are characterized by slow learning, poor handwriting, poor spelling skills and difficulties in planning, organizing, revising and editing texts; technology plays a major role in the educational environment; it has become crucial in impacting knowledge across the globe; and open research issues and challenges that have to be addressed in the design of the current dyslexic system have been presented in detail.

Full implementation of the proposed model and its application in developing countries.

The system improves the phonological awareness, reading and writing skills of dyslexic learners and it provides a solution for children as well as adults with dyslexia.

This survey can be used as a reference guide to understand learning barriers and intelligent systems for dyslexic learners and to promote the use of these in schools for those with learning disabilities who need assistive technologies.

Development of a newly proposed integrated intelligent assistive system for dyslexic learners; knowledge generation as a reference guide to understand dyslexic learning ability in general and an intelligent assistive dyslexic system in particular; and survey of open research issues and challenges to further research in intelligent dyslexic systems.

The rousing phenomenon of the ageing population is becoming a vital issue and demanding fulminant actions. Population ageing is a resultant of the enhanced health-care system, groovy antibiotics, medications and economic well-being. Old age leads to copious amounts of ailments. Aged people, owing to their reduced mobility and enervating disabilities, tend to rely upon caretakers and/or nursing personnel. With the increasing vogue of nuclear families in the society, the elderly are at the risk of being unveiled to emotional, physical and fiscal insecurities in the years to come. Caring for those seniors will be an enormous undertaking.

There is a dire need for an intelligent assistive system to meet out the requirements of continuous holistic care and monitoring. Assistive robots and systems used for elderly care are studied. The design motivation for the robots, elderly–robot interaction capabilities and technology incorporated in the systems are examined meticulously.

From the survey, it is suggested that the subsystems of an assistive robot revamped for better human–machine interactions will be a potential alternative to the human counterpart. Affirmable advancements in the robot design and interaction methodologies that would increase the holistic care and assistance for aged people are analyzed and listed.

This paper reviews the available assistive technologies and suggests a synergistic model that can be adopted for the caring of the elderly.

This paper aims to serve two main purposes. In the first instance it aims to it provide an overview addressing the state‐of‐the‐art in the area of activity recognition, in particular, in the area of object‐based activity recognition. This will provide the necessary material to inform relevant research communities of the latest developments in this area in addition to providing a reference for researchers and system developers who ware working towards the design and development of activity‐based context aware applications. In the second instance this paper introduces a novel approach to activity recognition based on the use of ontological modeling, representation and reasoning, aiming to consolidate and improve existing approaches in terms of scalability, applicability and easy‐of‐use.

The paper initially reviews the existing approaches and algorithms, which have been used for activity recognition in a number of related areas. From each of these, their strengths and weaknesses are discussed with particular emphasis being placed on the application domain of sensor enabled intelligent pervasive environments. Based on an analysis of existing solutions, the paper then proposes an integrated ontology‐based approach to activity recognition. The proposed approach adopts ontologies for modeling sensors, objects and activities, and exploits logical semantic reasoning for the purposes of activity recognition. This enables incremental progressive activity recognition at both coarse‐grained and fine‐grained levels. The approach has been considered within the realms of a real world activity recognition scenario in the context of assisted living within Smart Home environments.

Existing activity recognition methods are mainly based on probabilistic reasoning, which inherently suffer from a number of limitations such as ad hoc static models, data scarcity and scalability. Analysis of the state‐of‐the‐art has helped to identify a major gap between existing approaches and the need for novel recognition approaches posed by the emerging multimodal sensor technologies and context‐aware personalised activity‐based applications in intelligent pervasive environments. The proposed ontology based approach to activity recognition is believed to be the first of its kind, which provides an integrated framework‐based on the unified conceptual backbone, i.e. activity ontologies, addressing the lifecycle of activity recognition. The approach allows easy incorporation of domain knowledge and machine understandability, which facilitates interoperability, reusability and intelligent processing at a higher level of automation.

The comprehensive overview and critiques on existing work on activity recognition provide a valuable reference for researchers and system developers in related research communities. The proposed ontology‐based approach to activity recognition, in particular the recognition algorithm has been built on description logic based semantic reasoning and offers a promising alternative to traditional probabilistic methods. In addition, activities of daily living (ADL) activity ontologies in the context of smart homes have not been, to the best of one's knowledge, been produced elsewhere.

This study aims to analyze driver risks in the driving environment. A complete analysis of context aware assistive driving techniques. Context awareness in assistive driving by probabilistic modeling techniques. Advanced techniques using Spatio-temporal techniques, computer vision and deep learning techniques.

Autonomous vehicles have been aimed to increase driver safety by introducing vehicle control from the driver to Advanced Driver Assistance Systems (ADAS). The core objective of these systems is to cut down on road accidents by helping the user in various ways. Early anticipation of a particular action would give a prior benefit to the driver to successfully handle the dangers on the road. In this paper, the advancements that have taken place in the use of multi-modal machine learning for assistive driving systems are surveyed. The aim is to help elucidate the recent progress and techniques in the field while also identifying the scope for further research and improvement. The authors take an overview of context-aware driver assistance systems that alert drivers in case of maneuvers by taking advantage of multi-modal human processing to better safety and drivability.

There has been a huge improvement and investment in ADAS being a key concept for road safety. In such applications, data is processed and information is extracted from multiple data sources, thus requiring training of machine learning algorithms in a multi-modal style. The domain is fast gaining traction owing to its applications across multiple disciplines with crucial gains.

The research is focused on deep learning and computer vision-based techniques to generate a context for assistive driving and it would definitely adopt by the ADAS manufacturers.

As context-aware assistive driving would work in real-time and it would save the lives of many drivers, pedestrians.

This paper provides an understanding of context-aware deep learning frameworks for assistive driving. The research is mainly focused on deep learning and computer vision-based techniques to generate a context for assistive driving. It incorporates the latest state-of-the-art techniques using suitable driving context and the driver is alerted. Many automobile manufacturing companies and researchers would refer to this study for their enhancements.

The use of telecare with appropriate domiciliary care packages may provide the means to manage many of the risks associated with the increasing number of older people who wish to continue to live independently in their own homes. Those who become especially frail or disabled can retain their independence and quality of life if their homes are made ‘smart’. This paper discusses the range of services that are available, or under development, for the prototype ‘MIDAS’ (Modular Intelligent Domiciliary Alarm System) telecare system, which enable traditional community alarm, telecare and assistive technologies to be used in an integrated and intelligent fashion. A range of services that allow autonomous operation within the home (and hence increase the perceived independence of a client by decreasing the reliance on a response centre operator) known as ‘HAMISH’ may be used. It offers a wider range of cost‐effective services of relevance to both the individual, and to society, in different types of home environment including dispersed housing and new sheltered housing schemes.

This paper aims to overcome some of the practical difficulties in assistive control of exoskeletons by developing a new assistive algorithm, called output feedback assistive control (OFAC) method. This method does not require feedbacks from force, electromyography (EMG) or acceleration signals or even their estimated values.

The presented controller uses feedbacks from position and velocity of the output link of series elastic actuators (SEAs) to increase the apparent integral admittance of the assisted systems. Optimal controller coefficients are obtained by maximizing the assistance ratio subjected to constraints of stability, coupled stability and a newly defined comfort measure.

The results confirm the effectiveness of using the inherent properties of SEAs for removing the need for extra controversial sensors in assistive control of 1 degree of freedom (1-DOF) SEA powered exoskeletons. The results also clearly indicate the successful performance of the OFAC method in reducing the external forces required for moving the assisted systems.

As the provided experiments indicate, the proposed method can be easily applied to single DOF compliantly actuated exoskeletons to provide a more reliable assistance with lower costs. This is achieved by removing the need for extra controversial sensors.

This paper proposes a novel assistive controller for SEA-powered exoskeletons with a simple model-free structure and independent of any information about interaction forces and future paths of the system. It also removes the requirement for the extra sensors and transforms the assistive control of the compliantly actuated systems into a simpler problem of position control of the SEA motor.

This paper aims to propose a novel balance-assistive control strategy for hip exoskeleton robot.

A hierarchical balance assistive controller based on the virtual stiffness model of extrapolated center of mass (XCoM) is proposed and tested by exoskeleton balance assistive control experiments.

Experiment results show that the proposed controller can accelerate the swing foot chasing XCoM and enlarge the margin of stability.

As a proof of concept, this paper shows the potential for exoskeleton to actively assist human regain balance in sagittal plane when human suffers from a forward or backward disturbing force.

By developing a conceptual model, the purpose of this paper is to improve the understanding of the role of social assistive technologies in facilitating the process of service innovation in care providing organisations to adopt the principles of the consumer-directed care strategy and reduce perceived consumer vulnerability.

Using a cross-sectional survey method, the authors collected data through a survey questionnaire distributed among 335 aged caregivers and specialists. The conceptual model and its 11 research hypotheses were examined using confirmatory factor analysis in structural equation modelling. The rival and mediation models were also estimated.

The conceptual model was validated and eight of eleven hypotheses were supported. It was found that dynamic capabilities are crucial to developing service innovation concept in care providing organisations. In this way, social assistive technologies play a facilitating role to promote the consumer-directed care strategy throughout care providing organisations and allow care providers to enhance wellbeing of vulnerable older people based on their socio-economic status. From the lens of aged care providers, it was also found that the consumer-directed care strategy implemented in aged care facilities may help reduce consumer vulnerability among older people especially when they use social assistive technologies in their service settings.

This study suggests aged care service providers should boost dynamic service innovation capabilities to improve the need for social assistive technologies in aged care facilities with respect to the importance of the consumer-directed care strategy.

This study contributes to the development and validation of a conceptual model for the use of social assistive technologies to sustain service innovation in aged care business models and enhance the consumer-directed care strategy’s performance to better understand consumer vulnerability among older people.

A decade and a half after the debut of pervasive computing, a large number of prototypes, applications, and interaction interfaces have emerged. However, there is a lack of consensus about the best approaches to create such systems or how to evaluate them. To address these issues, this paper aims to develop a performance evaluation framework for pervasive computing systems.

Based on the authors' experience in the Gator Tech Smart House – an assistive environment for the elderly, they established a reference scenario that was used to guide the analysis of the large number of systems they studied. An extensive survey of the literature was conducted, and through a thorough analysis, the authors derived and arrived at a broad taxonomy that could form a basic framework for evaluating existing and future pervasive computing systems.

A taxonomy of pervasive systems is instrumental to their successful evaluation and assessment. The process of creating such taxonomy is cumbersome, and as pervasive systems evolve with new technological advances, such taxonomy is bound to change by way of refinement or extension. This paper found that a taxonomy for something so broad as pervasive systems is very complex. It overcomes the complexity by focusing the classifications on key aspects of pervasive systems, decided purely empirically and based on the authors own experience in a real‐life, large‐scale pervasive system project.

There are currently no methods or frameworks for comparing, classifying, or evaluating pervasive systems. The paper establishes a taxonomy – a first step toward a larger evaluation methodology. It also provides a wealth of information, derived from a survey of a broad collection of pervasive systems.

Conversational agents are natural language interaction interfaces designed to simulate conversation with a real person. This paper seeks to investigate current development and applications of these systems worldwide, while focusing on their availability in Canadian libraries. It aims to argue that it is both timely and conceivable for Canadian libraries to consider adopting conversational agents to enhance – not replace – face‐to‐face human interaction. Potential users include library web site tour guides, automated virtual reference and readers' advisory librarians, and virtual story‐tellers. To provide background and justification for this argument, the paper seeks to review agents from classic implementations to state‐of‐the‐art prototypes: how they interact with users, produce language, and control conversational behaviors.

The web sites of the 20 largest Canadian libraries were surveyed to assess the extent to which specific language‐related technologies are offered in Canada, including conversational agents. An exemplified taxonomy of four pragmatic purposes that conversational agents currently serve outside libraries – educational, informational, assistive, and socially interactive – is proposed and translated into library settings.

As of early 2010, artificially intelligent conversational systems have been found to be virtually non‐existent in Canadian libraries, while other innovative technologies proliferate (e.g. social media tools). These findings motivate the need for a broader awareness and discussion within the LIS community of these systems' applicability and potential for library purposes.

This paper is intended for reflective information professionals who seek a greater understanding of the issues related to adopting conversational agents in libraries, as this topic is scarcely covered in the LIS literature. The pros and cons are discussed, and insights offered into perceptions of intelligence (artificial or not) as well as the fundamentally social nature of human‐computer interaction.