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Blind people are confronting a number of challenges in performing activities of daily life such as reading labels on a product, identification of currency notes, exploring unknown spaces, identifying the appearance of an object of interest, interacting with digital artifacts, operating a smartphone’s user interface and selecting non-visual items on a screen. The emergence of smartphone-based assistive technologies promotes independence, ease of use and usability resulting in improved quality of life yet poses several challenging opportunities. We have reviewed research avenues in smartphone-based assistive technologies for blind people, highlighted the need for technological advancements, accessibility-inclusive interface paradigm, and collaboration between medical specialists, computer professionals, usability experts and domain users to realize the potential of ICT-based interventions for blind people. This paper analyzes a comprehensive review of the issues and challenges for visually impaired and blind people with the aim to highlight the benefits and limitations of the existing techniques and technologies. Future research ventures are also highlighted as a contribution to the field.

Feedback is one of the significant factors for the mental mapping of an environment. It is the communication of spatial information to blind people to perceive the surroundings. The assistive smartphone technologies deliver feedback for different activities using several feedback mediums, including voice, sonification and vibration. Researchers 0have proposed various solutions for conveying feedback messages to blind people using these mediums. Voice and sonification feedback are effective solutions to convey information. However, these solutions are not applicable in a noisy environment and may occupy the most important auditory sense. The privacy of a blind user can also be compromised with speech feedback. The vibration feedback could effectively be used as an alternative approach to these mediums. This paper proposes a real-time feedback system specifically designed for blind people to convey information to them based on vibration patterns. The proposed solution has been evaluated through an empirical study by collecting data from 24 blind people through a mixed-mode survey using a questionnaire. Results show the average recognition accuracy for 10 different vibration patterns are 90%, 82%, 75%, 87%, 65%, and 70%.

Touchscreen devices such as a smartphone, smartwatch, and tablets are essential assistive devices for visually impaired and blind people in performing activities of daily living. The vision alternative accessibility services such as screen readers, multimodal interactions, vibro-tactical, haptic feedback, and gestures are helping blind people in operating touchscreen interfaces. Part of usability problem with today touchscreen user interfaces contributes to a trade-off in discoverability, navigational complexity, cognitive overload, layout persistency, a cumbersome input mechanism, accessibility, and cross-device interactions. One solution to these problems is to design an accessibility-inclusive blind-friendly user interface framework for performing common activities on a smartphone. This framework re-organizes/re-generates the interface components into a simplified blind-friendly user interface based on user profile and contextual recommendations. The paper reports an improvement in the user experience of blind people in performing activities on a smartphone. Forty-one blind people have participated in this empirical study, resulting in improved users and interaction experience in an operating smartphone.

Despite the advancements in digital learning, students with visual disabilities face significant challenges in mathematics, particularly in solving arithmetic problems like missing digit identification in addition and subtraction. The insufficient availability of accessible tools with real-time feedback mechanisms, error correction features, and interactive learning methods leads to these challenges. This study proposes a novel solution to address these challenges by developing an algorithm designed to assist students with visual disabilities solve missing digit arithmetic problems. The algorithm systematically identifies missing digits and provides step-by-step audio instructions, ensuring adherence to mathematical principles and pedagogical standards. Real-time validation and adaptive computations for carry and borrow operations enhance learning. Implemented in Python, the solution was empirically tested with 40 participants, including students and instructors, with visual disabilities. The results from both qualitative and quantitative analyses indicate substantial improvements in learning outcomes, suggesting that this solution can effectively support inclusive mathematics education and be adapted to other assistive learning contexts.

Several technology-assisted aids are available to help blind and visually impaired people perform their daily activities. The current research uses the state-of-the-art technology to enhance the utility of traditional navigational aids to produce solutions that are more reliable. In this regard, a white cane is no exception, which is supplemented with the existing technologies to design Electronic Travel Aids (ETAs), Electronic Orientation Aids (EOAs), and Position Locator Devices (PLDs). Although several review articles uncover the strengths and limitations of research contributions that extend traditional navigational aids, we find no review article that covers research contributions on a technology-assisted white cane. The authors attempt to fill this literature gap by reviewing the most relevant research articles published during 2010-2017 with the common objective of enhancing the utility of white cane with the existing technology. The authors have collected the relevant literature published during 2010-17 by searching and browsing all the major digital libraries and publishers' websites. The inclusion/exclusion criteria were applied to select the research articles that are relevant to the topic of this review article, and all other irrelevant papers were excluded. Among the 577 (534 through database searching and 43 through other sources) initially screened papers, the authors collected 228 full-text articles, which after applying exclusion/inclusion criteria resulted in 36 papers that were included in the evaluation, comparison, and discussion. This also includes research articles of commercially available aids published before the specified range. The findings show that the research trend is shifting towards developing a technology-assisted white cane solution that is applicable in both indoor and outdoor environments to aid blind users in navigation. In this regard, exploiting smartphones to develop low-cost and user-friendly navigation solution is among the best research opportunities to explore. In addition, the authors contribute a theoretical evaluation framework to compare and evaluate the state-of-the-art solutions, identify research trends and future directions. Researchers have been in the quest to find out ways of enhancing the utility of white cane using existing technology. However, for a more reliable enhancement, the design should have user-centric characteristics. It should be portable, reliable, trust-worthy, lightweight, less costly, less power hungry, and require minimal training with special emphasis on its ergonomics and social acceptance. Smartphones, which are the ubiquitous and general-purpose portable devices, should be considered to exploit its capabilities in making technology-assisted white cane smarter and reliable.

Social media has changed the digital landscape of book retrieval and recommendation on the Web. The availability of the social collaborative cataloging and search applications including Amazon, GoodReads, and LibraryThing has enabled users to discuss their complex information needs and request recommendations on books in natural language. Others with similar interests and preferences suggest books. On these social book websites, users not only benefit from the available professionally-curated, publisher-provided (professional) metadata but also look at how group members assess books by reading their reviews, tags, and ratings, which are commonly referred to as the user-generated content or social metadata. This social collaborative cataloging practice and the resulting rich metadata collection attracted researchers under the broader topic of Social Book Search (SBS). The aim is to exploit the social metadata in book retrieval and understand the search behavior of users while interacting with the rich metadata collection. The retrieval side of the SBS research, which is the main focus of this paper, attempts to come up with book retrieval solutions considering the ambiguity of the natural language and the complexity of the information needs of the users. This paper gives in-depth and comprehensive coverage to the current state of the retrieval side of SBS research from its origin to the present day by critically and analytically reviewing the academically significant relevant research contributions. It reports on the retrieval methods, evaluation methodology, and best-performing runs using different evaluation metrics. It identifies the current trends as well as research challenges and opportunities.

Smart TV has become a pervasive device due to its support for numerous entertainment options. These capabilities of smart TV make it attractive for viewers and researcher. Besides, a plethora of multimedia content continues to grow, which makes searching and browsing the desired content a difficult, time-consuming, and contributes to cognitive overload problem. In the case of smart TV, making clusters of the related content based on user’s interest is among the best solutions. In this connection, this study proposed a dynamic approach for clustering the TV-related online multimedia content and presenting them in a manageable format on smart TV to mitigate the issue of searching and relevant recommendations. We collected and clustered the content from diverse data sources based on the viewer’s interest. This further recommends novel content to the viewers without social metadata, such as rates, tags, which is normally insignificant in for smart TV viewership due to its shared nature. We used bisecting K-means, Lingo, and Suffix Tree Clustering (STC) algorithms. A comparative analysis of these algorithms and suitability in the context of smart TV is also presented. Results show that the proposed approach enhances search results and recommends relevant content based on user’s interests.

The ubiquitous devices and technologies to support teachers and students in a learning environment include the Internet of things (IoT), learning analytics (LA), augmented or virtual reality (AR/VR), ubiquitous learning environment (ULE), and wearables. However, most of these solutions are obtrusive, with substantial infrastructure costs and pseudo-real-time results. Real-time detection of students’ activeness, participation, and activity monitoring is important, especially during a pandemic. This research study provides a low-cost teacher orchestration solution with real-time results using off-the-shelf devices. The proposed solution determines a teacher’s activeness using multimodal data (MMD) from both teacher and student’s devices. The MMD extracts different features from data, decodes them, and displays them to the instructor in real time. It allows the instructor to update their teaching methodology in real time to get more students on board and provide a more engaging learning experience. Our experimental results show that real-time feedback about the classroom’s current status helped improve learning outcomes by about 45%. Also, we investigated a 50% increase in classroom engaging experience.

Globally, students with visual disabilities face significant challenges in accessing and learning mathematics, particularly when solving mathematical equations and expressions. These challenges result from the inherent complexity and abstract nature of mathematical content. Additionally, braille codes are inconsistent across regions, collaborative math platforms are unavailable, and accessible mathematics literature is scarce. Assistive technologies, artificial intelligence, and educational resources have improved accessibility for students with visual disabilities. However, these students still face significant challenges when navigating, exploring, and solving mathematical equations and expressions. These challenges contribute underrepresentation of these students in the science, technology, engineering, and mathematics disciplines. To address these limitations, this study proposes a novel solution to assist students with visual disabilities in learning mathematical expressions interactively with flexible navigation. This study proposes an algorithmic approach for converting input mathematical expressions into content MathML expressions, parsing those expressions into semantic elements, and then providing a structural overview of these expressions. Moreover, interactive keyboard keys were designed to provide flexible navigation through speech feedback, so that users can interact more effectively with expressions. Python libraries were utilized to implement the proposed solution. An empirical evaluation was conducted by 15 instructors and 94 students with visual disabilities and validated by Cronbach’s alpha. Results indicate that the proposed solution improved mathematics accessibility and learning. This study lays a foundation for future research on the integration of advanced technologies in special education.

Social Book Search is an Information Retrieval (IR) approach that studies the impact of the Social Web on book retrieval. To understand this impact, it is necessary to develop a stronger classical baseline run by considering the contribution of query formulation, document representation, and retrieval model. Such a stronger baseline run can be re-ranked using metadata features from the Social Web to see if it improves the relevance of book search results over the classical IR approaches. However, existing studies neither considered collectively the contribution of the three mentioned factors in the baseline retrieval nor devised a re-ranking formula to exploit the collective impact of the metadata features in re-ranking. To fill these gaps in the literature, this research work first performs baseline retrieval by considering all three factors. For query formulation, it uses topic sets obtained from the discussion threads of LibraryThing. For book representation in indexing, it uses metadata from social websites including Amazon and LibraryThing. For the role of the retrieval model, it experiments with traditional, probabilistic, and fielded models. Second, it devises a re-ranking solution that exploits ratings, tags, reviews, and votes in reordering the baseline search results. Our best-performing retrieval methods outperform existing approaches on several topic sets and relevance judgments. The findings suggest that using all topic fields formulates the best search queries. The user-generated content gives better book representation if made part of the search index. Re-ranking the classical/baseline results improves relevance. The findings have implications for information science, IR, and Interactive IR.