Due to the limitations in the perception of graphical information by blind people and the need to substitute the sense of sight with other senses, the correct use of multimedia in the presentation of graphics is particularly important. The aim of the authors was to correctly present visual information in the tactile and audio form and to provide contextually selected information to reduce the existing cognitive barriers. In this article, the authors decided to research the method of exploring a tactile picture by a blind person and providing contextual and semantic information about the touched image elements using the developed tool for multimodal presentation of interactive audio-tactile graphics supporting the perception of blind people. The use of multimedia should improve the perception of the conveyed content. Therefore, the effectiveness of interpreting the information contained in the tactile image is verified by analyzing the tactile, audio, and contextual perceptions during the experiments. The following issues were considered in detail from the point of view of the blind and visually impaired: the recognition of shapes of image elements depending on their size and properties, the optimal width of elements displayed on the tablet screen, the time intervals between taps on an image element, and the acceptable length of graphic element audio description. The results from this study suggest the need to select the image presentation parameters in various perception channels to the user's needs. The findings of our research on tactile shape perception of geometric figures indicate potential problems in recognizing the shapes of figures in the case of wrong preparation of tactile pictures. In the case of a small difference in the proportions of the length of the sides of the figure or a slight difference in the measures of the angles of the figure sides, we have noticed that most blind people fail to recognize its shape. Considerable progress in improving such perception can be achieved by increasing the proportions in the lengths of the sides and the measures of the angles between the sides of the figure. Further steps concern introducing an alternative audio description of the properties of the figure so as to improve the interpretability of the figure shape. For most users, the width of a virtual line in a digital image displayed on a tablet should be around 5 mm for a corresponding 1 mm tactile line. The configuration of the time intervals defining the user's gestures (two-taps, three-taps) should be about 340 ms. Applying audio descriptions to tactile picture elements improves the understanding and interpretation of the information presented on it. Most participants in the test group accepted 5 to 10 seconds of voice prompts. Longer messages were incomprehensible, and details were hard to remember. In the proposed solution, the audio description can be divided into two or three different descriptions available to the user after tapping two or three times on an image element. It allows the user to decide on the amount of contextual information needed about the touched tactile picture element. The research attempted to show the typical values of various image presentation parameters and their ranges of values and indicated effective methods of their selection for a specific system user.

Teaching mathematics to blind people is a challenge of modern educational methods. This article presents a method of preparing the adapted material and its usage in the learning process of mathematics by blind people, as well as the results of evaluating the proposed approach. The presented results were obtained based on a mathematical analysis course conducted in two classes—with and without using the developed method. The developed method uses the conceptualization of knowledge as a graph. The learning process is supported by feedback processes that consider the mechanisms of knowledge and error vectors, on which a personalized adaptation of the learning path is made for each particular student. The evaluation process has shown a statistically significant improvement in learning results achieved by blind students. The average final test score in the group working with the platform during learning increased by 14%. In addition, there was an increase in cooperation between blind students who had the opportunity to take on the role of a teacher, which was observed in 27% of the participants. Our results indicate the effectiveness of the developed approach and motivate us to evaluate the method in a broader group of students. The engagement of students indirectly indicates overcoming the barriers known from the state of the art: uncertainty, poor motivation, and difficulties in consolidating the acquired skills.

UWB has been in existence for several years, but it was only a few years ago that it transitioned from a specialized niche to more mainstream applications. Recent market data indicate a rapid increase in the popularity of UWB in consumer products, such as smartphones and smart home devices, as well as automotive and industrial real-time location systems. The challenge of achieving accurate positioning in indoor environments arises from various factors such as distance, location, beacon density, dynamic surroundings, and the density and type of obstacles. This research used MFi-certified UWB beacon chipsets and integrated them with a mobile application dedicated to iOS by implementing the near interaction accessory protocol. The analysis covers both static and dynamic cases. Thanks to the acquisition of measurements, two main candidates for indoor localization infrastructure were analyzed and compared in terms of accuracy, namely UWB and LIDAR, with the latter used as a reference system. The problem of achieving accurate positioning in various applications and environments was analyzed, and future solutions were proposed. The results show that the achieved accuracy is sufficient for tracking individuals and may serve as guidelines for achievable accuracy or may provide a basis for further research into a complex sensor fusion-based navigation system. This research provides several findings. Firstly, in dynamic conditions, LIDAR measurements showed higher accuracy than UWB beacons. Secondly, integrating data from multiple sensors could enhance localization accuracy in non-line-of-sight scenarios. Lastly, advancements in UWB technology may expand the availability of competitive hardware, facilitating a thorough evaluation of its accuracy and effectiveness in practical systems. These insights may be particularly useful in designing navigation systems for blind individuals in buildings.

Alternative methods of presenting the information contained in mathematical images, which are adapted to the needs of blind people, are significant challenges in modern education. This article presents an alternative multimodal method that substitutes the sense of sight with the sense of touch and hearing to convey graphical information. The developed method was evaluated at a center specializing in the education of the blind in Poland, on a group of 46 students aged 15–19. They solved a set of 60 high school-level problems on geometry, mathematical analysis, and various types of graphs. We assessed the mechanisms introduced for the sense of touch and hearing, as well as the overall impression of the users. The system usability scale and the NASA task load index tests were used in the evaluation. The results obtained indicate an overall increase in user satisfaction and usefulness of the proposed approach and a reduction in the workload during exercise solving. The results also show a significant impact of the proposed navigation modes on the average time to reach objects in the drawing. Therefore, the presented method could significantly contribute to the development of systems supporting multimodal education for people with blindness.

This publication focuses on verifying the AI effectiveness in adapting traditional educational materials to digital form, with a focus on blind people. Despite the existence of solutions to assist visually impaired people, the adaptation of graphics is still problematic. To address these challenges, the use of machine learning, which is becoming increasingly prominent in modern solutions, can be effective. Of particular note are YOLO neural networks, known for their ability to analyze images accurately and in real time. The potential of these networks has not yet been fully validated in the context of mathematical graphics for the visually impaired. This research allowed for the determination of the effectiveness of selected versions of YOLO in recognizing relevant elements in mathematical graphs and the identification of the advantages and limitations of each version. It also helped to point out further potential developments in adapting graphs to accessible forms for blind people. The obtained results indicate that YOLOv5 and YOLOv8 have the most potential in this field. This research not only highlights the applicability of machine learning to accessibility challenges but also provides a foundation for the development of automated tools that can assist teachers in inclusive classroom environments.