There is no evidence that mathematical semantics cannot be understood due to blindness, the problem is the current access barrier to mathematical resources. In light of this problem, this survey aims at providing visually impaired persons (VIPs), or people close to them, with an overview of the currently available software tools for approaching mathematical content. These can be categorized into (a) tools for accessing mathematical documents (where VIPs are just consumers of content), and (b) tools that allow VIPs to become the creators of mathematical content and even to execute mathematical operations. We also explain the advantages and disadvantages of several key technologies used to interact with mathematics. Moreover, we discuss the necessity of the most common formats and languages behind these tools. Finally, we outline promising paths for future research and development towards blind-friendly mathematical resources. The authors hope that this survey may encourage researchers to engage with the still unsolved challenges of this topic.

The limitations in access to mathematical resources faced by visually impaired people (VIPs) are undoubtedly one of the most significant obstacles for them to obtain, e.g., a degree in science. In this context, computational tools such as Computer Algebra Systems (CAS) are not blind-friendly, which causes solving elementary mathematical problems to become a challenging task for this group of people. This paper presents the Casvi system, a CAS for people with visual disabilities that allows carried out basics and advanced numerical calculations using the Maxima mathematical engine. Twenty-five VIPs tested the Casvi system to assess its functionality and usability. As a result, VIPs achieved a 92% accuracy when executing mathematical operations through Casvi . Finally, our system outperforms the LAMBDA system regarding the time needed by VIPs to perform mathematical operations correctly.

As smart cities evolve, integrating new technologies into school transportation is becoming increasingly important to ensure student comfort and safety. Monitoring and enhancing comfort during daily commutes can significantly influence well-being and learning readiness. However, most existing research addresses isolated factors, which limits the development of comprehensive and scalable solutions. This study presents the design and implementation of a low-cost, generalized IoT-based system for monitoring comfort in school transportation. The system processes multiple environmental and operational signals, and these data are transmitted to a cloud computing platform for real-time analysis. Signal processing incorporates standardized metrics, such as root mean square (RMS) values from ISO 2631-1 for vibration assessment. In addition, machine learning techniques, including a Random Forest classifier and ensemble-based models, are applied to classify ride comfort levels using both road roughness and environmental variables. The results show that stacked multisensor fusion achieved a significant improvement in classification performance compared with vibration-only models. The platform also integrates route visualization with commuting time per student, providing valuable information to assess the impact of travel duration on school mobility.

A Tecnologia Assistiva (TA) tem se destacado como um recurso valioso no Ensino Superior, especialmente para alunos com deficiência visual em cursos de Engenharia. Este estudo teórico-prático aborda a criação de um protótipo assistivo, incluindo uma protoboard adaptada e um multímetro falante, além de um aplicativo móvel desenvolvido para auxiliar na programação e no controle de sensores e componentes eletrônicos para pessoas com deficiência visual. A pesquisa enfatiza a importância dessas ferramentas na melhoria da acessibilidade e na facilitação do processo de aprendizagem em laboratórios, argumentando que tais dispositivos são essenciais para a inclusão efetiva de estudantes com deficiência visual em diversas áreas de estudo.