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- Artificial Intelligence of Things Applied to Assistive Technology: A Systematic Literature ReviewPublication . Freitas, Mauricio; Vinícius Aquino Piai; Ricardo Heffel Farias; Fernandes, Anita; De Moraes Rossetto, Anubis Graciela; LEITHARDT, VALDERIAccording to the World Health Organization, about 15% of the world’s population has some form of disability. Assistive Technology, in this context, contributes directly to the overcoming of difficulties encountered by people with disabilities in their daily lives, allowing them to receive education and become part of the labor market and society in a worthy manner. Assistive Technology has made great advances in its integration with Artificial Intelligence of Things (AIoT) devices. AIoT processes and analyzes the large amount of data generated by Internet of Things (IoT) devices and applies Artificial Intelligence models, specifically, machine learning, to discover patterns for generating insights and assisting in decision making. Based on a systematic literature review, this article aims to identify the machine-learning models used across different research on Artificial Intelligence of Things applied to Assistive Technology. The survey of the topics approached in this article also highlights the context of such research, their application, the IoT devices used, and gaps and opportunities for further development. The survey results show that 50% of the analyzed research address visual impairment, and, for this reason, most of the topics cover issues related to computational vision. Portable devices, wearables, and smartphones constitute the majority of IoT devices. Deep neural networks represent 81% of the machine-learning models applied in the reviewed research.
- An Architecture for Managing Data Privacy in Healthcare with BlockchainPublication . De Moraes Rossetto, Anubis Graciela; Sega, Christofer Luiz; LEITHARDT, VALDERIWith the fast development of blockchain technology in the latest years, its application in scenarios that require privacy, such as health area, have become encouraged and widely discussed. This paper presents an architecture to ensure the privacy of health-related data, which are stored and shared within a blockchain network in a decentralized manner, through the use of encryption with the RSA, ECC, and AES algorithms. Evaluation tests were performed to verify the impact of cryptography on the proposed architecture in terms of computational effort, memory usage, and execution time. The results demonstrate an impact mainly on the execution time and on the increase in the computational effort for sending data to the blockchain, which is justifiable considering the privacy and security provided with the architecture and encryption.
- An architectural proposal to protect the privacy of health data stored in the BlockchainPublication . Sega, Christofer L.; De Moraes Rossetto, Anubis Graciela; Correia, Sérgio; LEITHARDT, VALDERIA Blockchain é um livro razão público, descentralizado e distribuído na rede peer-to-peer que utiliza uma estrutura de blocos para verificar e armazenar dados, empregando um mecanismo de consenso confiável. Com o rápido desenvolvimento dessa tecnologia nos últimos anos, diversas preocupações e empecilhos para a sua aplicação em alguns cenários começaram a surgir, dentre eles a privacidade sendo um dos tópicos apontados em vários trabalhos. Este trabalho propõe uma arquitetura para garantir a privacidade dos dados relacionados à área da saúde, que são armazenados dentro de uma rede Blockchain de maneira descentralizada, através do uso de técnicas de criptografia que serão comparadas como o RSA (Rivest-Shamir-Adleman) e o ECC (Elliptic Curve Cryptography).