iAssistMe - Adaptable Assistant for Persons with Eye Disabilities
Author(s) -
Cristina Georgiana Calancea,
Camelia-Maria Miluţ,
Lenuța Alboaie,
Adrian Iftene
Publication year - 2019
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2019.09.169
Subject(s) - computer science , novelty , cloud computing , human–computer interaction , architecture , multimedia , process (computing) , set (abstract data type) , context (archaeology) , resource (disambiguation) , event (particle physics) , world wide web , operating system , art , paleontology , computer network , philosophy , physics , theology , quantum mechanics , visual arts , biology , programming language
Visually challenged people may experience certain difficulties in their daily interaction with technology. That is essentially because the main way to exchange and process information is by written text, images or videos. Since the basic purpose of innovation is to improve people’s lifestyle, in this paper we propose a system that can make technology accessible to a broader group. Our prototype is presented as a mobile application based on vocal interaction, which can help people facing visual disorders consult their personal agenda, create an event, invite other friends to attend it, check the weather in certain areas and many other day-to-day tasks. Regarding the implementation, the project consists of a mobile application that interacts with a cloud based system, which makes it reliable and low in latency due to the resource availability in multiple global regions, provided by the newly emerging platform used in building the infrastructure. The novelty of the system lays in the highly flexible serverless architecture [1] that is open to extension and closed to modification through the set of autonomous cloud processing methods that sustain the base of the functionality. This distributed processing approach guarantees that the user always receives a response from his personal assistant, either by using artificial intelligence context generated phrases, by real-time cloud function processing or by fallback to the training answers.
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