Browsing by Author "Dissanayake, D. M. L. V"

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    Guide-Me:Voice authenticated indoor user guidance system
    (IEEE, 2021-12-01) Dissanayake, D. M. L. V; Rajapaksha, R. G. M. D. R. P; Prabhashawara, U. P; Solanga, S. A. D. S.P; Jayakody, A
    Due to a lack of knowledge about the building structure and possible impediments, the majority of blind persons require assistance when traveling through unknown regions. To solve this issue, this paper provides "Guide-Me" as a strategy for indoor navigation with optimum accessibility, usability, and security, decreasing obstacles that the user may meet when traveling through indoor surroundings. Because the intended audience for this research is blind or visually impaired persons, "Guide-Me" makes use of the user’s voice-based inputs. This paper also includes Bluetooth beacon integration for localization, a Smart stick with sensors for obstacle detection, a machine learning model for voice authentication, and an algorithm protocol for a secure connection between server and application Integration driven architecture to assist vision impaired in navigating the known and unknown indoor environment.
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    Navigate-Me: Secure voice authenticated indoor navigation system for blind individuals
    (IEEE, 2021-12-02) Dissanayake, D. M. L. V; Rajapaksha, R. G. M. D. R. P; Solanga, S. A. D. S. P; Prabhashawara ., U. P; Jayakody, C. A
    The majority of blind people require assistance when navigating through unfamiliar places due to a lack of information about the building structure and encounterable obstacles. To address this aspect of the problem, this paper presents "Navigate-Me" as an approach for indoor navigation with maximum accessibility, usability, and security, reducing the problems that the user might encounter while navigating through indoor environments. As the targeted audience of this paper is blind or visually impaired people, Navigate-Me utilizes voice-based inputs from the user. In addition, this paper includes Bluetooth beacon integration for localization, White Cane with sensors for obstacle detection, a machine learning model for voice authentication, and an algorithm protocol for a secure connection between server and application integration-driven architecture to assist the visually impaired in navigating known and unknown indoor environments.