Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1116
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dc.contributor.authorRizan, T.-
dc.contributor.authorSiriwardena, V.-
dc.contributor.authorRaleen, M.-
dc.contributor.authorPerera, L.-
dc.contributor.authorKasthurirathna, D.-
dc.date.accessioned2022-02-14T06:19:32Z-
dc.date.available2022-02-14T06:19:32Z-
dc.date.issued2021-12-09-
dc.identifier.issn978-1-6654-0862-2/21-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1116-
dc.description.abstractThis paper presents a novel solution for visually impaired individuals. A mobile app is connected to an ESP32CAM and a remote server to help visually impaired individuals to navigate around their environment safely. A deep learning model is deployed in the mobile app to detect obstacles in real-time without connecting to the internet. Other tasks such as reading texts, recognizing people, and describing objects are done in the remote server. We managed to connect the mobile app to the ESP32CAM and the remote server simultaneously. This was possible because the ESP32CAM is connected to the mobile app through Bluetooth. This gave the mobile the ability to connect to the remote server via the internet. To the best of our knowledge, no research has been done using Bluetooth to stream images to do object detection in a mobile app locally. Hence, our solution can detect obstacles locally and do other tasks mentioned previously in the remote server. This paper discusses how the ESP32CAM, obstacle detection module, face recognition module, text reading module, and object description module was implemented such that a low latent and highly efficient mobile app is created using minimal resources.en_US
dc.language.isoenen_US
dc.publisher2021 3rd International Conference on Advancements in Computing (ICAC), SLIITen_US
dc.subjectDeep Learningen_US
dc.subjectObstacle detectionen_US
dc.subjectFace Recognitionen_US
dc.subjectReading texten_US
dc.subjectObject Descriptionen_US
dc.subjectESP32CAMen_US
dc.subjectSSD Mobileneten_US
dc.subjectSiamese Networken_US
dc.titleGuided Vision: A High Efficient And Low Latent Mobile App For Visually Impaireden_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICAC54203.2021.9671191en_US
Appears in Collections:3rd International Conference on Advancements in Computing (ICAC) | 2021

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