دورية أكاديمية
Sensor Enabled Proximity Detection with Hybridisation of IoT and Computer Vision Models to Assist the Visually Impaired
العنوان: | Sensor Enabled Proximity Detection with Hybridisation of IoT and Computer Vision Models to Assist the Visually Impaired |
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المؤلفون: | S. Sajini, B. Pushpa |
المصدر: | Engineering, Technology & Applied Science Research, Vol 13, Iss 6 (2023) |
بيانات النشر: | D. G. Pylarinos, 2023. |
سنة النشر: | 2023 |
المجموعة: | LCC:Engineering (General). Civil engineering (General) LCC:Technology (General) LCC:Information technology |
مصطلحات موضوعية: | proximity detection systems, hybrid visually impaired proximity detection (HVIPD) algorithm, hybrid proximity detection for visually impaired framework, computer vision, hybrid IoT ultrasonic system, Engineering (General). Civil engineering (General), TA1-2040, Technology (General), T1-995, Information technology, T58.5-58.64 |
الوصف: | Proximity Detection Systems (PDS) are used to detect objects or persons close to Visually Impaired (VI) persons. Sensors are used to identify proximity based on the distance from objects. This study aimed to design a hybrid proximity detection framework for VI people using ultrasonic sensors embedded in a Raspberry Pi board to detect the proximity of a VI user in an office environment. Hybridization was based on the integration of IoT-enabled devices, ultrasonic proximity sensors, and computer vision algorithms to control the detection of objects or people and inform the user with a voice message. The model framework was implemented with 100 samples and tested with 10 analyses in each sample. The results showed significant improvement in detecting the proximity of the objects with an accuracy of 98.7%, outperforming current PDS with good results in precision, range, obstacle recognition, false positives and negatives, response time, usability, durability, reliability, etc. |
نوع الوثيقة: | article |
وصف الملف: | electronic resource |
اللغة: | English |
تدمد: | 2241-4487 1792-8036 |
Relation: | https://etasr.com/index.php/ETASR/article/view/6410; https://doaj.org/toc/2241-4487; https://doaj.org/toc/1792-8036 |
DOI: | 10.48084/etasr.6410 |
URL الوصول: | https://doaj.org/article/91137be9ebf143d7ab8b12db4bf3e8fc |
رقم الأكسشن: | edsdoj.91137be9ebf143d7ab8b12db4bf3e8fc |
قاعدة البيانات: | Directory of Open Access Journals |
تدمد: | 22414487 17928036 |
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DOI: | 10.48084/etasr.6410 |