Mesh Network of eHealth Intelligent Agents for Visually Impaired and Blind People: A Review Study on Arduino and Raspberry Pi Wearable Devices

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Author(s): Dmytro Zubov (University of Central Asia, Kyrgyzstan)
Copyright: 2022
Pages: 32
Source title: Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics
Source Author(s)/Editor(s): Pelin Yildirim Taser (Izmir Bakircay University, Turkey)
DOI: 10.4018/978-1-7998-4186-9.ch013

Keywords: Data Management / Engineering Science Reference / Knowledge Management and Library Science / Web Technologies

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Abstract

Smart assistive devices for blind and visually impaired (B&VI) people are of high interest today since wearable IoT hardware became available for a wide range of users. In the first project, the Raspberry Pi 3 B board measures a distance to the nearest obstacle via ultrasonic sensor HC-SR04 and recognizes human faces by Pi camera, OpenCV library, and Adam Geitgey module. Objects are found by Bluetooth devices of classes 1-3 and iBeacons. Intelligent eHealth agents cooperate with one another in a smart city mesh network via MQTT and BLE protocols. In the second project, B&VIs are supported to play golf. Golf flagsticks have sound marking devices with a buzzer, NodeMcu Lua ESP8266 ESP-12 WiFi board, and WiFi remote control. In the third project, an assistive device supports the orientation of B&VIs by measuring the distance to obstacles via Arduino Uno and HC-SR04. The distance is pronounced through headphones. In the fourth project, the soft-/hardware complex uses Raspberry Pi 3 B and Bytereal iBeacon fingerprinting to uniquely identify the B&VI location at industrial facilities.

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Mesh Network of eHealth Intelligent Agents for Visually Impaired and Blind People: A Review Study on Arduino and Raspberry Pi Wearable Devices

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