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

Smart assistive devices for visually impaired and blind people are of high interest last three decades since portable and wearable IoT hardware became available for a wide range of users. In this chapter, the mesh network of eHealth intelligent agents is discussed as a review study on the Arduino and Raspberry Pi based soft-/hardware. Presented projects were developed by a small group of professionals from different areas who support the spatial cognition of visually impaired and blind people. In the first project, the palm-sized computer Raspberry Pi 3 B measures the distance to the nearest obstacle via ultrasonic sensor HC-SR04 and recognizes human faces by the Pi camera, a library of programming functions OpenCV, and face recognition module of Adam Geitgey. Also, objects and places around the B&VI are indicated by the Blue-tooth devices of classes 1-3 and iBeacons, intelligent eHealth agents cooperate with one another to efficiently route data from/to clients in the smart city mesh network via MQTT and BLE protocols. In the second project, an assistive device supports the visually impaired person to play golf. Every golf flagstick has the sound marking device with the active buzzer and WiFi remote control by the person with a good vision. The NodeMcu Lua ESP8266 ESP-12 WiFi boards in devices are controlled by HTML websites. A portable WiFi router links all devices in the network. In the third project, an assistive device supports the orientation of B&VI by measuring the distance to the obstacle based on the Arduino Uno and ultrasonic sensor HC-SR04. The distance is pronounced to the B&VI via headphones and MP3 player with SD card. In the fourth project, the developed soft-/hardware complex uses wearable Raspberry Pi 3 B microcomputer and the Bytereal iBeacon fingerprinting to uniquely identify the B&VI location at the industrial facilities.