Abstract
The demand of devices for safe mobility of blind people is increasing with advancement in wireless communication. Artificial intelligent devices with multiple input and output methods are used for reliable data estimation based on maximum probability. A model of a smart home for safe and robust mobility of blind people has been proposed. Fuzzy logic has been used for simulation. Outputs from the internet of things (IoT) devices comprising sensors and bluetooth are taken as input of the fuzzy controller. Rules have been developed based on the conditions and requirements of the blind person to generate decisions as output. These outputs are communicated through IoT devices to assist the blind person or user for safe movement. The proposed system provides the user with easy navigation and obstacle avoidance.
Highlights
The implementation of public health awareness has reduced the blindness cases due to diseases.But the rate of blindness in elderly people is high and increasing
The rate of blindness in elderly people is high and increasing. These people need devices to assist them in navigation. This has increased the demand for assistive devices for navigation and orientation
Amongst several artificial intelligence techniques, fuzzy logic is considered a useful tool in the navigation control system for its linguistic terms and reliable decision-making capability without precise information of the surroundings
Summary
The implementation of public health awareness has reduced the blindness cases due to diseases. The first category includes travel aids, which are the electronic devices that provide the user with information about the surroundings. This information helps the user develop a mental map for safe mobility. Amongst several artificial intelligence techniques, fuzzy logic is considered a useful tool in the navigation control system for its linguistic terms and reliable decision-making capability without precise information of the surroundings. It utilizes human reasoning and decision making for reliable navigation in a dynamic environment with unknown obstacles [12,13]. Fuzzy-based simulation has been verified with Mamdani model calculations for result comparisons and optimizations
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