BlinkPi: A Smart Wheelchair Control via Eyeblink Technology

Abstract

Internet of Things (IoT) transforms the real-time world by turning raw data into action, enabling smart cities and predictive maintenance. It instantly responds to dynamic environments, making life more efficient, responsive, and connected than ever before. IoT also leverages its benefits to assist and improve the lives of paralyzed and disabled individuals. There are various IoT applications used for both public and physically challenged people. Using this in existing work offers significant advantages in usability, enhancing independence and mobility for users. The methodology in conventional smart wheelchairs depends on tracking eyeball movements for steering. In the existing system, we found drawbacks in accuracy, ease of use, and real-time responsiveness. Thus, we proposed a user-friendly system to address these limitations and overcome these challenges. We use eye-blinking as the primary method, allowing users to navigate the wheelchair by counting blinks to move in different directions. To enhance deaf-mute safety, we employ obstacle detection integrated with a buzzer and red light. Additionally, we can track health, and a console is provided to the caretaker. Our proposed work employs the Arduino platform for real-time processing and control, creating a robust and reliable solution. We also have additional features that set a new standard for assistive devices in the healthcare sector.