Real-Time Ensemble Model for Stroke, Drowsy, and Distracted Driver Detection Using Transfer Learning Models
Road safety remains a global concern, with driver-related factors like distraction, drowsiness, and medical conditions such as stroke being leading causes of accidents. In this paper, we propose a real-time ensemble learning framework that leverages transfer learning for the detection of stroke, drowsiness, and distracted driving. Our model integrates multiple Convolutional Neural Networks (CNNs) fine-tuned for each specific task, and employs a stacking method to combine the predictions of these models using a meta-classifier. Notably, the model is optimized to enhance stroke detection, minimizing false negatives— an essential aspect for timely medical intervention. Experimental evaluations on diverse datasets demonstrate the efficacy of our approach, achieving an overall accuracy of 92.5%. The results emphasize the model’s potential for real-time driver monitoring, offering critical safety features that could reduce accidents and save lives.
Beyond Limits: An Intelligent Wheelchair for Inclusive Living
The aim of this project is to enhance the mobility of individuals with disabilities, particularly aiding them in navigating stairs and challenging terrains. Across the world, powered wheelchair employ various methods, primarily categorized into two: 1) tracked mechanisms and 2) robotic wheelchair utilizing intricate robotic systems. The design presented by our team belongs to the latter category, which is recognized for its lighter build when contrasted with the former. However, despite its lightweight structure, this wheelchair design incorporates equipment that renders it more cost-effective and practical than conventional designs within the same category. Our design integrates three distinct mechanisms to adjust the height and center of mass of the passenger during stair climbing and maintain balance and surface contact. Utilizing an array of sensors, it continuously monitors the position of the person on the wheelchair and the wheelchair on the surface. This data guides adjustments in the mechanisms, ensuring stability. This innovation harbors the potential for enhancing various functionalities, including: GPS integration for user navigation. Real-time monitoring of vital signs (e.g., heart rate, blood pressure, body temperature). In an emergency, this data can be transmitted to ambulance centers to pinpoint the individual's location and immediate assistance. A simplified ambulance request system, accessible via a single button press. Overall, this innovative wheelchair prototypes aims to revolutionize accessibility, granting enhanced mobility and independence to individuals with disabilities.