Author and Presenter: Saad Areeb

Summary:
Falls pose a critical health risk, often resulting in severe injuries or fatalities and profoundly affecting individuals' quality of life. This study introduces an innovative machine learning-based fall detection system that utilizes a single low-cost accelerometer sensor to capture body acceleration signals during daily activities. This research presents a promising solution to minimize the consequences of falls, enhancing the safety and well-being of individuals at risk concisely and cost-effectively.

#fall
#accelerometer
#machinelearning
#machinelearningprojects
#machinelearningproject
#intellcity