Smart Elevator System with Intelligent Floor Level Prioritization using Object Detection

The increasing need for effective vertical transit systems in present-day areas has led to the creation of clever elevator system solutions. In order to improve floor-level prioritizing, this study presents a Smart Elevator System (SES) that incorporates innovative object-detecting technologies. The proposed approach automatically alters elevator priority in realtime by using strong computer vision algorithms to identify and assess the number of passengers waiting on each floor. Computer vision algorithms identify and track passengers in realtime, allowing for the dynamic adjustment of elevator priorities based on the object detection count. Through the use of machine learning models, the system can detect user counts and make intelligent adjustments to reduce waiting times and energy usage. The integration of Internet of Things (IoT) devices, which improves system responsiveness overall, Our proposed work shows notable gains in waiting time and energy savings through intelligent floor-level prioritization.