FPGA Implementation of Intelligent Elevator System for AI Applications

Source : Verilog HDL

Proposed Abstract:

Intelligent elevator systems are used in many smart buildings, offices, hospitals, and tall apartments to move people quickly, reduce waiting time, and save energy. They have many advantages, like faster operation, better safety, and the ability to handle requests from many floors at the same time. But there are also some disadvantages, such as slow response when many people use them, fixed movement patterns that cannot adjust to real-time needs, weak security for restricted floors, and no use of advanced AI features for learning and prediction. Most existing elevator systems are built using microcontrollers with fixed scheduling methods, which cannot easily change their operation or add smart features. The problem in this work is to create an elevator system that works faster, is more secure, can adjust to different situations, and is ready for AI use, while also keeping passengers safe. In this project, we design an elevator controller on FPGA using a finite state machine. The system includes floor request handling, priority scheduling, emergency stop, overload detection, automatic door timing, floor number display, passcode access for special floors, and a fire alarm mode. The new idea in this work is to use the speed and flexibility of FPGA hardware along with an FSM design that can later connect to AI for learning passenger habits and predicting movement needs. This makes the system quick, safe, and adaptable. The design is written in Verilog HDL, tested in ModelSim, and implemented on a Xilinx FPGA board. We measure performance by checking response time, scheduling efficiency, and safety accuracy, and the results show it is suitable for future smart building use.

List of the following  materials will be included with the Downloaded Backup: