An Adaptive LoRa based Forklift Tracking and Collision Avoidance System for Smart Warehouses

This Forklift tracking and collision avoidance are vital in improving industrial safety and operational performance. The proposed Adaptive LoRa Based Forklift Tracking and Collision Avoidance (ALFTCA) based on Forklift Tracking and Collision Avoidance. The system works by adapting the LoRa transmission intervals dynamically depending on forklift velocity, obstacle proximity and geofencing regions to maximize energy efficiency and real-time tracking. The system uses GPS for location tracking, IMU sensors for detecting motion and ultrasonic sensors for measuring obstacle proximity. LoRa modules are used for low- power and long-range communication. When a forklift approach travels at high speeds, the rate of transmission goes up to real-time information. When low activity areas, it goes down to save power. The system is reviewing data and initiating collision avoidance features in the form of audio visual signals and performs automatic braking when the forklifts are within a critical distance. Experimental evaluations prove that ALFTCA is capable of cutting energy consumption by 27 percentage with tracking and safety warnings.