A Real-Time Robotic Inventory Observation Framework for Smart Logistics Facilities Using ESP32 and Vision Sensors

Abstract

Modern warehousing and logistics operations require high levels of accuracy, efficiency, and real-time visibility in inventory management to meet the growing demands of e-commerce and supply chain industries. Traditional inventory monitoring methods rely heavily on manual stock verification and periodic inspections, which are time-consuming, labor-intensive, and prone to human errors. To address these challenges, this project proposes a Warehouse Robotic Inventory Assistant using an Espressif 32-bit Microcontroller (ESP32) and Vision Sensors, designed to provide automated inventory detection and intelligent warehouse monitoring through the integration of embedded systems and Internet of Things (IoT) technology. The proposed system incorporates an Ultrasonic Sensor (US) for object presence and distance detection, a Camera Module (CAM) for visual inventory verification and shelf occupancy monitoring, a Liquid Crystal Display (LCD) for local status indication, a buzzer for alert generation, and an IoT communication interface for remote monitoring. The ultrasonic sensor continuously measures the proximity of objects within designated inventory zones, while the camera module captures real-time images for visual confirmation of inventory status. The ESP32 processes sensor and image data, updates the LCD with current inventory information, activates the buzzer during anomaly or threshold conditions, and transmits inventory event data to a centralized IoT platform via wireless communication. The proposed system is cost-effective, scalable, and suitable for deployment in smart warehouse environments. By combining proximity sensing, vision-based verification, and IoT connectivity, the system enhances inventory accuracy, improves operational efficiency, and supports real-time warehouse management, contributing to the advancement of Industry 4.0 and intelligent logistics automation.