BillEase: A Hybrid Weight and Vision Based Real-Time Automated Checkout System

Abstract

Small-scale retail stores often depend on manual billing methods that are susceptible to human error, operational inefficiencies, and inadequate data management. To address these limitations, BillEase proposes a low-cost, real-time, AI-based automated billing system that integrates computer vision and embedded sensing technologies. The system utilizes an external camera for image acquisition and an ESP32 Dev Kit V1 interfaced with an HX711 load cell to perform accurate weight measurement for item validation. Captured images are processed using a lightweight TensorFlow Lite–based object detection model optimized for mobile devices, while real-time weight data is transmitted wirelessly to a mobile application via Wi-Fi. Upon successful product identification and verification, the system
automatically generates a digital invoice containing detailed item information along with a QR code to enable instant digital payment. Additional features, including offline billing capability, multi-language support, and a sales analytics dashboard, further enhance system usability and provide valuable business insights. By combining artificial intelligence, Internet of Things (IoT) hardware, and digital payment systems, BillEase delivers a fast,portable, and contactless billing solution that significantly reduces checkout time, improves operational efficiency, and modernizes billing processes in small-scale retail environments.