International Journal of Science, Engineering and TechnologyAuthors: Gundal Kirti Sandip, Professor Bangar Abhishek
Abstract: Long checkout queues, manual barcode scanning, billing errors and the physical effort of pushing a trolley through a crowded mall remain persistent problems in organised retail. Existing smart-trolley research addresses these problems in isolation: RFID-based systems automate billing, AI-driven carts add tracking and demand forecasting, IoT and fog-computing architectures reduce latency, and sensor-driven carts add autonomous following. This paper reviews four representative studies and proposes an integrated, low-cost Hybrid Smart Shopping Trolley for shopping malls. The proposed system combines an RFID reader and microcontroller for real-time item identification and billing, an ultrasonic and infrared sensor layer for obstacle-aware assistance, a fog/edge layer for time-critical processing, and a cloud layer for inventory forecasting and customer analytics. A layered architecture, working flow, component design, security model and evaluation methodology are presented. Based on results reported in the reviewed literature, the approach is expected to cut checkout time by roughly 70%, reach about 98% product-identification accuracy, and keep system latency below 200 ms, while remaining cheaper than camera-based cashierless stores. Limitations and future directions are also discussed.
