SELLA: An IoT-based smart shopping trolley with real-time RFID tracking and automated checkout
Abstract
The contemporary retail sector faces a persistent challenge in enhancing in store customer experience, primarily due to inefficiencies at checkout. This paper presents smart e-cart for lean logistics application (SELLA), a smart shopping trolley system engineered to eliminate this bottleneck. The system’s architecture is centered on a Raspberry Pi 4 microcontroller, orchestrating an ultra-high frequency (UHF) radio frequency identification (RFID) subsystem for instantaneous, non-line-of-sight product identification, and a responsive 7-inch touchscreen graphical user interface (GUI) developed in PyQt. The core contribution lies in developing a self contained shopping solution with integrated payment processing, supported by comprehensive performance validation. We present a detailed methodology, including the system’s multi-threaded software architecture and core operational algorithm. Experimental evaluation demonstrates a mean tag detection accuracy of 98.2% under optimal conditions, a robust user interface (UI) latency of under 500 ms, and an average central processing unit (CPU) utilization of 28%, proving system efficiency. Comparative analysis confirms that SELLA’s integration of on-trolley automated payment and detailed performance metrics represents a significant advancement over existing prototypes. The system provides a validated, high-performance solution for next-generation smart retail environments.
Keywords
automated checkout; microcontrollers; performance evaluation; radio frequency identification; retail technology; smart shopping cart;
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PDFDOI: http://doi.org/10.12928/telkomnika.v24i1.27464
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