• Ranjit Kumar
• Kamlesh Rawani
• Kailash Pati Dutta

The rapid evolution of the Internet of Things (IoT) has transformed traditional vending machines into intelligent, autonomous, and highly interactive service units. This paper proposes SmartVend, a next-generation IoT-enabled vending architecture designed to enhance product availability, optimize operational efficiency, and provide predictive and self-monitoring capabilities. SmartVend integrates sensor-rich hardware, RFID/QR-based authentication, UPI-enabled payment modules, and cloud-assisted real-time analytics to ensure seamless vending operations with minimal human intervention. The system employs an ESP8266-based embedded controller with modular sensing, edge processing, and MQTT communication for lightweight yet secure data exchange. The architecture further supports temperature regulation, environment sensing, automatic fault detection, remote diagnostics, and predictive maintenance. Results demonstrate improved inventory accuracy, faster transaction time, and higher dispensing reliability compared to existing systems. SmartVend establishes a scalable foundation suitable for offices, academic institutions, hospitals, and public infrastructures and contributes towards the development of fully autonomous retail ecosystems driven by IoT and intelligent automation.

IoT Vending Systems, SmartVend Architecture, Edge Computing, Predictive Analytics, RFID/QR Authentication, Cloud-Enabled Retail Automation.

"Next-Generation IoT-Enabled Vending Systems: A Scalable Architecture for Predictive Operations and Self-Monitoring", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 12, page no.d385-d389, December-2025, Available :http://www.jetir.org/papers/JETIR2512350.pdf

"Next-Generation IoT-Enabled Vending Systems: A Scalable Architecture for Predictive Operations and Self-Monitoring", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 12, page no. ppd385-d389, December-2025, Available at : http://www.jetir.org/papers/JETIR2512350.pdf