IoT-Enabled Smart Sanitary Pad Vending Machine with Dual-Mode Payment and AI-Based Predictive Restocking
DOI:
https://doi.org/10.67308/irjist.094Keywords:
Internet of Things (IoT), ESP32, Smart Vending Machine, Menstrual Hygiene, UPI Payments, Linear Regression, Predictive Stock Management, GSMAbstract
Availability of menstrual hygiene products with the public spaces remains a critical challenge in developing countries, particularly in educational institutions and rural areas. This paper presents a smart vending machine for sanitary pads that was designed, constructed and tested. The system includes a number of technical features: IR (infrared)-enabled contactless activation at the point of use, two digital payment options (UPI/QR ) and one coin-based payment, real time WI-FI based payment verification, AI-enabled stock deletion prediction, and GSM-based remote alerting. A microcontroller-based ESP32 board is the core component and its firmware is developed using the Arduino framework. Transaction logging, stock monitoring, multi-machine dashboard visualization, etc., are handled through the Firebase Realtime Database with which the system is connected. A linear regression model that is trained using Firebase usage logs can predict when stock will run out. This enables planned restocking and minimizing stock-outs. The vending machine dispenses the product within 1.2 s of receiving a valid payment. (payment to dispensing), a dispensing accuracy of 95% was achieved over 20 dispensing trails, Firebase verification delay is 310ms, total hardware costs amount to about ₹2,045. The system developed here brings a low-cost, sanitary, and easy-to-maintain solution to the automated distribution of menstrual hygiene products
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[1] R. Patil, A. Deshmukh, and S. Kulkarni, "Coin-Operated Sanitary Napkin Vending Machine Using Arduino," Int. J. Eng. Res. Technol., vol. 10, no. 3, pp. 45–49, 2021.
[2] A. Kumar and P. Singh, "IoT-Based Smart Vending Machine with Online Payment Integration," Proc. IEEE Int. Conf. IoT and Smart Systems (ICISS), pp. 112–117, 2022.
[3] V. Sharma, R. Jain, and N. Patel, "GSM-Based Remote Monitoring and Alert System for Automated Dispensing Machines," Int. J. Adv. Res. Electron. Commun. Eng., vol. 9, no. 6, pp. 78–83, 2020.
[4] D. Mehta, K. Shah, and R. Verma, "LSTM-Based Demand Forecasting for Smart Vending Systems," IEEE Trans. Consumer Electron., vol. 69, no. 2, pp. 234–241, 2023.
[5] S. Gupta and T. Mishra, "Firebase Realtime Database for ESP32-Based IoT Payment Verification," Proc. Int. Conf. Emerging Trends Eng. Technol. (ICETET), pp. 56–61, 2022.
[6] P. Verma and R. Chauhan, "Automated Sanitary Napkin Vending System with GSM Alerting for Rural Schools," Int. J. Innov. Res. Sci. Eng. Technol., vol. 10, no. 5, pp. 112–118, 2021.
[7] S. Rao, M. Nair, and K. Pillai, "IoT-Enabled Dispensing System Using NodeMCU and Blynk for Hospital Environments," Int. J. Compute. Appl., vol. 184, no. 12, pp. 34–39, 2022.
[8] S. Bhorge, P. Avhad, G. Nemade, H. Sonarkar, and R. Dhawale, “IoT Based IV Pole Monitoring System,” in 2023 IEEE 8th International Conference for Convergence in Technology (I2CT), 2023, pp. 880–885, doi: 10.1109/I2CT57861.2023.10126408.
[9] A. Pusegaokar, R. Sonji, V. Revankar, and S. Bhorge, “VitaAir—Breathable Air in Processing Plants Using Internet of Things (IoT),” in Proceedings of the 2nd International Conference on Machine Learning and Autonomous Systems (ICMLAS 2025), 2025, pp. 740–744, doi: 10.1109/ICMLAS64557.2025.10968105.
[10] S. Bhorge, V. Mane, U. S. Salunkhe, S. S. Savane, and V. N. Rane, “Predictive Maintenance System with Secure Data Transmission Using Machine Learning and Signal Processing Techniques for Vibration Analysis,” in 2025 IEEE 2nd International Conference on Advances in Modern Age Technologies for Health and Engineering Science (AMATHE), 2025, doi: 10.1109/AMATHE65477.2025.11081320.
[11] P. Bisht, “AI-Based Detection of Phishing Attacks in Digital Payment Systems Using Explainable Machine Learning,” International Research Journal of Innovation in Science and Technology, vol. 1, no. 3, 2026, doi: 10.67308/irjist.083.
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Copyright (c) 2026 Anurag Gupta, Amey Wani, Parth Gurav, Sandhya Maske, Siddharth Bhorge (Author)
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