Smart Vault Security Through Self-Calibrating Weight Analytics, IoT, Blockchain, and Machine Learning

This paper enhances vault security by integrating IoT, blockchain, and machine learning to monitor banknote weight. Blockchain ensures secure, tamper-proof storage of weight data, helping detect inconsistencies and potential theft. Machine learning models, including Linear Regression, Lasso Regression, KNN, SVM, and Random Forest, predict banknote count based on weight, with Linear and Lasso Regression achieving the highest accuracy. Challenges like data limitations and computational constraints are addressed, with recommendations for improvements. By combining these technologies, the system strengthens vault security, prevents theft, and ensures data integrity, offering a reliable solution for safeguarding physical currency.