DUAL AUTHENTICATED SMART DOOR LOCKS USING MACHINE LEARNING TECHNIQUE
Satvik V, Rohit M and U. Vignesh
School of Computer Science and EngineeringVellore Institute of Technology, Chennai, Tamil Nadu – 600127, India
Abstract: This research is about a door lock system that combines RFID and keypad authentication, along with a simple user interface for easy use. The system records each successful entry in a database, noting the time and method of access. The keypad password is stored encrypted in the database for security reasons. The main goal is to improve security by using machine learning to spot unusual access patterns that could mean a potential security issue. By using past access data, a model is created to identify unusual times when the door is opened, which could indicate unauthorized access. The machine learning model learns from regular access records to recognize normal patterns and alert users if anything out of the ordinary happens. This system not only makes traditional door locks more secure but also adds smart features that adapt and learn over time, making it a proactive solution for detecting intruders. This combination of hardware, data analysis, and machine learning helps create a strong security solution for homes and businesses. Additionally, the system is designed to be energy efficient by using a PIR sensor to only power the system when movement is detected, ensuring minimal energy consumption.
Keywords: RFID, Keypad Authentication, Door Lock System, Machine Learning, Anomaly Detection, Security Systems, Access Control, Data Encryption, Smart Locks, Internet of Things (IoT).