Bell Buddy: A Dual-Mode IoT-Based Smart Doorbell with Real-Time Facial Recognition and Intruder Alert System - TS, Sivakami; Binoy, Jasmin Maria; Jose, Alphia; Vijay, Hredya (International Journal of Computer Sciences and Engineering, 2025)
In the evolving landscape of home automation, security remains a top priority. This paper presents "Bell Buddy," a dual-mode smart doorbell system designed to enhance residential safety through real-time image processing and IoT integration. The system operates in two distinct modes: Doorbell Mode and Intruder Detection Mode. In Doorbell Mode, when the bell is pressed, a notification is instantly sent to the user`s mobile device, along with a captured image of the visitor for manual verification and remote access control. In Intruder Detection Mode, the system actively monitors for motion near the entrance and uses facial recognition algorithms to determine whether the detected individual is authorized or not. If an unknown face is identified, alerts are dispatched to both the user and predefined emergency contacts, while an audible alarm is triggered. The proposed system combines ESP32, Raspberry Pi, and cloud-based services for seamless real-time communication. The user interface is developed using React Native, while machine learning models trained using TensorFlow ensure accurate intruder detection. With end-to-end encryption and database integration, Bell Buddy offers an intelligent, efficient, and scalable solution for modern home security. The system has been evaluated on parameters such as recognition accuracy, notification speed, and reliability under varying environmental conditions.