Implementing Microservice Architecture for An Elevator Monitoring System to Improve Scalability and Flexibility

The demand for more efficient and reliable elevator monitoring systems has increased due to security and safety issues in high-mobility buildings. This paper proposes a microservice architecture for an elevator monitoring system to enhance scalability, flexibility, and fault tolerance by decomposing the system into more minor, loosely coupled services. This paper will discuss the proposed system's design, implementation, and evaluation. The system, equipped with ESP32Cam and ultrasonic sensors, excels in real-time monitoring. Data is processed and analyzed using Python and OpenCV, allowing the system to not only count the number of people in the elevator but also detect any anomalies, ensuring the safety of the occupants. LED notification alerts, managed by NodeMCU8266, are triggered based on ultrasonic sensor data. MongoDB handles user management and analytical data, while the dashboard offers a user-friendly interface for real-time monitoring and system management provide essential information for elevator operators. The architecture's use of MQTT ensures efficient communication between sensors and services, creating a robust, scalable, and efficient solution.