Smart Alarm IoT System: Monitoring Elevator Traffic and Meteorological Data on Job Sites Using MQTT and InfluxDB integrated with Grafana

In this paper, we design and implement an IoT system as part of a comprehensive solution to collect and analyze meteorologiacal and elevator traffic data at job sites, with the ultimate goal of developing a sophisticated smart alarm system. This system is designed to wake workers at an optimal time, considering various job site conditions to minimize delays and ensure timely arrival. The system utilizes MQTT to publish data from various stations across the site, with a central station subscribing to this data for further processing. InfluxDB is employed as the cloud storage solution for structured data, which is then integrated with Grafana for advanced analysis. This allows us to determine peak elevator traffic hours and average daily outside temperatures in addition to fuel tank level estimation of heating system. This done by using a Raspberry-Pi with a camera captures periodic images, which are published to an MQTT broker. The main PC subscribes to this topic, processes the images to detect the number of faces; which represent the elevator traffic load at this moment of capturing the photo; then sends the results with timestamps to InfluxDB, alongside meteorological data. In addition to job site monitoring we implement the rout to work system to log the time needed by attached a GSM module in the body of the car. These analyses are crucial for developing the next phase of the Smart wakeup Alarm IoT system. The system underscores the potential of IoT technologies in reducing worker delays and improving punctuality