Development of a Scalable Industrial Process Monitoring Sensor System for Large-Scale IoT Networks using MQTT and Time Series Database

This research paper presents the design process and implementation of a large-scale industrial Process Monitoring Sensor System for large-scale IoT deployments. With the rising popularity of IoT devices, a major concern is the ease of use and integration of these off-the-shelf devices into the existing infrastructure of embedded systems. This paper focuses on building easy-to-use back end and front-end software that can be interfaced to any sensor that uses the widely popular MQTT protocol. By utilizing a Time Series database to store the acquired data, the system can deliver precise range queries which can produce powerful data visualizations for key insights. The proposed system can be hosted on any cloud service provider and was tested extensively with both off-the-shelf commercially available sensor modules and sensors developed using the ESP32 microcontroller series. All peripherals used are commonly used in industrial cases and the sensors use Wi-Fi (IEEE 802.11b/g). The experiment demonstrates successful data acquisition of both telemetry and events from five different sensor modules into a time series database.