Wireless sensor network for the detection and storage of industrial acoustic event data (LACCEI, 2024)
This study focuses on the designing and deployment of a Wireless Sensor Network that allows collection, storage and presentation of industrial acoustic contamination events data or dBA sound intensity which are measured through the implementation and programming of sensor nodes made up of Arduino UNO device and sound sensor MAX9814, this system sends the data through wireless transceiver module called nRF24L01 to a collecting device which is a Raspberry PI model B+ that receives the data by a like device nRF24L01. The collecting device performs a calibration data by software considering a percent relative error of less than ±5% which is calculated based on data measured by the UT353 Sonometer of UNI-T, finally, this device redirects the acoustic contamination events data to a database called Influxdb Cloud for a post analysis. The wireless sensor network deployment in a real environment is performed on the DANILACT enterprise that is dedicated to the manufacture and sale of products like mozzarella cheese, white cheese, milk, and yogurt. So, based on comments of administrative and operative personnel has been determined that the production processes generate annoying sound noise levels which have not been previously monitored for analysis, and in fact, the health of the enterprise‘s shift workers could be affected.