# Individual Environmental Risk Assessment and Management in Industry 4.0: An IoT-Based Model
## 3 Results
### Tests with the Monitoring Device, Mosquito, Telegraf, InfluxDB, and Grafana  
Figures 5-7 show the temperature, humidity, and illuminance graphs generated by Grafana. As can be seen in these figures, the integration of our server-side applications (web server, Mosquito, Telegraf, InfluxDB, and Grafana) worked properly, as well as the communication of the monitoring device with the server. The measurements obtained from the DHT11 sensor were by the temperature set in the air conditioner. In addition, these measurements were checked every hour with the Room Temperature Thermometer smartphone app [49]. The readings differed by up to one degree and 1%, respectively. Such results are consistent with the specifications of the DHT11 sensor.  
Figure 4: Example of job history with health details.  
Figure 5: Temperature graph.  
Figure 6: Relative humidity graph.  
Figure 7: Illuminance graph.  
As can be seen in Figure 5, it is possible to display details about a specific moment by positioning the mouse at the desired point. The minimum, maximum, and mean measurements for the entire period, in this case, 12 h, are also displayed. These preferences may be set in Grafana.  
To verify the illuminance measurements obtained by the sensor, the Light Meter smartphone app [50] was used. The environment had constant artificial lighting during the entire period, and the measured values varied from 90 up to 109 lx in the sensor readings throughout the tests. Light Meter presented values very close to these, from 93 to 116 lx. The measurements were taken every hour.  
From the tests carried out, it was possible to verify that the server features--memory, disk, and CPU--are adequate for the present stage of the study. However, if it was necessary to significantly increase the number of workers and monitoring devices (for example, to store data from hundreds of workers and consequently handle messages sent by hundreds of devices), it would be necessary to expand these resources. The integration of Mosquitto, Telegraf, InfluxDB, and Grafana proved to be suitable for the system once these solutions did not fail during the tests. It is important to point out that Mosquitto can be configured to send and receive messages with or without encryption, according to the needs of each application. In addition, Grafana has a user-friendly interface and may be used with several databases. In this way, the use of Grafana in our system creates possibilities for integration with other applications. As mentioned earlier, all server-side solutions are free software, and they are constantly updated and improved, in addition to being used by several companies and having extensive documentation available on the Internet.  
The monitoring device worked correctly, and the chosen sensors proved to be suitable for the system, as well as the ESP32. However, the prototype was assembled with just a few sensors on a breadboard, and this breadboard remained static during the tests. In the future stage of this study, the tests should be performed in the laboratory with the device complete and in motion and then in a real work environment.  
There is a wide variety of sensors for the same purposes, and in general, their integration with the ESP32 is easy. Sensor costs may vary widely, and for this study, the use of very low-cost solutions was prioritized, aiming at the design of a solution that can be used with many workers and with a viable cost for companies.