Logarithmic Regression Model to Estimate the Maximum Values of Ultraviolet Irradiance Measurements in an Internet of Things Based Monitoring System

A monitoring system based on the Internet of Things has been designed and implemented to measure ultraviolet irradiance, which is made up of a series of static sensors installed in a defined geographical region, together with a processing and communication system send the measurements to a centralized database and this data is shown by the HTTP protocol; however, the measurements obtained come from static sensors, and would be better to obtain them from mobile sensors that are always pointing directly at the sun and this sensors would obtain the maximum value of ultraviolet irradiance at the moment of taking a measurement, thus these data may be relevant as a source of information. To obtain the maximum values of the measurements, it is necessary to design and implement another mobile measurement system that at all times points directly at the sun, however, the design, implementation and maintenance make it too difficult and expensive to maintain the reliability of the information which provides the monitoring system; therefore, a logarithmic regression model has been developed to obtain the values of maximum ultraviolet radiation measurements based on the measurements of the static sensors that constantly make measurements and based on samples of the mobile sensors, so the system can show information relevant using static sensors.