Abstract
1 tmawer@uj.ac.za 2 johanm@uj.ac.za 3 svonsolms@uj.ac.za Abstract— This paper focuses on the exploration into reducing the cost of low accuracy, internet of things sensors through the application of the statistical algorithm known as the Kalman filter. The Kalman filter is used to make accurate estimations from noisy data. With this application, one can substitute a reliable and accurate but costly internet of things sensor with at least two more cost effective sensors and a Kalman filter to produce comparable results.