  The primary objective of non-intrusive load monitoring (NILM) techniques is
to monitor and track power consumption within residential buildings. This is
achieved by approximating the consumption of each individual appliance from the
aggregate energy measurements. Event-based NILM solutions are generally more
accurate than other methods. Our paper introduces a novel event detection
algorithm called Tukey's Fences-based event detector (TFED). This algorithm
uses the fast Fourier transform in conjunction with the Tukey fences rule to
detect variations in the aggregated current signal. The primary benefit of TFED
is its superior ability to accurately pinpoint the start times of events, as
demonstrated through simulations. Our findings reveal that the proposed
algorithm boasts an impressive 99% accuracy rate, surpassing the accuracy of
other recent works in the literature such as the Cepstrum and $\chi ^2$ GOF
statistic-based analyses, which only achieved 98% accuracy.
