Table 2 Basic differences between Autoflow© and AutoflowU
From: An adaptive model for the autonomous monitoring and management of water end use
Features | Autoflow© | Autoflow U | |
|---|---|---|---|
Version 2.1 | Version 3.1 | Version 1.0 | |
Released date | December 2013 | September 2018 | November 2018 |
Model development | Rely on available water end use data for model training | Do not require any existing data for development and calibration | |
Applied techniques | • Hidden Markov Model • Dynamic Time Warping Algorithm • Time of day Probability | • Hidden Markov Model • Dynamic Time Warping Algorithm • Deep Learning (Stacked Auto-encoder) • Time of day Probability • K-means clustering • Self Organising Map | • Dynamic Time Warping algorithm • Self Organising Map • Decision Tree Method |
Available categories for categorisation | 8 – Shower, Bath, Irrigation, Clothes washer, Dishwasher, Evaporative Cooler, Toilet, Tap | 7 – Shower, Irrigation, Clothes washer, Dishwasher, Evaporative Cooler, Toilet, Tap. (*) Shower and Bath are merged into one single category | |
Obtained accuracy when analysing different dataset | |||
Australia data | 75.0–92.0 | 76.3–93.5 | 72.1–92.3 |
US data | 72.5–90.6 | 72.5–90.6 | 74.2–92.2 |