Smart technologies in reducing carbon emission: Artificial intelligence and smart water meter
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Global warming caused by greenhouse gases (GHG) is regarded as one of the biggest threats facing our world. Climate scientists predict that a 1.5°C rise in global temperature may cause the extinction of 25% of the Earth's animals and plants disappear. In this fearsome prospect, carbon emission was identified as the main factor contributing to this issue, and needed to be effectively controlled to mitigate their detrimental impacts on the environment as well as human life. GHG mitigation requires developing and implementing policies, and utilizing new technologies to reduce GHG. In this paper, we explore the role of smart technologies in reducing the carbon emission. With the increasing deployment of Smart water meters across Australia in the last five years, an intelligent and knowledge base system called Autoflow© has been developed to help: (i) monitor and predict carbon emission level from water consumption in realtime (e.g. Property A: Carbon emission from 6am-6pm tomorrow is 12.4kg), and (ii) suggest options for reducing water consumption and carbon emission. This Autoflow© system operates based on smart algorithms including Dynamic Time Warping, Hidden Markov Model, Dynamic Harmonic Regression and Artificial Neural Network, and has potential to go beyond Australian border in a very near future to help effectively sustain the limited water resource and environment around the word.
Proceedings of the 2017 9th International Conference on Machine Learning and Computing: ICMLC 2017
Artificial Intelligence and Image Processing not elsewhere classified