A Deep Belief Network for Electricity Utilisation Feature Analysis of Air Conditioners Using a Smart IoT Platform
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Currently, electricity consumption and feedback mechanisms are being widely researched in Internet ofThings (IoT) areas to realise power consumption monitoring and management through the remote control ofappliances. This paper aims to develop a smart electricity utilisation IoT platform with a deep belief networkfor electricity utilisation feature modelling. In the end node of electricity utilisation, a smart monitoring andcontrol module is developed for automatically operating air conditioners with a gateway, which connects andcontrols the appliances through an embedded ZigBee solution. To collect electricity consumption data, aprogrammable smart IoT gateway is developed to connect an IoT cloud server of smart electricity utilisationvia the Internet and report the operational parameters and working states. The cloud platform manages thebehaviour planning functions of the energy-saving strategies based on the power consumption featuresanalysed by a deep belief network algorithm, which enables the automatic classification of the electricityutilisation situation. Besides increasing the user’s comfort and improving the user’s experience, theestablished feature models provide reliable information and effective control suggestions for power reductionby refining the air conditioner operation habits of each house. In addition, several data visualisationtechnologies are utilised to present the power consumption datasets intuitively.
Abstract
Currently, electricity consumption and feedback mechanisms are being widely researched in Internet ofThings (IoT) areas to realise power consumption monitoring and management through the remote control ofappliances. This paper aims to develop a smart electricity utilisation IoT platform with a deep belief networkfor electricity utilisation feature modelling. In the end node of electricity utilisation, a smart monitoring andcontrol module is developed for automatically operating air conditioners with a gateway, which connects andcontrols the appliances through an embedded ZigBee solution. To collect electricity consumption data, aprogrammable smart IoT gateway is developed to connect an IoT cloud server of smart electricity utilisationvia the Internet and report the operational parameters and working states. The cloud platform manages thebehaviour planning functions of the energy-saving strategies based on the power consumption featuresanalysed by a deep belief network algorithm, which enables the automatic classification of the electricityutilisation situation. Besides increasing the user’s comfort and improving the user’s experience, theestablished feature models provide reliable information and effective control suggestions for power reductionby refining the air conditioner operation habits of each house. In addition, several data visualisationtechnologies are utilised to present the power consumption datasets intuitively.
참고문헌 (27)
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