Usage prediction of appliances in filipino households using Bayesian algorithm

The standby power accumulated after some time contributes to the wasted energy of a household and can be noticeable in a home's power consumption. In this study, the group aims to devise a standby power management system that is able to adapt constantly with one's changing lifestyle. To know the appliances available in households, a survey with 230 respondents was conducted and the most common appliances were taken into consideration. The power measurements of the appliances were also recorded using a power meter. The data log was conducted by members of different households for the activation of the appliances, the users, and the occupancy of the household. The mentioned factors from the usage log was then used on the Bayesian algorithm, which was used to calculate the probability of usage of the appliances. This learning prediction, in addition, to a power management system will minimize the power consumed by appliances in standby mode, thus saving energy and income.

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