Publication | Closed Access
Development of a Smart Home Context-aware Application: A Machine Learning based Approach
23
Citations
10
References
2015
Year
EngineeringMachine LearningSmart CityWearable TechnologyHome AutomationSmart EnvironmentIntelligent SystemsBuilt EnvironmentData ScienceData MiningPattern RecognitionSmart SystemsInternet Of ThingsK Nearest NeighborsAssistive TechnologyMobile ComputingComputer ScienceSmart HomeMahalanobis DistanceSmart LivingContext-aware Pervasive System
Context-awareness is an important characteristic of smart home. Several methods are used in context-aware application to provide services. The main target of smart home is to predict the demand of home users and proactively provide the proper services by computing user’s context information. In this paper, we present a context-aware application which can provide service according to predefined choice of user. It uses Mahalanobis distance based k nearest neighbors classifier technique for inference of predefined service. We combine the features of supervised and unsupervised machine learning in the proposed application. This application can also adapt itself when the choice of user is changed by using Q-learning reinforcement learning algorithm.
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