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The spread of sensor technologies in the past decade has given rise to several ideas that assimilate the physical world with the virtual one. One such idea has been termed the Internet of Things (IoT). The Internet of Things describes the evolution from systems linking digital information, to systems relating digital information to real world physical items. In this sphere the Internet connects with our routines through this network of connected objects.Given the potentially vast amount of data stream from IoT systems, an increasingly important feature of these systems will include applications and algorithms to fuse, interpret, augment and present information from smart objects. Data mining as applied to "business intelligence" applications may play a role but may be inadequate to address the relationships between smart objects. This is where the established view of data mining may diverge and techniques currently applied to understanding human behaviour and interactions may be applicable to IoT systems.Reality Mining is one such technique. This paper proposes our vision of applying techniques developed to understand human relationships to the Internet of Things, which will allow for the identification of patterns and interactions between smart objects. We also present an analysis of issues to be resolved to realise such a vision.

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