Smart Me versus Smart Things: The Development of a Personal Resource Planning (PRP) System through Human Interactions with Data Enabled by the IoT

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Every day we see the development of new "smart" things and come closer and closer to the moment when the perfect "smart" home of the future becomes a reality. A "Smart" home, is one in which each appliance (thing) is not only controllable but is also "intelligent", ie. tailored to our individual needs. Yet, smart objects and smart homes often consider the individual as a passive entity to be 'served', rather than an empowered individual who can make smart decisions based on information. This is often because of the assumption that human cognition isn't able to take on the massive amount of information that could be generated from such smart objects. Indeed, very little is known about how people interact with data and how much of the data which we generate can actually inform our day-to-day decision making. We also do not know whether data generated within a home can change our consumption habits and behaviour. Finally, we are uncertain about whether and to what extent the data that we produce influences other decision makers in our household. Our project offers a new approach to answering these questions by observing actual household behaviour "in the wild" and developing a personal resource planning system (PRP) to support decisions made by individuals, ie. a smart 'me'. Our approach is different from existing IoT research in the following ways. First, while traditional research views the customer, who either accepts or rejects the product/service developed by businesses, to be outside the supply system, our approach offers a new perspective in which the customer is also viewed as an inside component of the supply system. This means that the customer, through his/her behaviour, becomes an inherent component of the supply system, and thereby transforms this system into a collaborative exchange system. This collaborative exchange system allows customers to interact with businesses and make decisions about how much customisation they would like to see in each product/service they themselves consume (e.g., Crowcroft et al., 2011; McAuley et al., 2011; Ng. et al., 2013). Second, since our approach has a person (customer) in the centre, the main focus of this project is to understand how "smart" things interact with human behaviour, and possibly how this behaviour can be informed by the new data from "smart" things to catalyse the appearance of a more informed "smart" consumer (e.g., Ng, 2012). Finally, our third contribution to existing research is to create data architecture through the IoT which would allow customers to make more informed "smart" decisions. In a way, the main output of this project will be a proof of concept that customers could be "nudged" into making "smarter" consumption decisions which would optimise business-customer interactions and create more value for each household.