Internet of Things is making everything smart through a network of items with sensors connected to the Internet (Minn et al., 2015). Smart devices are those items that connect to other devices or networks using wireless connectivity such as Wi-Fi, 5G (IGI Global, 2021). Smartphones, smart locks, smartwatches are examples of smart devices. The personal data according to the UK Data Protection Act (DPA) and the General Data Protection Regulation (GDPR) is any information that relates to an identified or identifiable individual such as name, email, NI number, location data (ICO, n.d.). Both the DPA and GDPR mandate that the design process for new products and services consider data protection and privacy risks within it. We argue that the cutting edge for storing personal data in the home and setting user preferences in smart devices requires research. Our research will (i) provide design and governance guidelines in a non-legalistic language for the manufacturers and the service providers of smart devices to consider in the design process for new products and services and (ii) consequently they will yield competitive advantage, and reduce their compliance, and data processing burden. (iii) Our research will bridge the gap between the manufacturers, service providers, privacy professionals and the regulators concerning the data protection and privacy risks leading to privacy issues in smart devices.
Why it is important? Smart device users lack understanding of data privacy (Marwick & Boyd, 2014) and control over how their personal data is shared and processed (Broenink et al., 2010). Our proposed research will (a) enable and empower the users of smart devices to make informed choices about how much and who they share their data with and therefore have control over their personal data. (b) So the users can enjoy the tailored services of smart devices, to improve convenience and not worry about their data privacy.
We will do this through co-creation of design and governance guidelines. A technical standpoint of our starting position is to assume a solution that brings data processing and storage closer to where it is generated, such as the Databox (McAuley et al., 2016). The guidelines for the solution will cover the user interface and interactions, so users can model their privacy settings and preferences without difficulty, it will also cover areas such as user authentication and security.
This author is supported by the Horizon Centre for Doctoral Training at the University of Nottingham (UKRI Grant No. EP/S023305/1).