IoT products are embedded with sensors that transmit live data about their use and environment. A key challenge for designers is to gather useful insights from this data in order to accelerate product research, which can be time consuming and labour intensive. Through the Chatty Products dashboard we aim to explore
how virtual representations of IoT products and their sensor data, also known as digital twins, can support insight gathering. This demo will present a series of Bluetooth IoT speakers, which are connected to the Chatty Products dashboard, a data exploration and visualisation research tool containing supervisory digital twinsof the speakers. The project aims to visualise live data as it relates to the physical product in the wild, enabling contextual inquiry and supporting data exploration. The demo will promote a dialogue around how digital twins can be used to gather design insights based on live data.@en

Chatty Factories is a three-year investment by the Engineering and Physical Sciences Research Council (EPSRC) through its programme for New Industrial Systems. The project explores the transformative potential of placing IoT-enabled data driven systems at the core of design and manufacturing processes. The research focuses on the opportunity to collect data from IoT-enabled sensors embedded in products during real-time use by consumers, explores how that data might be immediately transferred into usable information to inform design, and considers what characteristics of the manufacturing environment might optimise the response to such data. The project also considers implications arising for skills development in the education sector as well as ethics in manufacturing. In this paper we provide a vision for future “Chatty Factories”.

@en

A key challenge in carrying out product design research is obtaining rich contextual information about use in the wild. We present a method that algorithmically mediates between participants, researchers, and objects in order to enable real-time collaborative sensemaking. It facilitates contextual inquiry, revealing behaviours and motivations that frame product use in the wild. In particular, we are interested in developing a practice of use driven design, where products become research tools that generate design insights grounded in user experiences. The value of this method was explored through the deployment of a collection of Bluetooth speakers that capture and stream live data to remote but co-present researchers about their movementand operation. Researchers monitored a visualisation of the real-time data to build up a picture of how the speakers were being used, responding to moments of activity within the data, initiating text conversations and prompting participants to capture photos and video. Based on the findings of this explorative study, we discuss the value of this method, how it compares to contemporary research practices, and the potential of machine learning to scale it up for use within industrial contexts. As greater agency is given to both objects and algorithms, we explore ways to empower ethnographers and participants to actively collaborate within remote real-time research@en