In this paper we describe the development of two heat and movement-sensitive sonic textile prototypes. The prototypes interactively sonify in real-time the bodily temperature of the person who wears them, complementing the user’s felt experience of warmth. The main aim is making users aware of the heat exchanges between the body, the fabric, and the surrounding environment through non-intrusive and creative sonic interactions. After describing the design challenges and the technical development of the prototypes - in terms of textile fabrication, electronics and sound components - we discuss the results of two user experiments. In the first experiment, two different sonification approaches were evaluated allowing us to select the most appropriate for the task. The prototypes’ use-experience was explored in the second experiment.

In this paper we describe the development of two heat and movement-sensitive sonic textile prototypes. The prototypes interactively sonify in real-time the bodily temperature of the person who wears them, complementing the user’s felt experience of warmth. The main aim is making users aware of the heat exchanges between the body, the fabric, and the surrounding environment through nonintrusive and creative sonic interactions. After describing the design challenges and the technical development of the prototypes - in terms of textile fabrication, electronics and sound components - we discuss the results of two user experiments. In the first experiment, two different sonification approaches were evaluated allowing us to select the most appropriate for the task. The prototypes’ use-experience was explored in the second experiment.

In this paper we present a system for the sonification of the electricity drawn by different household appliances. The system uses SpecSinGAN as the basis for the sound design, which is an unconditional generative architecture that takes a single one-shot sound effect (e.g., a fire crackle) and produces novel variations of it. SpecSinGAN is based on single-image generative adversarial networks that learn from the internal distribution of a single training example (in this case the spectrogram of the sound file) to generate novel variations of it, removing the need of a large dataset. In our system, we use a python script in a Raspberry PI to receive the data of the electricity drawn by an appliance via a Smart Plug. The data is then sent to a Pure Data patch via Open Sound Control. The electricity drawn is mapped to the sound of fire, which is generated in real-time using Pure Data by mixing different variations of four fire sounds - a fire crackle, a low end fire rumble, a mid level rumble, and hiss - which were synthesised offline by SpecSinGAN. The result is a dynamic fire sound that is never the same, and that grows in intensity depending on the electricity consumption. The density of the crackles and the level of the rumbles increase with the electricity consumption. We pilot tested the system in two households, and with different appliances. Results confirm that, from a technical standpoint, the sonification system responds as intended, and that it provides an intuitive auditory display of the energy consumed by different appliances. In particular, this sonification is useful in drawing attention to “invisible” energy consumption. Finally, we discuss these results and future work.

In this paper we present our prototype of a sound augmented blanket. With this artifact we aim to investigate the potential to achieve sonic implicit interactions through auditory augmentation of fabrics. We describe the development of a blanket that sonifies the approximate temperature exchange between the body and the fabric, using sound as a medium of interaction and a carrier of information. We propose different methods for auditory augmentation of fabrics through a piezoelectric contact microphone used for movement sensing. After describing the technical development of the prototype, we discuss our early findings from a qualitative standpoint, focusing on the process of sense-making of such an artifact from an evaluation based on free exploration. Our preliminary results suggest that different auditory augmentation models encourage different affordances, and are able to provide a simple creative and aesthetic experience. The ability of the chosen sonic interaction models to effectively communicate information should however be further investigated.

As buildings become increasingly automated and energy efficient, the relative impact of occupants on the overall building carbon footprint is expected to increase. Research shows that by changing occupant behaviour energy savings between 5 and 15 % could be achieved. A commonly used device for energy-related behaviour change is the smart meter, a visual-based interface which provides users with data about energy consumption and emissions of their household. This paper approaches the problem from a Sonic Interaction Design point of view, with the aim of developing an alternative, sound-based design to provide feedback about some of the data usually accessed through smart meters. In this work, we experimented with sonic augmentation of a common household object, a door mat, in order to provide a non-intrusive everyday sonic interaction. The prototype that we built is an energy-aware sonic carpet that provides real-time feedback on home electricity consumption and emissions through sound. An experiment has been designed to evaluate the prototype from a user experience perspective, and to assess how users understand the chosen sonifications.