Pingu: A New Miniature Wearable Device for Ubiquitous Computing Environments

TLDR

Around Device Interaction (ADI) is a recent HCI paradigm that enables touch‑less, intuitive interaction beyond the physical boundaries of computing devices. This work introduces Pingu, a fingering ADI input device that lets users wirelessly interact with any nearby computing device in ubiquitous environments. Pingu consists of a fingering form factor equipped with multiple sensors, visual and vibrotactile feedback, and wireless connectivity, enabling gesture, tactile, and touch interactions for applications such as social interaction, context recognition, in‑car use, and physical activity analysis. The device enables advanced, compact gestural interaction across diverse devices, mobile and networked sensing, and social computing.

Abstract

Around Device Interaction (ADI) is recently introduced in the field of Human Computer Interaction (HCI)to provide touch less, more intuitive way of interaction using space beyond the physical boundary of the computing devices. In this paper, we introduce a new ADI input device called Pingu in the form factor of a fingering that allows users to interact with any nearby computing device with wireless connectivity in a ubiquitous environment. Fingering form factor is chosen for our prototype design, as it is socially acceptable and is commonly worn in everyday social contexts, and based on the previous research, the information entropy of interaction by fingers is greater than the entropy for any other parts of the human body. The current Pingu prototype is consisted of an extensive set of sensors, visual and vibrot actile feedback mechanisms with wireless connectivity that make it a unique input device for human-computer or human-human interaction in the form of gestures, tactile and touch. Its usage can range from advanced, tiny and novel gestural interaction with a variety of devices to mobile and networked sensing, and social computing. We present a few potential applications of Pingu such as social interaction, context recognition, in-car interaction, and physical activity analysis.