One of the main benefits of large interactive surfaces (e.g. wall-sized displays) lies in their support for collocated collaboration by facilitating simultaneous interactions with the displays and high awareness of other group members' actions. In the context of remote collaboration, this awareness information needs to be acquired through digital means such as video feeds, which typically offer very limited information on non-verbal communication aspects, including on workspace awareness. We describe a new approach we have implemented to tackle that challenge through a multimodal pipeline that deals with tracking, attributing, transmitting, and visualising non-verbal information through what we refer to as workspace awareness cues, across wall-sized displays placed at distant locations. Our approach relies on commodity depth cameras combined with screen configuration information to generate deictic cues such as pointing targets and gaze direction. It also leverages recent artificial intelligence breakthroughs to attribute such cues to identified individuals and augment them with additional gestural interactions. In the present paper, we expand on the details and rationale behind our approach, describe its technical implementation, validate its novelty with regards to the existing literature, and report on early but promising results from an evaluation we conducted based on a mixed-presence decision-making scenario across two distant wall-sized displays.

In this paper, we present DeBORAh, a front-end, web-based software layer supporting orchestration of interactive spaces combining multiple devices and screens. DeBORAh uses a flexible approach to decompose multimedia content into containers and webpages, so that they can be displayed in various ways across devices. We describe the concept and implementation of DeBORAh and explain how it has been used to instantiate two different cross-device scenarios.

Nowadays, computational thinking skills are considered as fundamental for our future daily life and many initiatives and tools are created to foster these skills. In this paper, we present the Kniwwelino, a new platform for prototyping physical computing projects based on WiFi. The novelty of our solution lies in the use of a WiFi chip on a small, extendable board, programmable via a block based visual programming language, making the platform compact, low-cost, WiFi enabled, and accessible to children. This paper presents the design rationale and implementation of the platform as well as two simple, example projects making use of the new WiFi-based functionalities.