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Falls are dangerous for the elderly, often causing serious injuries especially when the fallen person stays on the ground for a long time without assistance. This paper extends our previous work on the development of a Fall Detection System (FDS) using an inertial measurement unit worn at the waist. Data come from SisFall, a publicly available dataset containing records of Activities of Daily Living and falls. We first applied a preprocessing and a feature extraction stage before using five Machine Learning algorithms, allowing us to compare them. Ensemble learning algorithms such as Random Forest and Gradient Boosting have the best performance, with a Sensitivity and Specificity both close to 99%. Our contribution is: a multi-class classification approach for fall detection combined with a study of the effect of the sensors’ sampling rate on the performance of the FDS. Our multi-class classification approach splits the fall into three phases: pre-fall, impact, post-fall. The extension to a multi-class problem is not trivial and we present a well-performing solution. We experimented sampling rates between 1 and 200 Hz. The results show that, while high sampling rates tend to improve performance, a sampling rate of 50 Hz is generally sufficient for an accurate detection.

Information and communication technologies are central tools for Humanitarian Organizations operations. ICT field specialists are real practical experts, but the lack of theoretical knowledge prevents them from being self-sufficient and efficient in unexpected situations. United Nations (UN) members have agreed on defining 17 Sustainable Development Goals (SDG). As a University of Applied Sciences, we are concerned about the development of skills in information and communication technologies (ICT). This concern is shared in the “SDG 4: Quality education”. Training can be a controversial topic in the humanitarian field because of the priority of operations activities. Our aim was to design a training device which could cope with this priority. Through our partnership with a Humanitarian Organization (HO), we built a full and innovating hybrid training methodology for ICT field specialists. This methodology is based on state-of-the-art education and ergonomics techniques. Work analysis and ergonomic theory assume that in order to offer a pertinent and transferable training, the learnings must be built on the real work the trainees do. In this study, we present our global training concept in broad terms. We focus here on the results of the first implemented phase. This phase concerns the assessment of the ICT theoretical knowledge of our HO partner's specialists.

This paper examines the design and implementation of a system to support firefighting exercises based on tools and ideas of pervasive computing. Through this development a range of technologies and conceptual tools were used, such as sensors, wireless communication, and the programming framework uMove; as well as context-awareness, situation management, and activity detection. In this development, the notion of implicit human-computer interaction was of particular relevance. The use of a programming framework for interaction through motion was central, and this implementation is one of its proofs of concept, as it presented opportunities to improve it and recommendations to adapt it for future applications.

This chapter presents a conceptual framework for an emerging type of user interfaces for mobile ubiquitous computing systems, and focuses in particular on the interaction through motion of people and objects in physical space. We introduce the notion of Kinetic User Interface as a unifying framework and a middleware for the design of pervasive interfaces, in which motion is considered as the primary input modality.

The greenhouse gas effect has become a major preoccupation worldwide. Heating of buildings and houses is one of the major sources of this effect. We propose to optimize heating control systems by directly integrating the recognition of people activities and context in the process of temperature regulation. We introduce the concept of kinetic-awareness as a way of making heating control system aware of userspsila motion in the physical space in order to adjust temperature according to their current activities.

This chapter presents a conceptual framework for an emerging type of user interfaces for mobile ubiquitous computing systems, and focuses in particular on the interaction through motion of people and objects in physical space. We introduce the notion of Kinetic User Interface as a unifying framework and a middleware for the design of pervasive interfaces, in which motion is considered as the primary input modality.

In this paper we address the problem of collaborative workflow in mobile environments. Specifically, we present a solution for opportunistic task assignment to mobile users based on location, context and motion awareness. As an example of this approach, we present an application based on the new Kinetic User Interface framework where users participate to dynamic workflow through their displacement in designated active zones.