In our increasingly tech-saturated world, from mobile apps and health sensors to autonomous cars and factory robots, we expect these devices to seamlessly integrate into our lives, enhancing safety and convenience. However, as these devices proliferate and their autonomy grows, ensuring they provide unobtrusive, yet effective support becomes crucial. The Horizon Europe KST multi-partner project “Distributed Multi-Sensor Systems for Human Safety and Health” (DistriMuSe) intends to support human health and safety by improved sensing of human presence, behaviour, and vital signs in a collaborative or common environment by means of multi-sensor systems, distributed processing and MachinelDeep Learning (ML/DL) techniques. In this paper, we focus on the DistriMuSe's approach on sports performance and health assessment, focusing on monitoring the physical activity of non-professional and hobby athletes, people who like sports and care about their health, elderly healthy people, and subjects affected by neurological disability (e.g., Parkinson's disease). The overall goal is to measure activity and exertion, estimating performance levels and determining maximum effort. We discuss the overall system-of-systems architecture, focusing on the adopted technologies.

This paper provides an overview of the domain challenges, use cases, objectives, high-level concepts, intended innovations, and expected impact of the DistriMuSe project. The project’s main aim is to enhance human health and safety by improved sensing of human presence, behaviour, intentions and vital signs in a collaborative or common environment by means of multi-sensor systems, distributed processing and machine learning. The use cases address challenges in health monitoring of elderly, sleep and exercise, of drivers and vulnerable road users in traffic and of people interacting with robots in a factory environment. Technical development in the project focuses on unobtrusive monitoring sensors, multi-sensor systems, distribution of computation and intelligence, and domain specific needs for the use cases.

This paper describes the NextPerception project’s outcomes organized as examples motivated by user stories. The project developed next-generation perception sensors and enhanced the distributed intelligence paradigm to build versatile, secure, reliable and proactive human monitoring systems, in turn applied in use cases in health and automotive domains.

This is a position paper that introduces intention awareness (IA) as a counterfactual approach for designing IA technologies. The approach distinguishes human intention as a premise for developing intention-aware systems. Intention-aware technologies utilise information about the user's intentions to improve the services that are provided by the environment. The paper will initially define intention awareness as a concept, and subsequently introduce four scenarios that illustrate the approach.

This paper proposes a 'Thing'-centric simple rule editor for the Internet of Things. The demonstration is aimed at laymen to connect and configure sensors and their home appliances. In providing a tool for simple do-it-yourself configurations, we present a user-centric approach for the combining and configuring of tasks that can be deployed in highly diverse domestic contexts, with heterogeneous resources available and with deployment environments changing over time. Composing and configuring the tasks of the sensors and devices take center stage in our 'Thing' - or object-centric prototype. An important part of the user-centric editing tool is the visualization scheme for the graphical representation of the heterogeneous sensors and devices, combined with verbal instructions for editing.

In this paper we describe the co-design process of a proof-of-concept home control system, and how it was carried out by utilising a user-centred design methodology. The aim was to develop a demonstrator of a home control system that supports elderly people in living more independently in their homes. The focus of the research was on the configuration tool of the environment, which was meant to be exploited in a nursing home. The home control system was intended to be used and configured by non-technologically versed users: mainly the care personnel, but also the inhabitants and their close relatives. The system was co-designed and evaluated at first with nurses, who were considered to be the local experts of the chosen ecosystem. The final web-based proof-of-concept system was evaluated with nurses and end-users.

This paper presents a solution for creating light-weighted content and context-aware mobile multimedia services. The main application domain is in user created multimedia content and experience sharing. Our approach is to have a platform supporting state-of-the art content management functionalities in order to enable easy creation of specialized multimedia services for various target groups and purposes. We have developed a mobile multimedia content creation platform with integrated context metadata support. To verify the overall functionality of our platform we have defined a multimedia content service template and created a set of exemplary services using Web-based technologies such as JavaScript, media RSS feed and Java.

Visualization method is proposed as an additional feature for accelerometer-based gesture control. The motivation for visualization of gesture control is justified and the challenges related to visualization are presented. The gesture control is based on Hidden Markov Models. This paper describes basic concepts of the gesture visualization and studies how well the developed visualization method can animate hand movement performed during the gesture control. The results indicate that visualization clearly provides information about the performed gesture, and it could be utilized in providing essential feedback and guidance to the user in future gesture control applications.

The wide availability of digital recording devices leads to investigate how multimedia content can be navigated beyond a desktop computer set up. We present a system and a variety of applications, to navigate multimedia recordings from visits making use of: large multiple projections, location information to organise media and re-experience aspects of visits, physical interfaces as gesture-based interaction and other interfaces that render media more tangible and therefore more readily available. Analysing field trials we discuss the expressiveness and experiential aspects of gesture based interfaces as important features in navigating multimedia in "immersive" environments.

The objective of this research is the development of a general purpose image understanding system. The object-oriented libraries described in this paper contain object definitions of image features, operators to deal with these features, and a framework for storage. Upon creation of an image feature, links are established from this feature to source features and upon request other links may be established to otherwise related features. Referring to single features or groups of features may be done by a property selection rule. The first aim is to find and store perceptual groupings found in an image by bottom-up processing for later use by a top-down image understanding system.>