SPECIAL SESSION #4
Measurement of Well-Being and Comfort for Aging Populations: How Technology Can Foster Age-Friendly Environments
ORGANIZED BY
Sara Casaccia
Sara Casaccia
University Polytechnic of Marche, Italy
Gian Marco Revel
Gian Marco Revel
University Polytechnic of Marche, Italy
Riccardo Caponetto
Riccardo Caponetto
University of Messina, Italy
Andrea Monteriù
Andrea Monteriù
University Polytechnic of Marche, Italy
Laura Burattini
Laura Burattini
University Polytechnic of Marche, Italy
Ennio Gambi
Ennio Gambi
University Polytechnic of Marche, Italy
Luca Marinelli
Luca Marinelli
University Polytechnic of Marche, Italy
ABSTRACT
Living environments should enable aging individuals to remain independent, active, and healthy. To achieve this, these spaces must be designed as age-friendly, ensuring a healthy lifestyle for all residents, fostering social interactions, and enabling participation in community life. In this context, technology plays a pivotal role in creating age-friendly environments that support independent living and enhance the quality of life for older adults.
By measuring the activities and comfort of aging individuals in multi-resident settings, it becomes possible to detect changes in behavior, Activities of Daily Living (ADLs), and risk factors such as falls or environmental conditions that may negatively impact health. For older adults, understanding each resident's individual perception of comfort is particularly important to improve their well-being and secure their engagement and cooperation.
However, monitoring activities and comfort in multi-resident contexts presents significant challenges. Unlike single-resident scenarios, where sensor data directly corresponds to one person's activities and comfort levels, multi-resident environments involve overlapping signals. This makes it difficult and costly to accurately associate activities and comfort perceptions with specific individuals.
This special session focuses on exploring technologies, methodologies, and future perspectives for developing age-friendly environments, with a particular emphasis on emerging sensors and applications such as robotics, wearable devices, mobile health (m-health) systems, Artificial Intelligence (AI), and more. The aim is to improve the well-being and comfort of aging populations in various living settings, including multi-resident scenarios. Contributions detailing the development of systems with a metrological perspective—such as considerations of measurement uncertainty, sensor accuracy, and reliability—are highly encouraged. Such examples demonstrate how these systems can be tailored for different user needs and diverse environments.
This special session is organized as part of the Age-SenseAI project, a cascade call within the Age-It PNRR initiative. The objective of Age-SenseAI is to develop an innovative sensory ecosystem for monitoring the activities and comfort of older adults in multi-resident environments. The project leverages advanced sensor networks, robotics, Data Fusion techniques, and Artificial Intelligence to address the unique challenges of these complex settings, where multiple individuals share the same living space.
TOPICS
Topics of interest for this Special Session include, but are not limited to:
- Non-invasive sensors for ageing people;
- Innovative sensor network for living environments;
- Sensor network optimization;
- New services to improve life of ageing people and their caregivers;
- Human-centric technology solutions design;
- Assistive & social robotics and virtual coaches;
- Data analysis techniques, e.g. AI learning methods, and Data Fusion to measure well-being, activity, health status, comfort, etc. of ageing people;
- Measurement of activity in indoor and outdoor environments;
- Measurement of thermal, visual, air quality and acoustic comfort specific for ageing people;
- Measurement of uncertainty in the field of age-friendly environement.
ABOUT THE ORGANIZERS
Sara Casaccia is Assistant Professor in Mechanical and Thermal Measurement at the Department of Industrial Engineering and Mathematical Sciences (DIISM) of Università Politecnica delle Marche (UNIVPM). Her research is focused on measurement techniques and sensing systems for supporting people in living environments (e.g. comfort, wellbeing), data processing to extract complex information (e.g. using AI), sensors for health and Active and Assisted Living applications, buildings, industrial applications and non-destructive techniques.
Gian Marco Revel is Full Professor in Mechanical and Thermal Measurement at Università Politecnica delle Marche, where he is Rector Delegate for European Research. He received the Ph.D. degree in mechanical measurements from Università degli Studi di Padova in 1998. His research focuses on sensors and measurement technologies for buildings, health and industrial applications, with a particular focus on comfort and human behaviour and diagnostics.
Riccardo Caponetto received the electronic degree from the University of Catania in 1991 and then the Ph.D. in 1994 from the same University. Starting from 1994 he has been working as researcher at STMicroelectronics, Catania site. Since 2001 he was assistant professor at the D.I.E.E.S of the Engineering Faculty, Enna branch, of the University of Catania. From 2018 Associate professor at University of Catania, DIEEI and from 2023 full Professor at University of Messina. His interest includes: Systems modeling and control, Fractional order systems, Home and building automation and Soft computing techniques.Bibliometric.
Andrea Monteriù is Associate Professor in Systems and Control at Università Politecnica delle Marche where he is also the Principal Investigator of the Laboratory of Artificially Intelligent Robotics (LAIR). His thesis was developed at the Department of Automation at the Technical University of Denmark. In 2005, he was a visiting researcher at the Center for Robot Assisted Search & Rescue at the University of South Florida, where he developed part of his PhD thesis. His research interests mainly focus on the areas of robotics and intelligent autonomous systems, assistive and service robotics, assistive technologies, and fault-tolerant diagnosis and control applied to intelligent robotic systems.
Laura Burattini is Full Professor of Bioengineering at the Department of Information Engineering of Università Politecnica delle Marche. She received the PhD degree in electrical/biomedical engineering at the University of Rochester (USA) in 1998 and the master’s degree in electrical/biomedical engineering at the Politecnico di Milano (Itay) in 1993. She is member of the board of directors of the Italian National Group of Bioengineering (GNB), of the International Society for Computerized Electrocardiology (ISCE) and of the Computing in Cardiology society (CinC). Her main research interests are processing, modelling and classification of biomedical signals and images.
Ennio Gambi is Associate Professor in Telecommunications at the Department of Information Engineering (DII) of Università Politecnica delle Marche (UNIVPM). His main research interests are currently focused on the applications of millimeter-wave radars and RGBD sensors, with particular attention to observation of subjects for the extraction of vital parameters, through the processing of extracted data based on machine learning algorithms. He has also been dealing with home automation systems for some time, and their evolution towards Ambient Assisted Living systems.
Luca Marinelli holds a PhD in business administration at Università Politecnica delle Marche. He is Researcher at the Department of Management of Università Politecnica delle Marche where teaches as lecturer “Laboratory of Digital Strategy and Data Intelligence Analysis” and “Web Marketing”. As researcher, he plays an active role in several regional innovation ecosystems in which his University is involved as actor supporting SMEs and MSMEs in managing digital transformation processes. As scholar, his work has been published in high-ranked international journals as Journal of Knowledge Management, European Journal of Innovation Management, Technovation and Journal of Business Research.
