Sensing and AI techniques for aging well
As life expectancy increases, it is necessary to ensure that elderly people live with dignity in their homes by promoting their well-being through the creation of comfortable living environments and ensuring personalized assistance. The goal of Age-SenseAI is to develop an innovative sensor ecosystem in the home environment, aimed at the elderly living in multi-resident contexts and their caregivers, to measure the comfort and activities of the inhabitants. Through these measurements, it is possible to identify changes in people’s behaviors, Activities of Daily Living (ADL), and risk factors, such as falls or diseases that arise due to environmental conditions, thereby improving the well-being and health status of the elderly. In particular, Age-SenseAI aims to go beyond the state of the art by creating an ecosystem suitable for living environments where multiple people live together. To date, this scenario is little considered due to the cost of sensors and the complexity of the measurement problem. Age-SenseAI aims to overcome this obstacle by integrating a network of sensors in the environment and on mobile robotic systems that allows monitoring the activities and comfort of multiple inhabitants through data analysis with Data Fusion (DF) and Artificial Intelligence (AI) techniques. DF techniques will be applied to obtain less uncertain, more accurate, and complete data sets, which will then be processed through AI techniques to discriminate the specific activities and comfort of multiple users. Additionally, AI will serve to optimize the sensor ecosystem to reduce hardware and installation costs. For the identification and development of the Age-SenseAI sensor ecosystem, co-design sessions will be held with the partners of the Age-It consortium, specifically of Spoke 9, and with the end users (elderly and caregivers) to define the scenario most suited to the design needs. The developed ecosystem will then be tested in the lead partner’s Living Lab with real users.
PMF will design the Cloud platform based on AWS architecture, where data will be represented and AI algorithms integrated. PMF will coordinate WP3 for the capabilities in data representation and visualization, and for the expertise in Cloud platform design. WP5 activities will be coordinated by PMF and UNIVPM. PMF, together with the DIMA group of UNIVPM, will manage market evaluation and impact monitoring.
