LOCALIZATION OF OLDER PEOPLE IN AN INDOOR SCENARIO: A MEASUREMENT SYSTEM BASED ON PIR SENSORS INSTALLED ON A SOCIAL ROBOT

The indoor localization of older people (> 65 years old) can address the challenges for the creation of personalized Ambient and Assisted Living (AAL) experiences for a varied aging population in the smart living spaces, such as Smart Homes [1]. Methods based on sensors network, such as RGB camera and microphones, were widely used for older people localization in indoor environment [2]. However, in the last years the increased privacy concerns with these sensors have led researchers to move towards new technologies. Thus, systems based on wearable devices like smartwatches and mobile phones have gradually been involved in localizing older people in indoor environments [3]. Anyway, pitfalls related to reliability, validity, and accuracy of data need to be addressed for wider acceptance and adoption of wearables [3]. Passive infrared (PIR) motion sensors are typical house sensors for the detection of people. Frequently, these sensors are mounted on the ceiling of a room allowing a room-based localization system [4]. The objective of this work is to introduce in the indoor environment a non-invasive and inexpensive system to localize people in every room of an apartment [5]. The system is composed of PIR motion sensors mounted on the head of a mobile social robot (Misty II). To predict the direction information related to people’s movements a measurement procedure is developed, in which a Decision Tree (DT) classifier algorithm is tested.