# Extracting Daily Routines from Raw RSSI Data

## TL;DR

This paper presents a method to extract daily routines of older adults in care homes using signal strength data from smartwatches.

## Contribution

A novel methodology for analyzing raw RSSI data to estimate daily routines and activity probabilities in care home residents.

## Key findings

- Fingerprint-based localization was used to track minute-by-minute locations of volunteers.
- Daily activities were estimated for each volunteer over five months of data collection.
- Probabilities of weekday activities were calculated based on observed routines.

## Abstract

Detecting behavioral routines is an important research area with many implications in various practical applications. One such application involves studying the behavior of older adults residing in care homes. This paper proposes a comprehensive methodology for extracting and analyzing the daily routines of older adults in care homes. The methodology utilizes raw data comprising signal strength measurements obtained from smartwatches worn by six volunteers over five months. To establish the basis for estimating daily activities, fingerprint-based localization techniques are employed to track the minute-by-minute location of each volunteer. Subsequently, the activity performed by each volunteer is estimated for each day. Finally, the study estimates the probability of a user undertaking each one of the studied activities on a given weekday.