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Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

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Using Interoperability between Mobile Robot and KNX Technology for Occupancy Monitoring in Smart Home Care.

Jan Vanus¹, Radim Hercik¹, Petr Bilik¹

¹Department of Cybernetics and Biomedical Engineering, VŠB-TU Ostrava, 70800 Ostrava, Czech Republic.

Sensors (Basel, Switzerland)

|November 14, 2023

Summary

Smart Home Care (SHC) uses mobile robots and KNX technology to monitor elderly and disabled individuals living alone. This system accurately detects occupancy without cameras, enhancing safety and independent living.

Keywords:

KNX technology Smart Home Care localization mobile robot occupancy presence

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Area of Science:

Smart Home Care (SHC) automation
Human-Robot Interaction
Internet of Things (IoT) in healthcare

Background:

Independent living for elderly and disabled individuals presents daily challenges.
Smart Home Care (SHC) aims to support independent living through automated assistance.
Mobile robots can enhance control of home functions and assist with daily activities.

Purpose of the Study:

To propose and implement interoperability between mobile robots and KNX technology within SHC.
To determine human presence and occupancy in SHC environments without using cameras.
To indirectly monitor occupancy by analyzing environmental variables and door/window status.

Main Methods:

Integration of mobile robots with KNX technology for SHC automation.
Utilizing environmental sensors (temperature, humidity, light, CO2) and magnetic contacts.
Employing nonlinear autoregressive Neural Networks (NN) with exogenous inputs to predict CO2 concentration.

Main Results:

Achieved accurate prediction of CO2 concentration waveforms with over 98% accuracy.
Successfully transmitted environmental data from KNX to mobile robots.
Demonstrated a novel method for indirect occupancy detection without cameras.

Conclusions:

The proposed SHC system effectively integrates mobile robots and KNX technology for occupancy monitoring.
The NN-based CO2 prediction method enhances the accuracy of occupancy detection.
This approach offers a privacy-preserving solution for supporting independent living.