SIKELAS: A smart safety system for the elderly using AI and IoT technology

Authors

  • Michael Faldo Universitas Pertahanan Republik Indonesia, Bogor, Indonesia
  • De Sheperd Guella Winisia Zega Universitas Pertahanan Republik Indonesia, Bogor, Indonesia
  • Hizkia Purba Universitas Pertahanan Republik Indonesia, Bogor, Indonesia
  • Eliana Maharani Universitas Pertahanan Republik Indonesia, Bogor, Indonesia

DOI:

https://doi.org/10.35335/int.jo.emod.v20i2.199

Keywords:

AI, Anomaly Detection, Elderly Safety, Environmental Sensors, Voice Recognition

Abstract

The number of elderly people in Indonesia continues to rise every year, posing serious challenges regarding their well-being and safety, particularly in nursing homes where caregiver shortages and limited monitoring capabilities remain critical issues. Existing elderly monitoring systems are typically limited to single-modality approaches, such as vision-only fall detection or single-sensor environmental monitoring, lacking real-time multimodal integration. To address these gaps, the “SIKELAS” (Smart Safety System for the Elderly) system was developed as a novel integrated solution combining AI technology, anomaly detection, voice recognition, and five environmental sensors into a single unified real-time monitoring platform. The novelty of SIKELAS lies in its simultaneous integration of MediaPipe-based fall and gesture detection, Speech-to-Text voice recognition, and multi-sensor environmental monitoring coordinated through an ESP32 microcontroller and Flask back-end, delivering automated Telegram alerts with an average response time under 1 second. This research employs an experimental quantitative approach with controlled laboratory testing across five datasets. Key results: gesture detection accuracy 98.38%, fall detection accuracy 89.16%, gas detection above 2500 threshold, flame detection below 500 threshold, and ultrasonic error below 3%. SIKELAS outperforms previous single-modality systems, delivering a comprehensive, measurable solution that reduces caregiver workload through automated multimodal monitoring and real-time emergency notifications.

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Published

2026-05-30

How to Cite

Faldo, M., Zega, D. S. G. W., Purba, H., & Maharani, E. (2026). SIKELAS: A smart safety system for the elderly using AI and IoT technology. International Journal of Enterprise Modelling, 20(2), 202–211. https://doi.org/10.35335/int.jo.emod.v20i2.199

Issue

Vol. 20 No. 2 (2026): May: Enterprise Modelling

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Articles

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Copyright (c) 2026 Michael Faldo, De Sheperd Guella Winisia Zega, Hizkia Purba, Eliana Maharani

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This work is licensed under a Creative Commons Attribution 4.0 International License.