Open Access

ARTICLE

MediServe: An IoT-Enhanced Deep Learning Framework for Personalized Medication Management for Elderly Care

Smita Kapse¹, Ganesh Yenurkar^1,*, Vincent Omollo Nyangaresi^2,3,*, Gunjan Balpande¹, Shravani Kale¹, Manthan Jadhav¹, Sahil Lawankar¹, Vikrant Jaunjale¹

1 Department of Computer Technology, Yeshwantrao Chavan College of Engineering, Wanadongari, Nagpur, 441110, Maharashtra, India
2 Computer Science & Engineering, Jaramogi Oginga Odinga University of Science & Technology, Bondo, 40601, Kenya
3 Department of Applied Electronics, Saveetha School of Engineering, SIMATS, Chennai, 602105, Tamilnadu, India

* Corresponding Authors: Ganesh Yenurkar. Email: ; Vincent Omollo Nyangaresi. Email:

Computers, Materials & Continua 2025, 83(1), 935-976. https://doi.org/10.32604/cmc.2025.061981

Received 07 December 2024; Accepted 17 February 2025; Issue published 26 March 2025

Abstract

In today’s fast-paced world, many elderly individuals struggle to adhere to their medication schedules, especially those with memory-related conditions like Alzheimer’s disease, leading to serious health risks, hospitalizations, and increased healthcare costs. Traditional reminder systems often fail due to a lack of personalization and real-time intervention. To address this critical challenge, we introduce MediServe, an advanced IoT-enabled medication management system that seamlessly integrates deep learning techniques to provide a personalized, secure, and adaptive solution. MediServe features a smart medication box equipped with biometric authentication, such as fingerprint recognition, ensuring authorized access to prescribed medication while preventing misuse. A user-friendly mobile application complements the system, offering real-time notifications, adherence tracking, and emergency alerts for caregivers and healthcare providers. The system employs predictive deep learning models, achieving an impressive classification accuracy of 98%, to analyze user behavior, detect anomalies in medication adherence, and optimize scheduling based on an individual’s habits and health conditions. Furthermore, MediServe enhances accessibility by employing natural language processing (NLP) models for voice-activated interactions and text-to-speech capabilities, making it especially beneficial for visually impaired users and those with cognitive impairments. Cloud-based data analytics and wireless connectivity facilitate remote monitoring, ensuring that caregivers receive instant alerts in case of missed doses or medication mismanagement. Additionally, machine learning-based clustering and anomaly detection refine medication reminders by adapting to users’ changing health patterns. By combining IoT, deep learning, and advanced security protocols, MediServe delivers a comprehensive, intelligent, and inclusive solution for medication adherence. This innovative approach not only improves the quality of life for elderly individuals but also reduces the burden on caregivers and healthcare systems, ultimately fostering independent and efficient health management.

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