Energy Conservation Clustering through Agent Nodes and Clusters (EECANC) for Wearable Health Monitoring and Smart Building Automation in Smart Hospitals using Wireless Sensor Networks

Wireless Sensor Networks (WSNs) play a vital role in enabling real-time patient monitoring, medical device tracking, and automated management of building operations in smart hospitals. Wearable health sensors and hospital automation systems produce a constant flow of data, resulting in elevated ener...

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Published inJournal of electronics, electromedical engineering, and medical informatics Vol. 7; no. 4; pp. 1199 - 1225
Main Authors Mirkar, Sulalah Qais, Shinde, Shilpa
Format Journal Article
LanguageEnglish
Published 15.10.2025
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ISSN2656-8632
2656-8632
DOI10.35882/jeeemi.v7i4.1082

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Abstract Wireless Sensor Networks (WSNs) play a vital role in enabling real-time patient monitoring, medical device tracking, and automated management of building operations in smart hospitals. Wearable health sensors and hospital automation systems produce a constant flow of data, resulting in elevated energy usage and network congestion. This study introduces an advanced framework named Energy Conservation via Clustering by Agent Nodes and Clusters (EECANC), designed to improve energy efficiency, extend the network's longevity, and facilitate smart building automation in hospitals. The EECANC protocol amalgamates wearable medical monitoring (oxygen saturation, body temperature, heart rate, and motion tracking) with intelligent hospital building automation (HVAC regulation, lighting management, and security surveillance) through a hierarchical Wireless Sensor Network-based clustering system. By reducing routing and data redundancy, cluster heads (CHs) and agent nodes (ANs) reduce redundant transmissions and extend the life of sensor batteries. EECANC limits direct interaction with the hospital's Smart Building Management System, thereby reducing emergency response times and improving energy efficiency throughout the hospital. The efficiency of EECANC was proven by comparing its performance with other existing clustering protocols, including EECAS, ECRRS, EA-DB-CRP, and IEE-LEACH. The protocol achieved a successful packet delivery rate of 83.33% to the base station, exceeding the performance of EECAS (83.33%), ECRRS (48.45%), EA-DB-CRP (54.37%), and IEE-LEACH (59.13%). The system demonstrated better energy utilization, resulting in a longer network longevity and lower transmission costs especially during high-traffic medical events. It is clear from the first and last node death rates that EECANC is the most energy-efficient protocol, significantly better than the other methods available. The EECANC model supports hospital automation, enhances patient safety, and promotes sustainability, providing a cost-effective and energy-efficient solution for future smart healthcare facilities
AbstractList Wireless Sensor Networks (WSNs) play a vital role in enabling real-time patient monitoring, medical device tracking, and automated management of building operations in smart hospitals. Wearable health sensors and hospital automation systems produce a constant flow of data, resulting in elevated energy usage and network congestion. This study introduces an advanced framework named Energy Conservation via Clustering by Agent Nodes and Clusters (EECANC), designed to improve energy efficiency, extend the network's longevity, and facilitate smart building automation in hospitals. The EECANC protocol amalgamates wearable medical monitoring (oxygen saturation, body temperature, heart rate, and motion tracking) with intelligent hospital building automation (HVAC regulation, lighting management, and security surveillance) through a hierarchical Wireless Sensor Network-based clustering system. By reducing routing and data redundancy, cluster heads (CHs) and agent nodes (ANs) reduce redundant transmissions and extend the life of sensor batteries. EECANC limits direct interaction with the hospital's Smart Building Management System, thereby reducing emergency response times and improving energy efficiency throughout the hospital. The efficiency of EECANC was proven by comparing its performance with other existing clustering protocols, including EECAS, ECRRS, EA-DB-CRP, and IEE-LEACH. The protocol achieved a successful packet delivery rate of 83.33% to the base station, exceeding the performance of EECAS (83.33%), ECRRS (48.45%), EA-DB-CRP (54.37%), and IEE-LEACH (59.13%). The system demonstrated better energy utilization, resulting in a longer network longevity and lower transmission costs especially during high-traffic medical events. It is clear from the first and last node death rates that EECANC is the most energy-efficient protocol, significantly better than the other methods available. The EECANC model supports hospital automation, enhances patient safety, and promotes sustainability, providing a cost-effective and energy-efficient solution for future smart healthcare facilities
Author Shinde, Shilpa
Mirkar, Sulalah Qais
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Title Energy Conservation Clustering through Agent Nodes and Clusters (EECANC) for Wearable Health Monitoring and Smart Building Automation in Smart Hospitals using Wireless Sensor Networks
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