MFO-AIChain: An Intelligent Optimization and Blockchain-Backed Architecture for Resilient and Real-Time Healthcare IoT Communication

With proliferation of IoT devices in healthcare systems, things like real-time patient data management, quick diagnosis, and constant monitoring are becoming a reality. Yet, there are substantial obstacles to energy efficiency, secure data transfer, latency, and durability against hostile assaults that these systems must overcome. For efficient and safe data transmission in healthcare-oriented IoT networks, this article suggests a new framework called moth flame optimized AI-driven blockchain framework (MFO-AIChain). For efficient routing and clustering, suggested model incorporates moth flame optimization (MFO). For distributed data integrity and safe authentication, it uses AI-based trust computation. model guarantees equal distribution of loads and decreased communication overhead by choosing energy-efficient cluster heads and routes on fly depending on remaining energy, signal strength, and node density. Additionally, symmetric digital certificates are used for mutual authentication, and blockchain technology in conjunction with XOR encryption offers strong data protection in a lightweight package. When compared to other models, including SKID and QoS-Trust, MFO-AIChain routinely performs better in important metrics like packet delivery ratio, latency, energy consumption, runtime overhead, and link stability. These evaluations were carried out using NS-3 simulation with different node densities and data rates. When compared to baselines, suggested solution improves delivery ratio by more than 14%, reduces energy usage by 30%, and reduces influence of malicious packets by up to 40%. Critical services like remote monitoring and real-time diagnostics in restricted IoT contexts rely on MFO-AIChain's dependable, secure, and efficient platform for healthcare data transmission.

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Publication Details

Published
2025-07-25
DOI
https://doi.org/10.1109/isac364032.2025.11156495
Citations
1
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
1.49
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article

MFO-AIChain: An Intelligent Optimization and Blockchain-Backed Architecture for Resilient and Real-Time Healthcare IoT Communication

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1 citations
IoT and Edge/Fog Computing
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article

MFO-AIChain: An Intelligent Optimization and Blockchain-Backed Architecture for Resilient and Real-Time Healthcare IoT Communication

Anorgul Ashirova, Dinesh Gottipalli, Ajinkya Potdar, Venkatesh Kodela, Sahithi Donkina, Azizjon Begaliev
article en
1 citations

Abstract

With proliferation of IoT devices in healthcare systems, things like real-time patient data management, quick diagnosis, and constant monitoring are becoming a reality. Yet, there are substantial obstacles to energy efficiency, secure data transfer, latency, and durability against hostile assaults that these systems must overcome. For efficient and safe data transmission in healthcare-oriented IoT networks, this article suggests a new framework called moth flame optimized AI-driven blockchain framework (MFO-AIChain). For efficient routing and clustering, suggested model incorporates moth flame optimization (MFO). For distributed data integrity and safe authentication, it uses AI-based trust computation. model guarantees equal distribution of loads and decreased communication overhead by choosing energy-efficient cluster heads and routes on fly depending on remaining energy, signal strength, and node density. Additionally, symmetric digital certificates are used for mutual authentication, and blockchain technology in conjunction with XOR encryption offers strong data protection in a lightweight package. When compared to other models, including SKID and QoS-Trust, MFO-AIChain routinely performs better in important metrics like packet delivery ratio, latency, energy consumption, runtime overhead, and link stability. These evaluations were carried out using NS-3 simulation with different node densities and data rates. When compared to baselines, suggested solution improves delivery ratio by more than 14%, reduces energy usage by 30%, and reduces influence of malicious packets by up to 40%. Critical services like remote monitoring and real-time diagnostics in restricted IoT contexts rely on MFO-AIChain's dependable, secure, and efficient platform for healthcare data transmission.

Google (United States) (US), Amazon (United States) (US), George Mason University (US), Zimmer Biomet (United States) (US), Termez State University (UZ)
Openalex Percentile: Top 13%
IoT and Edge/Fog Computing
1.49
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