BIONIB: Blockchain-Based IoT Using Novelty Index in Bridge Health Monitoring

Bridge health monitoring is critical for infrastructure safety, especially with the growing deployment of IoT sensors. This work addresses the challenge of securely storing large volumes of sensor data and extracting actionable insights for timely damage detection. We propose BIONIB, a novel framework that combines an unsupervised machine learning approach called the Novelty Index (NI) with a scalable blockchain platform (EOSIO) for secure, real-time monitoring of bridges. BIONIB leverages EOSIO’s smart contracts for efficient, programmable, and secure data management across distributed sensor nodes. Experiments on real-world bridge sensor data under varying loads, climatic conditions, and health states demonstrate BIONIB’s practical effectiveness. Key findings include CPU utilization below 40% across scenarios, a twofold increase in storage efficiency, and acceptable latency degradation, which is not critical in this domain. Our comparative analysis suggests that BIONIB fills a unique niche by coupling NI-based detection with a decentralized architecture, offering real-time alerts and transparent, verifiable records across sensor nodes.

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Publication Details

Journal
Applied Sciences
Published
2025-09-29
DOI
https://doi.org/10.3390/app151910542
Citations
1
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
Field-Weighted Citation Impact
2.48

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article

BIONIB: Blockchain-Based IoT Using Novelty Index in Bridge Health Monitoring

Divija Swetha Gadiraju, Deepak Khazanchi, Saeed Eftekhar Azam, Ryan McMaster
1 citations
Applied Sciences
Anomaly Detection Techniques and Applications
2.48
article

BIONIB: Blockchain-Based IoT Using Novelty Index in Bridge Health Monitoring

Divija Swetha Gadiraju, Deepak Khazanchi, Saeed Eftekhar Azam, Ryan McMaster
article en
1 citations

Abstract

Bridge health monitoring is critical for infrastructure safety, especially with the growing deployment of IoT sensors. This work addresses the challenge of securely storing large volumes of sensor data and extracting actionable insights for timely damage detection. We propose BIONIB, a novel framework that combines an unsupervised machine learning approach called the Novelty Index (NI) with a scalable blockchain platform (EOSIO) for secure, real-time monitoring of bridges. BIONIB leverages EOSIO’s smart contracts for efficient, programmable, and secure data management across distributed sensor nodes. Experiments on real-world bridge sensor data under varying loads, climatic conditions, and health states demonstrate BIONIB’s practical effectiveness. Key findings include CPU utilization below 40% across scenarios, a twofold increase in storage efficiency, and acceptable latency degradation, which is not critical in this domain. Our comparative analysis suggests that BIONIB fills a unique niche by coupling NI-based detection with a decentralized architecture, offering real-time alerts and transparent, verifiable records across sensor nodes.

Applied SciencesVol. 15(19)
University of Nebraska at Omaha (US), University of New Hampshire (US)
U.S. Army Corps of Engineers, Engineer Research and Development Center
Openalex Percentile: Top 8%
Anomaly Detection Techniques and Applications
2.48
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