  Bridge health monitoring becomes crucial with the deployment of IoT sensors.
The challenge lies in securely storing vast amounts of data and extracting
useful information to promptly identify unhealthy bridge conditions. To address
this challenge, we propose BIONIB, wherein real-time IoT data is stored on the
blockchain for monitoring bridges. One of the emerging blockchains, EOSIO is
used because of its exceptional scaling capabilities for monitoring the health
of bridges. The approach involves collecting data from IoT sensors and using an
unsupervised machine learning-based technique called the Novelty Index (NI) to
observe meaningful patterns in the data. Smart contracts of EOSIO are used in
implementation because of their efficiency, security, and programmability,
making them well-suited for handling complex transactions and automating
processes within decentralized applications. BIONIB provides secure storage
benefits of blockchain, as well as useful predictions based on the NI.
Performance analysis uses real-time data collected from IoT sensors at the
bridge in healthy and unhealthy states. The data is collected with extensive
experimentation with different loads, climatic conditions, and the health of
the bridge. The performance of BIONIB under varying numbers of sensors and
various numbers of participating blockchain nodes is observed. We observe a
tradeoff between throughput, latency, and computational resources. Storage
efficiency can be increased by manifolds with a slight increase in latency
caused by NI calculation. As latency is not a significant concern in bridge
health applications, the results demonstrate that BIONIB has high throughput,
parallel processing, and high security while efficiently scaled.
