Blockchain for Real-Time Supply Chain Tracking with Predictive AI
DOI:
https://doi.org/10.63345/Keywords:
Blockchain, Supply Chain Visibility, Predictive Analytics, Cold Chain, Smart Contracts, Anomaly Detection,, InteroperabilityAbstract
Globalized supply chains face persistent problems of poor visibility, delayed exception handling, counterfeit risk, and brittle planning under uncertainty. Real-time tracking is frequently hampered by siloed information systems and data integrity issues that erode trust among trading partners. This manuscript proposes a reference architecture that integrates permissioned blockchain ledgers with predictive AI to create a shared, tamper-evident backbone for event data (e.g., EPCIS-compliant commissioning, aggregation, shipping, receiving, and sensor telemetry) and to enable continuous forecasting of estimated time of arrival (ETA), stockouts, and cold-chain excursions. The blockchain layer establishes data lineage, non-repudiation, and programmable compliance via smart contracts, while the AI layer ingests the same high-quality, time-stamped events to learn patterns and anticipate disruptions.
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