Leveraging blockchain integrity mechanisms and IoT sensors to boost internal process efficiency in logistics management - Čale, D.; Ferreira, J.; Ana Maria Madureira; Coutinho, C. (2025 IEEE International Conference on Distributed Ledger Technologies (ICDLT), Proceedings, 2025)
Fleet logistics management requires reliable monitoring of temperature-sensitive goods and asset utilization to meet regulatory requirements and operational efficiency targets. This paper presents an integrated framework combining blockchain technology and IoT sensors to enhance internal process efficiency and data integrity in logistics operations. The research develops and deploys a permissioned blockchain system within a Portuguese logistics company, enabling empirical evaluation of core performance metrics including end-to-end latency, transaction throughput, and audit traceability under operational conditions. A pilot study involving 12 sensors distributed across transport operations demonstrates measurable improvements in audit preparation efficiency. Analysis indicates that low-latency event registration (meaning 5 seconds) supports operational monitoring requirements, whilst automated evidence generation with cryptographic proofs reduces manual verification overhead in internal and external audit processes. The study establishes performance benchmarks and cost-benefit analysis comparing blockchain adoption against centralized logging solutions with digital signatures. The architecture enhances decision-making transparency by providing logistics managers with cryptographically verifiable operational data, whilst governance insights support organizations implementing blockchain-based Ana Maria Madureira ISRC Instituto Superior de Engenharia do Porto, ISEP/IPP Porto, Portugal amd@isep.ipp.pt ORCID 0000-0002-0264-4710 when managing high-value or perishable goods demanding verifiable handling conditions [1]. The value of these data streams is frequently undermined by concerns about sensor data reliability, especially when data is stored in centralized systems. Lack of trust in data authenticity can lead to redundant manual inspections and parallel maintenance of independent records, negating expected efficiency gains from digitization. Furthermore, traditional logistics management systems often struggle with data silos, manual errors, transparency issues, and information delays, all of which hinder effective real-time decisionmaking and reduce stakeholder trust [2]. integrity environments.