{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T22:37:52Z","timestamp":1776379072589,"version":"3.51.2"},"reference-count":61,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,1,15]],"date-time":"2024-01-15T00:00:00Z","timestamp":1705276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sustainability"],"abstract":"<jats:p>Logistics is significantly impacted by quality\/quantity issues associated with data collection and data sharing restrictions. Nonetheless, public data from national entities and internet-of-things (IoT) solutions enable the development of integrated tools for performance analysis and real-time optimization of logistics networks. This study proposes a three-module data-driven system architecture that covers (a) logistics data collection tools, (b) logistics services performance evaluation, and (c) the transition to synchromodal systems. Module 1 integrates multisource data from national logistics platforms and embedded devices placed within intermodal containers. A multigraph representation of the problem is conceived. Environmental, economic, and operational data are generated and injected into a digital twin. Thus, key performance indicators (KPIs) are computed by simulation or direct transformation of the collected data. Module 2 uses Multi-directional Efficiency Analysis, an optimization algorithm that benchmarks multimodal transportation routes of containers using prior KPIs. Outputs are a technical performance index relevant to logistics clients and improvement measures for logistics service providers. A real case study application of the solution proposed for Module 2 is presented. Module 3 provides real-time scheduling and assignment models using CP-sat solvers, accommodating varying system dynamics and resource availability, minimizing makespan and operational costs.<\/jats:p>","DOI":"10.3390\/su16020742","type":"journal-article","created":{"date-parts":[[2024,1,15]],"date-time":"2024-01-15T08:52:03Z","timestamp":1705308723000},"page":"742","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["A Modular IoT-Based Architecture for Logistics Service Performance Assessment and Real-Time Scheduling towards a Synchromodal Transport System"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1222-9529","authenticated-orcid":false,"given":"\u00c2ngela F.","family":"Brochado","sequence":"first","affiliation":[{"name":"Department of Economics, Management, Industrial Engineering and Tourism (DEGEIT), Campus Universit\u00e1rio de Santiago, University of Aveiro, 3810-193 Aveiro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3628-6795","authenticated-orcid":false,"given":"Eug\u00e9nio M.","family":"Rocha","sequence":"additional","affiliation":[{"name":"Department of Mathematics (DMat) and Center for Research and Development in Mathematics and Applications (CIDMA), Campus Universit\u00e1rio de Santiago, University of Aveiro, 3810-193 Aveiro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4995-0539","authenticated-orcid":false,"given":"Diogo","family":"Costa","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering (DEM), Campus Universit\u00e1rio de Santiago, University of Aveiro, 3810-193 Aveiro, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,15]]},"reference":[{"key":"ref_1","unstructured":"Dutch Institute for Advanced Logistics (2020). 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