An Integrated Data-Driven IoT Framework for Real-Time Downstream Petroleum Logistics

An integrated, real-time view of downstream petroleum logistics is essential for supporting Saudi Arabia’s Vision 2030 and National Transport and Logistics Strategy objectives, yet current practice largely relies on fragmented systems, manual planning and cost-only optimisation of hazardous fuel transport. This paper proposes the Downstream Petroleum Logistics Management (DPLM) system, an integrated IoT-based framework for real-time, data-driven distribution of petroleum products from suppliers to petrol stations, airports and industrial customers. DPLM combines three core components: a Tank-data Tracking and Transmission system (TTT) that continuously captures tank levels and product temperatures over secure wireless networks; a Data Management System (DMS) that consolidates inventory, customer, routing and fleet information; and a Decision Support System (DSS) that generates delivery plans using a bi-objective optimisation model. The DSS explicitly balances transportation cost and hazardous materials risk, enabling managers to explore a Pareto frontier of cost–risk trade-offs and to embed varying levels of risk aversion and operational constraints in routing and scheduling decisions. Conceptually, the framework is designed to reduce manual planning effort, improve utilisation of trucks and storage capacity, minimise emergency deliveries and support green logistics objectives through risk-aware, emissions-conscious routing choices. The paper formalises the architectural design, data integration structure and optimisation logic of DPLM, providing a systematic foundation for future implementation, mathematical modelling and empirical validation in Saudi downstream petroleum logistics networks.