Core Viewpoint - The article highlights the significant advancements in energy transportation through the development of the Energy Smart Transportation Integrated Optimization Solution (ESTIOS) by Liu Yang, showcasing its role in enhancing efficiency, safety, and digital transformation in the industry [1][2][3]. Group 1: Development and Implementation of ESTIOS - Liu Yang began his journey in energy smart transportation in 2010, focusing on addressing long-standing scheduling challenges through technological innovation [1][2]. - The ESTIOS solution was initially piloted in 2015, demonstrating a fivefold increase in response speed and over 40% improvement in overall operational efficiency [2]. - The solution has evolved to cover key aspects such as terminal perception, intelligent scheduling, and remote operation, becoming a benchmark system for integrated smart operations in the industry [3]. Group 2: Impact and Recognition - ESTIOS has been deployed at multiple energy bases and has received significant recognition, including a prestigious technology advancement award, marking it as a model for digital transformation in energy transportation [3][4]. - In a pilot at a major oil and gas transportation base, ESTIOS supported over 700 orders per hour, reducing scheduling response time to one-fifth and cutting energy consumption by nearly 20% [4]. Group 3: Technological Innovations and Features - The system incorporates advanced features such as a self-learning correction mechanism, which allows it to automatically adjust scheduling parameters based on feedback data, enhancing accuracy and efficiency [4][5]. - Liu Yang has developed four key software components under ESTIOS, focusing on safety, digital analysis, and intelligent management across the energy transportation supply chain [5]. Group 4: Future Directions and Industry Alignment - The ongoing development of ESTIOS aligns with national strategies to integrate emerging technologies like AI and blockchain into energy transportation, aiming to reshape industry operational logic [7][8]. - Future plans include expanding functionalities to cover hydrogen energy scheduling and AI-driven optimization, further enhancing the energy transportation ecosystem [7][8].