The Intelligent Operation Control and Service System refers to a full-process smart system embodying "perception - analysis - decision-making - execution - service" that combines next-generation communication technologies like the Internet of Things (IoT), big data, artificial intelligence (AI), and cloud computing. It is a product of the core needs "operation scheduling" and "user service" that are mainly met in the fields of transportation, logistics, energy, and manufacturing, etc. Its primary purpose is to use data-driven means to break down the barrier of the flow of information between "operation" and "service". While the system efficiently performs "efficient scheduling, safe management and control, and cost optimization", it also makes available "personalized, precise, and proactive" services. In contrast to traditional single systems that only focus on "scheduling functions", it serves as an intelligent center for the deep collaboration between "operation management and control" and "user service".
The "intelligence" of the Intelligent Operation Control and Service System is supported by the collaborative technologies on the ground. The system's layout includes five layers: "Perception Layer, Network Layer, Data Layer, Algorithm Layer, and Application Layer" thus, it forms a full-process technological closed loop for "data from collection to application".
Perception Layer: The "data entry point" - gathers fully dimensional data on operations and services.
Network Layer: The "data channel" - guarantees timely and trustworthy data transmission.
Data Layer: The "data warehouse" - is the place where data integration and data management take place.
Algorithm Layer: The "intelligent brain" - the primary function of the layer is to upgrade the decision-making and services levels to the next one of intelligence.
Application Layer: The "value realization point" - provides different fields with the scenario-based applications.
The Intelligent Operation Control and Service System is going further in the direction of "more intelligent, more collaborative, and more proactive" due to the changes of technologies and the upgrading of demands. The principal trends are:
1. Cross-Domain Collaboration: Breaking "Information Silos" and Enabling "Multi-Industry Linkage"
The system of tomorrow will not be limited to an area only, but it will have the capability of "cross-domain data interconnection and capacity collaboration". Some examples are:
"Bus - Subway - High-Speed Rail" Collaboration: As a result of the delay of the high-speed rail, the system automatically communicates the delay information to the subway and bus operation control systems, it changes the last train time of the subway and it adds bus feeder services to make the passenger transfers easy again.
"Logistics - E-Commerce - Supply Chain" Collaboration: The "peak promotion order data" from e-commerce platforms is immediately transferred to the logistics operation control system for transportation capacity reservation in advance; the "delivery delay data" from the logistics system is sent to the e-commerce service system that, in turn, sends "delay reminders" to users informing them of the situation and also providing them with compensation solutions (like coupons) automatically.
2. In-Depth Integration of AI Large Models: From "Single Algorithm" to "General Intelligence"
Currently most of system algorithms are "dedicated algorithms for specific scenarios" (e.g. a single route planning algorithm). Later on, they will merge "AI large models" (like transportation large models and logistics large models) to perform "general intelligent decision-making":
Natural Language Interaction: By means of "voice conversations" (e.g., "Query the top 3 bus routes with the highest passenger flow this week"), operation managers give the system commands, and the system through the large model understands the idea and gives the results.
Complex Scenario Decision-Making: When faced with complex scenarios like "heavy rain + holidays + route failures" the large model can analyze different data (meteorology, passenger flow, transportation capacity) and come up with a "globally optimal solution" (e.g., deciding to adjust the transportation capacity of buses, subways, and shared bikes simultaneously).
3. Proactive Service Upgrade: From "User Query" to "Demand Prediction"
The systems of tomorrow will be making a shift from "users actively querying services" to "proactively predicting needs and providing services":
Travel Demand Prediction: The evaluation of users' past travel records and calendar schedules (e.g., a "going home" label at 18:00 every Friday) results in the system sending a "bus reservation reminder for going home on Friday" even before the user and thus it is the one who books the seats.
Proactive Risk Avoidance: The logistics system is studying "historical delivery delay data + real-time road conditions". When it concludes that a package will be delayed, it sends a "delay warning" to the user and provides some solutions like "changing the delivery address" and "priority delivery".
4. Green and Low-Carbon Orientation: In-Depth Integration of Operation Control Optimization and Low-Carbon Goals
To be in line with the "dual carbon" goals, the system plans to insert a "low-carbon optimization module" that would reduce energy consumption by operation control strategies:
Transportation Field: The bus departure frequency should be re-arranged in such a way that empty-mileage can be brought down; the idea of "energy-saving routes" (for example, by not going uphill) should be used to lessen the vehicle's energy consumption.
Logistics Field: The loading rate for trucks should be optimized (e.g., "by combining several orders for delivery") so as to decrease the transportation times; the introduction of new energy vehicles should be done first, the energy consumption of vehicles should be tracked in real-time, and "energy-saving driving suggestions" (e.g., "Your current speed is too high; I recommend that you reduce it to 60km/h if you want to save energy") should be given to the driver.
FAQ – Frequently Asked Questions
1. When and where will the Expo be held?
The expo will be at the Xiamen International Conference and Exhibition Center (XICEC), Hall C, Xiamen, China from May 13 to 15, 2026.
2. What is the scale of the exhibition?
The event is planned to take place on a 40,000 m² area featuring more than 350 companies. In addition, they predicted the presence of more than 30,000 professional visitors from all over the world.
3. What else is there besides the exhibition?
Besides the exhibition, over 80 professional forums and events will be held. Some of the topics addressed will be smart mobility, communication in transportation, safety, and sustainable development, only to mention a few.
4. How many countries and regions are participating?
The world conference on intelligent transportation innovation gathers the members from more than 80 countries and regions.
5. Can I cooperate with other participants?
Yes, the Expo is a platform for business collaboration, technology exchange, and investment opportunities with more than 1,000 global partners.
6. Who can I talk to if I want more details?
If you are in need of more information, kindly get in touch with the Organizing Committee through the "Contact Us" section on the official website.
