All-weather Highway
Three major application fields:
1. Fog Cluster Research: The main point is to apply video structuring, Internet of Things (IoT), and big data technologies for real-time detection, early warning, and control of fog clusters in fog cluster-prone road sections. In addition, the around-the-clock data collection will be used to establish analysis models and, through data accumulation and deep learning, to strive for high-probability prediction of fog clusters within several years.
2. Traffic Situation Model Analysis and Judgment: The key idea is to use big data and AI technologies for thorough perception and integration of various data such as traffic flow, vehicle categories, and congestion status. On top of that, the system is able to analyze and derive traffic situation indices for nodes and road sections, realize comprehensive control of traffic conditions, and hierarchical proactive management and control.
3. Unmanned Aerial Vehicle (UAV) Integrated Patrol and Control: It mainly revolves around UAVs as the prime equipment that is capable of supporting the functions like real-time audio and video transmission and fixed-route patrol. In this way, it makes possible 24-hour patrolling, illegal act capture, and emergency response;
Traffic flow detection technology
1. Mainstream Technologies: These are various technologies, including inductive loops and microwave, among which "video detection" is the most commonly used, that is characterized by the advantages of low cost, easy installation and maintenance, and the ability to obtain intuitive and rich information. When used together with the relevant technologies, it can recognize vehicle types, traffic signs, etc.; "millimeter-wave radar detection" has a strong anti-interference capability and is very adaptable to the climate, thus it can operate in all-weather conditions.
2. Technology Integration: Given the limitations of a single sensor (the video is affected by the environment and lacks depth information, while the radar gives insufficient information), the main point is to combine radar and video to get more reliable information, thus improving system robustness and data accuracy.
Multi-element state perception equipment
Key Technologies:
1. Full-Stack Technology: The Internet of Things (IoT), big data, and industry informatization are integrated to form a full-scenario solution covering "ICT sensing equipment - data infrastructure - hydrogen fuel cell bus management and control". Thereby, it realizes the "terminal - pipeline - cloud" architectural innovation.
2. Middle-End Technology: It is designed to have one data asset management platform for hydrogen fuel cell buses that are unified, standardized, and updatable. Through microservices, functional modularization is performed to form data services that have a high level of cohesion, thus the mutual empowerment between business operations and data is facilitated.
3. AI + IoT: A trustworthy IoT transmission mechanism is set up to achieve the second-level transmission of vehicle CAN data. Along with this, deep learning is used to handle vehicle operation and fault data that supports fault prediction and the identification of maintenance points.
4. Distributed Technology: The use of technologies like Spark and Flink is aimed at full-process handling of CAN data from hydrogen fuel cell vehicles and real-time data from hydrogen refueling stations. It also realizes quick multi-dimensional data integration with second-level data response.
5. 3D Data Visualization Technology: It makes use of virtual simulation to show the data in several dimensions for the purpose of comprehensive monitoring of the operational safety of hydrogen fuel cell vehicles and hydrogen refueling stations and thus, providing management decision support.
Overall Approach
The main idea is to use vehicle detection technology for cleaning traffic flow data by relying on the millimeter-wave radars and video detectors. Then, the models are updated, and static/dynamic/path information is managed;
Deep learning is used in conjunction with the video equipment to analyze the video data, get the historical traffic flow data, as well as to mine the information such as traffic flow distribution and congestion levels. Simultaneously parking management can be supported with parking lot data;
The installation of video sensing equipment on the main and branch road sections of the area will help in the analysis of vehicle trajectories, calculation of inbound and outbound traffic flow, and consequently, derivation of the total number of vehicles in the area.
FAQ – Frequently Asked Questions
1. When and where is the Expo?
The Expo will be at the XICEC Hall C from May 13–15, 2026. The event is planned to be held in Xiamen, China.
2. How big is the exhibition?
The event covered an area of more than 40,000 m², with the number of 350+ companies and a total of 30,000 professional visitors from all over the world.
3. What are the main topics of the exhibitions and conferences?
There will be more than 80 professional forums and events held to discuss such topics as smart mobility, transport communication, safety, and sustainable development.
4. How many countries and regions are involved?
Delegates from over 80 countries and regions will be at the event, which, therefore, will be a global meeting of new tech for the intelligent transport sector.
5. Are there collaboration opportunities?
Yes, of course. Collaborations for business, technology exchange, and investment are plentiful at the Expo with more than 1,000 global partners.
6. Who can give me the information?
If you want more information, please reach out to the Organizing Committee through the Contact Us page on the official website.
