The Smart City Research Center focuses on effectively constructing credible and interpretable models for heterogeneous data to integrate various data sources related to human mobility data, addressing the issues of information scarcity and privacy protection in independent data sources. Key breakthroughs are made in:
(1)Data preprocessing techniques for sparse trajectory data and model methods for personal privacy protection;
(2)Data mining techniques for the correlation between urban elements and human mobility, and interpretability theories for data models;
(3)Robust city-scale human mobility prediction techniques for rare events;
(4)Simulation and deduction techniques for human mobility during major events, and credibility measurement theories for simulation and deduction models, laying a technical foundation for city-scale human mobility modeling and analysis.

The research team models, predicts, and simulates massive urban human mobility behaviors using advanced machine learning theories. Based on the prediction, they integrate traditional fields in emergency management, transportation, energy, and epidemiology to develop novel theoretical methods and models for smart cities:
(1)Propose emergency management model methods based on city-scale emergency human mobility modeling and prediction, providing new theoretical support for urban human mobility evacuation, traffic scheduling, and evacuation route planning during emergencies;
(2)Propose optimization theories for energy supply and demand based on heterogeneous agent-based microsimulation, solving the challenges of spatiotemporal coupling and load complexity in energy supply and demand;
(3)Propose modeling, prediction, and simulation methods for infectious disease transmission based on city-scale human mobility modeling and data-driven approaches, providing theoretical support for infectious disease prevention and control and government policy-making.

In response to the "COVID-19 pandemic" outbreak in early 2020, the team urgently developed the "Big Data on Human Mobility and AI-Driven COVID-19 Transmission Modeling, Prediction, and Simulation Platform" to serve national critical needs. Upon its release, the platform received extensive coverage from national media outlets such as the Xuexi Qiangguo Platform, People's Weekly, China Science Daily, China Reform Daily, China.com.cn, China.com, Science and Technology Daily, and China Science and Technology Network. It has provided simulation results to domestic research institutions multiple times, aiding the country and Shenzhen in formulating efficient epidemic prevention policies and contributing crucial support to related epidemic prevention efforts.

Outcome 1: A Big Data and AI-Driven Modeling and Prediction Platform for COVID-19 Transmission Based on Human Mobility

Outcome 2: A Big Data-Based Behavior Prediction and Service Management Platform System for Ride-Hailing Drivers and Passengers

Outcome 3: Research on Optimal Control of AI-Integrated Internet of Things in Transportation Based on Smart Cities