2022年1月28日星期五

HKIE Technical Seminar: AI/ML and Big Data use cases in Smart City

Hong Kong Institution of Engineers (HKIE) IT Division supported Innovation Lab of PCCW to organize a technical seminar on “AI/ML and Big Data use cases in Smart City” on 28 January 2022.  Machine Learning (ML) is the core subarea of AI and it makes computer get into a self-learning mode without explicit programming.  When fed new data, these computers learn, grow, change and develop by themselves. This seminar (online) introduced machine learning and big data, use cases included smart building, shopping and mobility, as well as 5G empowerment. 


Dr. Chung Ng (SVP at Group CTO Office of PCCW-HKT) was guest speaker.  Firstly, he said “Data is the new oil” that the growth of data, devices and computing power drive the development of Data Analytics, Big Data, AI & ML.


Then he briefed the Big Data Analytics that is the process of collecting and analyzing large data sets to take more informed business decisions.  The myths of big data is explained.


And then Dr. Ng mentioned the different between traditional programming and machine learning.


A typical end-to-end journey of a Data Scientist was briefed from data merge to cleanup & transformation, and to be model building with feedback, and final model deployment at the end.


After that Dr. Ng introduced smart city evolving intelligence via AI/ML and there were four steps from IoT/Devices to Connectivity to Data Analytics/Reporting and then to AI/ML model. Some cases are discussed including smart parking project, smart green minibus project and City Brain of Hangzhou, etc.


Finally, he briefed four key advantages of 5G and explained how 5G change the game of IoT and Smart City. For instance, 5G Drone for real-time site modelling, smart hospital for remoting consultation.  


Lastly, Dr. Ng quoted Alan Turing (1950) question that “Can machine think?” and explained ML model had been growing in terms complexity and intelligence.  He concluded that unsupervised learning could be applied for self-organized solution to optimize between business objectives. 



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