On September 19, I chaired the keynote speech from Distinguished Prof. Shuo-Yan Chou (from National Taiwan University of Science and Technology, Director of Centre for Internet of Things Innovation) on IEEE ICELTICs’ 2018. The topic of this speech is indeed interesting: “Development and Opportunities in Digitally Fused World”. In this article, I’d like to summarize the speech with a simple discussion along with visual explanation through the successive images provided on his slides. Nowadays, the revolution of the industry is establishing the 4th generation. In the early stage, the industry was focusing on mechanical and mass production. This is so-called the 1st and 2nd generation which didn’t involve any artificial intelligence inside the machine. It then gradually enhanced, when the 3rd generation started to introduce the automation which greatly expedites the production stage.
Currently, with the advancement of the Internet (IoT) and artificial intelligence (AI) the industry is initiating the smart factory which allows the machine to interact with one each other. An intuitive illustration is shown below, where the machine can communicate with each other in order to check the availability, current working load, and upcoming arrangement. This leads to flexibility and agility of production, and at the same time cope with the complexity.
Apart from IoT boom and connected device, one of the important keys of technology is an evolution of machine learning. As we can see in the Fig. 3 that this research has been conducting for many years. In the last three years, the “deep learning” is changing everything by revisiting the idea to make a more advanced layer on the artificial network. This becomes much more influential while incorporating a “big data” to let the machine learn what it gets and output much more accurate results. To date, implementation of AI in the smart city has shown a great impact, one of them is smart transportation. A camera/imaging sensors are commonly installed to automatically detect and identify potential vehicle/cars through automated object detection methods. For example, on Beijing’s ring roads — concentric circles around the city — 157 high-definition cameras automatically count vehicles and provide traffic flow statistics. When events such as accidents, congestion, and surface water accumulation occur, the system automatically videotapes the event and activates an alarm as needed [Zhu, 2016].
As a result, the fusion of IoT, AI, and blockchain create abundant opportunities for a machine to be more intelligent, distributed and trusted.
Hope this short article is useful for the readers :).
