School of Engineering Department of Computer Science and Engineering 93 Video Analytics and IoT People/Asset Sensing for Smart City Applications Supervisor: CHAN, Gary Shueng Han / CSE Student: TAM, Shing Hang Boris / COGBM Course: UROP1100, Spring Researched by Professor Kent Chen, Professor Gary Chan, and their team, the LPR, together with LoRa and EdgeAI technology can detect license plates, find empty lots, and detect vehicle types. This technological breakthrough is readily applicable in the Hong Kong’s context. This paper researched the unique carpark environment and niches in Hong Kong, and suggested three potential adoptions of the technology, namely restricted areas, transportation hubs, and government parking meters. The value propositions, designs and implementations, and the business plans were also discussed in the paper. Video Analytics and IoT People/Asset Sensing for Smart City Applications Supervisor: CHAN, Gary Shueng Han / CSE Student: TSANG, Hong Ting / COMP Course: UROP2100, Fall The objective of this project is to create a standard for Pervasive Positioning, allowing applications to locate an object anywhere, on a country scale seamlessly. In current technology for location-based applications, both indoor and outdoor positioning work well independently but there is no one standard that allows applications to perform Pervasive Positioning using current technology. Utilizing the approach of decoupling and then recoupling, the lookup server first gathers all data and server addresses of site owners, depending on the privacy control and requested data format, set by site owners and applications, returning the appropriate data or address for further computation. Under this approach, we can achieve Pervasive Positioning utilizing current technology by contacting the right party using the right formats. In this semester, application that is utilizing this standard is attempted to be developed. One major obstacle is to switch between different localization mode seamlessly in application, several solutions are introduced to attempt tackling this problem and will be introduced in this report. Video Analytics and IoT People/Asset Sensing for Smart City Applications Supervisor: CHAN, Gary Shueng Han / CSE Student: WU, Minghua / SENG Course: UROP1000, Summer I participated in 2 projects this semester. The first project is the Jockey Club Caring Communities for Dementia Campaign, which aims to use phone as a “forwarder” to locate elderly with dementia. Based on the previous work of the group, I extracted the main services from the app and created an Android Library which can be used by third-party developers to promote the distribution of this project. The second project is AI nurse. I was responsible for studying and reporting the API provided by Fitbit. A sample app was also created for testing the authorization process and the API. I learnt a lot during the process, and I also recognized the aspects that I still need to improve.
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