We are happy to announce two invited talks during the workshop!
What Are your IoT devices doing? – Exploring Citizen’s Privacy Challenges using Augmented Reality, given by Prof. Pan Hui (University of Helsinki, Finland & HKUST, Hong Kong)
The ubiquity of smart devices combined with a general lack of information about the data gathered by them are making privacy a critical challenge for adoption of IoT technologies. Besides lacking awareness of privacy threats, users currently have limited means to control their privacy in these scenarios. In this talk, we present the design and development of a novel augmented reality (AR) prototype that informs users about privacy threats posed by smart devices and provides a unified point of control for data disclosure through privacy-enhancing technologies, called privacy filters. To provide a foundation understanding of users’ privacy awareness and privacy control, we present a quantitative user study that evaluates users’ privacy awareness of commercial IoT devices and our proposed AR system for controlling IoT privacy. Our results show that participants generally are not aware of the risks posed by IoT devices. Informing users about device’s sensing capabilities or its location has an only small effect on privacy awareness, but demonstrating potential malicious use for the sensor has a significant effect on user’s comfort level and awareness. Our results also show that participants are capable of identifying risks and controlling their privacy disclosure better with our AR system against traditional text-based interfaces or voice assistant-based solutions.
Predicting for the Adaptive Transport System, given by Prof. Francisco C. Pereira (Technical University of Denmark, Denmark)
It is not uncommon that traffic prediction tools and research report very high accuracy. However, the very few such tools that exist in the market seem not to be performing as well as people would like, even though their accuracy may in fact correspond to the announced. There is a paradox in the field: traffic prediction is not difficult most of the time (the routine conditions), but sometimes it becomes extremely hard (the non-recurrent events), which is often when it is needed! In fact, our transport system, and in fact, the Smart City as a whole, is moving to a paradigm where supply can adapt much faster to demand than before, and this brings new challenges to predictability. It becomes less acceptable to fail!
This presentation will focus on ongoing and past work from DTU, MIT, CISUC and Singapore-MIT Alliance for Research and Technology (SMART) related to treatment of non-recurrent events in traffic, and its interaction with system optimization.