Smart Home
Privacy perception refers to the control individuals have over the use of their data, including determining who can access, share, and utilize it without interference or intrusion. In the context of the Internet of Things (IoT), particularly in Smart Home Data Monetization (SH-DM), users’ data is aggregated and made available to potential service providers to target end users with personalized advertisements.
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This dataset presents a comprehensive video collection of Internet of Things (IoT) products, encompassing both market successes and failures. Its primary focus is to explore the vision, technology, and capabilities of these IoT innovations, recognizing that products not viable today might inspire or become feasible in the future due to advancements in technology and reductions in manufacturing costs. The collection is particularly valuable for a wide array of stakeholders in IoT, including educators, researchers, product designers, and manufacturers.
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Smart homes contain programmable electronic devices (mostly IoT) that enable home automation. People who live in smart homes benefit from interconnected devices by controlling them either remotely or manually/autonomously. However, high interconnectivity comes with an increased attack surface, making the smart home an attractive target for adversaries. NCC Group and the Global Cyber Alliance recorded over 12,000 attacks to log into smart home devices maliciously. Recent statistics show that over 200 million smart homes can be subjected to these attacks.
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With the rapid deployment of indoor Wi-Fi networks, Channel State Information (CSI) has been used for device-free occupant activity recognition. However, various environmental factors interfere with the stable propagation of Wi-Fi signals indoors, which causes temporal variation of CSI data. In this study, we investigated temporal CSI variation in a real-world housing environment and its impact on learning-based occupant activity recognition.
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This is a repository of 102 smart home conflict scenarios, which were designated as conflict by actual human users. In other words, humans consider the scenarios below to be conflicts in a smart home environment. To see how to use this repository, and how the repository was collected, please read the following paper:
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