| Title |
Using a Ubiquitous Personal Online Datastore for Aggregating and Sharing IoT Data to Smart City |
| ID_Doc |
36615 |
| Authors |
Chen, H |
| Title |
Using a Ubiquitous Personal Online Datastore for Aggregating and Sharing IoT Data to Smart City |
| Year |
2022 |
| Published |
|
| DOI |
10.1109/DASC/PiCom/CBDCom/Cy55231.2022.9927797 |
| Abstract |
With the spread of smartphones and smart homes, citizens can create huge amounts of data. However, most of this data is held by the data platform company. Platform companies sometimes leak data and sometimes discontinue unprofitable services. Collecting and analyzing data on residents and the urban environment is essential for smart cities to improve their services. Due to the need for data relevant to residents' privacy, strict restrictions on access and use of this data can be costly. We proposed Ubiquitous Personal Online Datastore (UPOD) as a personal IoT data framework that enables users to become the owners of their data and to freely grant or revoke the sharing of parts of their data. Personal IoT data such as personal movement history and smart home records can be seamlessly collected in a personally owned UPOD. Fragmentation of personal IoT data by platform companies IoT platforms can also be prevented. In this study we use our UPOD framework to collect user's personal data and provide parts of data to smart cities service providers, exchange it for the services of data service providers, and secure the right to opt out of personal data. Data service providers can legally obtain data from users for a specified portion and for a specified period at any time, which saves investment in data security management. Applying the UPOD framework to the smart city sensing platform will improve the smart city service and reduce the effort and cost of retrieving personal data. |
| Author Keywords |
Decentralized Social Network; Solid Pod; UPOD; IoT; Smart City |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000948109800145 |
| WoS Category |
Automation & Control Systems; Computer Science, Artificial Intelligence; Computer Science, Theory & Methods; Engineering, Electrical & Electronic |
| Research Area |
Automation & Control Systems; Computer Science; Engineering |
| PDF |
|