Smart City Gnosys
Smart city article details
| Title | Blockchain Framework For Real-Time Streaming Data Generated In Image Sensor Networks For Smart Monitoring |
|---|---|
| ID_Doc | 12483 |
| Authors | Masuda D.; Shinkuma R.; Inagaki Y.; Oki E. |
| Year | 2020 |
| Published | 2020 2nd Conference on Blockchain Research and Applications for Innovative Networks and Services, BRAINS 2020 |
| DOI | http://dx.doi.org/10.1109/BRAINS49436.2020.9223311 |
| Abstract | The smart city concept is attracting increasing attention from society. Smart monitoring, which enables the detection and prevention of road traffic accidents, is one promising application of the smart city concept. The deployment of three-dimensional (3D) image sensor networks formed by light detection and ranging (LIDAR) devices interconnected via a network is a key enabler for smart monitoring. Data collected by image sensor networks for smart monitoring are sensitive because the usage of the data is often related to public safety or law enforcement. Managing sensor data using the blockchain technology is one way to address these sensitivity concerns, as a blockchain network helps prevent data from being tampered with even by the administrators of the system. However, prior works have not considered how to handle streaming data such as image sensor data generated by LIDAR devices in real-time, which means there is a risk of overflow in the network if the data are handled frame by frame. In response to this issue, we propose a blockchain framework for real-time monitoring in a smart city using image sensor networks. Our key concept with this framework is to aggregate hash values converted from multiple frames of image sensor data into one hash value. The proposed framework reduces the number of data 'writes' on a blockchain network, thus preventing any overflow. Our framework also enables the estimation of the optimal number of aggregated hash values that minimizes delay while avoiding overflow. Measurements taken in actual environments using a real-world LIDAR dataset demonstrated the effectiveness of the proposed framework. © 2020 IEEE. |
| Author Keywords | blockchain network; hash aggregation; image sensor network; LIDAR; smart monitoring |
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