| Title |
Monitoring the Smart City Sensor Data Using Thingsboard and Node-Red |
| ID_Doc |
37231 |
| Authors |
Okhovat, E; Bauer, M |
| Title |
Monitoring the Smart City Sensor Data Using Thingsboard and Node-Red |
| Year |
2021 |
| Published |
|
| DOI |
10.1109/SWC50871.2021.00064 |
| Abstract |
The ubiquitous use of smartphones, smart devices, and low-cost sensors, has fostered much attention around the Internet of things (IoT). The Internet of Things has led to the manufacturing of more IoT-related products ranging from devices to applications. The sensors in an IoT network provide data on the environment in which they are deployed and interact with other devices and the applications in the broader IoT ecosystem. IoT components do not necessarily adhere to the same standard and so can be very heterogeneous in a particular environment. This can create challenges in the collection and monitoring of heterogeneous data in real-time as well as monitoring the infrastructure itself. Such data collection is not only important for the analysis of the environment but also for monitoring the health of the devices and operational components, such as software elements. In this paper, we introduce an architecture aimed at collecting, visualizing, and monitoring streams of data from sensors and from infrastructure components. The ThingsBoard IoT platform is used for data collection and visualization. Node-Red is used to categorize the data on the sensor name. Experiments using sensor data sets are provided to illustrate the approach, processing, and visualization. |
| Author Keywords |
Internet of Things; IoT Solution; Smart City; Monitoring; ThingsBoard; Node-Red |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000937542900054 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Information Systems; Computer Science, Theory & Methods; Engineering, Electrical & Electronic |
| Research Area |
Computer Science; Engineering |
| PDF |
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