| Title |
MLK Smart Corridor: An Urban Testbed for Smart City Applications |
| ID_Doc |
45588 |
| Authors |
Harris, A; Stovall, J; Sartipi, M |
| Title |
MLK Smart Corridor: An Urban Testbed for Smart City Applications |
| Year |
2019 |
| Published |
|
| DOI |
|
| Abstract |
Urbanization over the next decade will present many complex challenges to developing cities. The smart city concept aims to address these challenges by exploiting large scale deployments of Internet of Things (IoT) and communication technologies. These technologies generate data that provide quantifiable insights into the state of the infrastructure within a city. Using these insights, cities can more effectively allocate resources, manage services, and enhance the lives of its citizens. The data generated by smart cities is complex and requires high throughput. Advanced data integration platforms must support city-wide data collection, analysis, and storage. These systems must provide features that allow them to scale alongside the growth of the cities to support high rates of data ingestion in large volumes. Additionally, these systems must support low latency response times which is a critical requirement for time sensitive smart city applications. In this paper, we introduce a smart city testbed that will provide a real-world testing environment for applications in areas such as intelligent transportation, pedestrian safety, and autonomous vehicles. The proposed testbed will act as an open platform for researchers and developers to test new sensors, algorithms and more in a live urban environment, allowing them to test before deploying a product or application. In addition to the physical testbed and its capabilities, we will discuss the data integration system and applications responsible for collecting, analyzing, and storing the data generated by the testbed. Lastly, we will introduce an open data platform where researchers can access datasets generated by the testbed. |
| Author Keywords |
Big Data; smart city; Iot; Testbed; Software Architecture |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000554828703073 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Information Systems; Computer Science, Theory & Methods |
| Research Area |
Computer Science |
| PDF |
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