| Title |
Towards a data-driven IoT software architecture for smart city utilities |
| ID_Doc |
40845 |
| Authors |
Simmhan, Y; Ravindra, P; Chaturvedi, S; Hegde, M; Ballamajalu, R |
| Title |
Towards a data-driven IoT software architecture for smart city utilities |
| Year |
2018 |
| Published |
Software-Practice & Experience, 48, 7 |
| DOI |
10.1002/spe.2580 |
| Abstract |
The Internet of things (IoT) is emerging as the next big wave of digital presence for billions of devices on the Internet. Smart cities are a practical manifestation of IoT, with the goal of efficient, reliable, and safe delivery of city utilities like water, power, and transport to residents, through their intelligent management. A data-driven IoT software platform is essential for realizing manageable and sustainable smart utilities and for novel applications to be developed upon them. Here, we propose such service-oriented software architecture to address 2 key operational activities in a smart utility: the IoT fabric for resource management and the data and application platform for decision-making. Our design uses Open Web standards and evolving network protocols, cloud and edge resources, and streaming big data platforms. We motivate our design requirements using the smart water management domain; some of these requirements are unique to developing nations. We also validate the architecture within a campus-scale IoT testbed at the Indian Institute of Science, Bangalore and present our experiences. Our architecture is scalable to a township or city while also generalizable to other smart utility domains. Our experiences serve as a template for other similar efforts, particularly in emerging markets and highlight the gaps and opportunities for a data-driven IoT software architecture for smart cities. |
| Author Keywords |
big data platforms; cloud computing; information integration; Internet of things; smart cities; stream processing; wireless sensor networks |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000434645700004 |
| WoS Category |
Computer Science, Software Engineering |
| Research Area |
Computer Science |
| PDF |
https://arxiv.org/pdf/1803.02500
|