| Title | Review and synthesis of Big Data analytics and computing for smart sustainable cities |
|---|---|
| ID_Doc | 42182 |
| Authors | Chang, JP; Kadry, SN; Krishnamoorthy, S |
| Title | Review and synthesis of Big Data analytics and computing for smart sustainable cities |
| Year | 2020 |
| Published | Iet Intelligent Transport Systems, 14, 11 |
| Abstract | There has been a great deal of movement around the idea of Smart City for quite a while. Urban areas are being distinguished as future shrewd urban areas. Hypothetically, at any rate, brilliant urban areas can on a very basic level transform ourselves at numerous levels, the execution of the smart city idea around the globe has been sporadic, the best-case scenario because of a few reasons. Whatever the stage the smart city usage is at internationally, big data, information and the Internet of things (IoT) can drive the execution. Huge information and the IoT are getting down to business with other programming and equipment to lead the vision of a smart city to realisation. Big information can help diminish outflows and cut down contamination. In this study, the adaptive heuristic mathematical model based on traffic congestion has been proposed. Sensors fitted in the streets will gauge the complete traffic at various occasions of multi-day and the all-out emissions. The information can be sent to a focal unit which will organise with the traffic police using sustainable management techniques. Traffic can be overseen or redirected along different, less blocked territories to lessen carbon outflows in a specific territory. Sustainable management analysis has been done based on numerical simulations. |
| https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/iet-its.2020.0006 |
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