Real-Time Emergency Vehicle Response System for Smart City Applications

Author(s):  
Lima Priyadarsini ◽  
Prashant Deshmukh ◽  
Santos Kumar Das
2019 ◽  
Vol 6 (2) ◽  
pp. 2651-2668 ◽  
Author(s):  
Sefki Kolozali ◽  
Daniel Kuemper ◽  
Ralf Tonjes ◽  
Maria Bermudez-Edo ◽  
Nazli Farajidavar ◽  
...  
Keyword(s):  

2021 ◽  
Vol 12 (5/6) ◽  
pp. 507
Author(s):  
Ainun Kamal ◽  
Fiza Jefreen ◽  
Md. Pabel Sikder ◽  
Shah Reza Mohammad Fahad Ul Hossain ◽  
Shoaib Mahmud ◽  
...  

Author(s):  
Suresh P. ◽  
Keerthika P. ◽  
Sathiyamoorthi V. ◽  
Logeswaran K. ◽  
Manjula Devi R. ◽  
...  

Cloud computing and big data analytics are the key parts of smart city development that can create reliable, secure, healthier, more informed communities while producing tremendous data to the public and private sectors. Since the various sectors of smart cities generate enormous amounts of streaming data from sensors and other devices, storing and analyzing this huge real-time data typically entail significant computing capacity. Most smart city solutions use a combination of core technologies such as computing, storage, databases, data warehouses, and advanced technologies such as analytics on big data, real-time streaming data, artificial intelligence, machine learning, and the internet of things (IoT). This chapter presents a theoretical and experimental perspective on the smart city services such as smart healthcare, water management, education, transportation and traffic management, and smart grid that are offered using big data management and cloud-based analytics services.


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