Month: August 2020

Hi my name is Akmalbek Davronov, I am from uzbekistan Samarkand city, I am interested in painting and decorations, i have done bachelors of business Economics in university of Bangor, UK

The main technical issues regarding smart city solutions are related to data gathering, aggregation, reasoning, data analytics, access, and service delivering via Smart City APIs (Application Program Interfaces). Different kinds of Smart City APIs enable smart city services and applications, while their effectiveness depends on the architectural solutions to pass from data to services for city users and operators, exploiting data analytics, and presenting services via APIs.

Therefore, there is a strong activity on defining smart city architectures to cope with this complexity, putting in place a significant range of different kinds of services and processes. In this paper, the work performed in the context of Sii-Mobility smart city project on defining a smart city architecture addressing a wide range of processes and data is presented. To this end, comparisons of the state of the art solutions of smart city architectures for data aggregation and for Smart City API are presented by putting in evidence the usage semantic ontologies and knowledge base in the data aggregation in the production of smart services. The solution proposed aggregate and re-conciliate data (open and private, static and real time) by using reasoning/smart algorithms for enabling sophisticated service delivering via Smart City API. The work presented has been developed in the context of the Sii-Mobility national smart city project on mobility and transport integrated with smart city services with the aim of reaching a more sustainable mobility and transport systems. Sii-Mobility is grounded on Km4City ontology and tools for smart city data aggregation, analytics support and service production exploiting smart city API. To this end, Sii-Mobility/Km4City APIs have been compared to the state of the art solutions. Moreover, the proposed architecture has been assessed in terms of performance, computational and network costs in terms of measures that can be easily performed on private cloud on premise. The computational costs and workloads of the data ingestion and data analytics processes have been assessed to identify suitable measures to estimate needed resources. Finally, the API consumption related data in the recent period are presented.

Technology is known to bring in innovations; making us live a smarter life. Smarter people prefer smart things, which can understand their needs and act on its own. To meet the expectations of the new generation, intangible things are also rejuvenating themselves. We now prefer to live in cities where almost everything is automated, a city which is so well connected that things happen seamlessly. This is the vision the entire world is following. With the Smart City Initiative, many cities are taking concrete steps towards creating happier and smarter communities living within. Few have paved way into our lives and few we await to witness.

A smart city is a digital revolution where different domains of the city are connected and correlated using different technology modules to provide best services to its citizens and is primarily driven by data. When data generated from each and every department of a city is collected and co-related then optimum decision on allocation of resources and effectiveness of pre-existing services can be taken smoothly.