Towards first urban data space in Bulgaria

Vassilev, Vassil, Sowinski-Mydlarz, Viktor, Mariyanayagam, Dion, Petrova-Antonova, Dessislava, Marinov, Evgeny, Hristov, Petar O., Bali, Tarun, Radu, Sorin, Nakarmi, Sabin and Rabka, Monika (2022) Towards first urban data space in Bulgaria. 2022 IEEE International Smart Cities Conference (ISC2) (992223). pp. 1-7.

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Abstract / Description

Smart city is no longer fiction, which targets the future – it is now around us and requires immediate action in different directions: environment, transport, energy, social and cultural life, healthcare, etc. This article presents the current efforts of GATE Institute at Sofia University for building an urban data space based on data from a variety of sources in the Bulgarian capital. It has an open architecture, based on a private cloud, which allows the integration of diverse data and provides different data processing capabilities and services necessary to build integral data spaces. The pilot implementation currently performs monitoring and analysis of the environmental factors in Sofia using a set of bespoke components, which implement data management and data analysis algorithms from simple filtering and correlation to data analytics and prediction using historical data, static modelled data and dynamic data from environmental sensors in real-time. It serves as a basis for data enrichment based on different sources and cross-domain analysis using a variety of methods. This new opportunity has a huge potential and will have a significant impact on urban life – from planning the infrastructure and managing the communal services to the personalization of social services for the citizens.

Item Type:	Article
Uncontrolled Keywords:	AI-powered smart city services; data platform; urban data space; environment monitoring; urban analysis and simulation
Subjects:	000 Computer science, information & general works 600 Technology
Department:	School of Computing and Digital Media
Depositing User:	Vassil Vassilev
Date Deposited:	17 Aug 2022 10:38
Last Modified:	16 Dec 2022 11:25
URI:	https://repository.londonmet.ac.uk/id/eprint/7856

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