http://seb-21.kesinternational.org/cms/userfiles/is04.pdf
As the development of urban areas keeps encouraging, to ensure populace development, financial advancement, and social advance stroll in a similar way, the difficulties of urban communities should be however through. Smart and sustainable cities are transformed by improving infrastructure and transportation systems, providing waste management, reducing traffic congestion. Smart cities become more innovative, competitive, and attractive by promoting integrated and sustainable development. Nowadays, lots of smart devices and objectives are integrated with different types of sensors and Internet of Things (IoT) as a whole system to detect the environmental information, for example, carbon monoxide, nitrogen dioxide, vehicle and passerby activity, light, barometric weight, temperature, and encompassing sound. Those connected systems could allow to citizens to interface with the nodes via smartphones in order to analyse the environmental data collected by these nodes. However, these complex systems require rapid decision-making for improving system quality, and sustainability based on big-data analytics. Some of these complex systems are not yet ready to manage and take full advantage of the big data that is available to them due to the lack of pipelined data acquisition, processing, analysis, and finally, decision-making procedures that are tailored to the specific problem.
Big-data analytics is a new research area and a key enabler for unlimited domains, including sustainable and smart cities. The proposed special session aims to bring together new theories and applications of big data analytics in sustainable and smart cities. We solicit both academic, research, and industrial contributions. The topics of interest include, but are not limited to:
• Big Data Analytics in Sustainable Smart City
• Internet of Things Sustainability.
• Data Science for Sustainable Applications.
• Real-Time Ubiquitous Data Science and Software.
• Mobile Platform for Privacy Preserving Data Science for Sustainable City.
• Data Applications of Cognitive Communication for Sustainable City.
• Scalable Data Analytics for Sustainable City.
• Machine Learning Approaches and Data Processing.
• Big Algorithms and Software Development.
• Global Climate Analytics.
• Population Growth and Migration Analytics.
• Cyber-Threats Analytics for Smart City Application.
• Data Collection, Modeling, Storage, And Visualization
• Online Experiments, Simulation and Agent-Based Modeling Applied to Sustainable City.
• Social Network Analysis and Semantic Network Analysis.