Smart City Data Stream Visualization Using Glyphs

Investigating the Role of Virtual Reality in Planning for Sustainable Smart Cities

“…Considerable research has focused on different visualization techniques including heat maps [14], glyph annotated maps [15] and tradition 2D graphs [16], but studies on the effectiveness of VR in modeling the future of smart cities and on demonstrating the impacts of "what-if" scenarios to policy-makers and communities is lacking.…”

Addressing big data challenges in smart cities: a systematic literature review

“…Issues such as data visualization, i.e., failure of big data when unusual circumstances such as Tsunami takes place (Villanueva et al, 2014), delay in data fetching from remote storage devices or due to geographical constraints (Li et al, 2015b), lack of big data analytics platform between applications and services to provide data intelligence (Xiong et al, 2014), and lack of appropriate tools and techniques for decision making (Truong and Dustdar, 2014) have been highlighted in literature. In order to deal with such issues, researchers have suggested techniques such as data pre-fetching using Bayesian algorithm which can timely predict the data required by the user and transfer it from remote location to the local cache (Li et al, 2015b), data streaming in real time using glyphs to ensure scalability and modularity of data to overcome the visualization issues (Li et al, 2015b), involvement of humans to visualize the patterns as they can successfully collect the data during unusual circumstances (Li et al, 2015b), and the development of context aware platforms between data sources and services for effective decision making process (Xiong et al, 2014).…”

“…Big data has some important characteristics namely volume, velocity, variety, veracity, and value (Villanueva et al, 2014). Volume indicates that the data is ever growing and expanding beyond terabytes.…”

“…Veracity emphasizes the significance of addressing and managing the data uncertainty, however big data often fails in unusual circumstances (Koh et al, 2015). As high data quality is a crucial requirement for big data (Villanueva et al, 2014), there should be a way to achieve unified data and avoid dirty data (Corradi et al, 2015). Lastly, value refers to the necessity of technological innovation that enables people and organizations to integrate, analyze, and visualize different kinds of data at different temporal and spatial scales.…”

“…Lastly, value refers to the necessity of technological innovation that enables people and organizations to integrate, analyze, and visualize different kinds of data at different temporal and spatial scales. However, sometimes the complexity of big data restricts it to be processed and analyzed using traditional ways (Villanueva et al, 2014). As a result, though the big data has immense potential to improve the quality of urban life, its use in smart cities accompanies several challenges.…”