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CP-12 - Location-Based Services

Location-Based Services (LBS) are mobile applications that provide information depending on the location of the user. To make LBS work, different system components are needed, i.e., mobile devices, positioning, communication networks, and service and content provider. Almost every LBS application needs several key elements to handle the main tasks of positioning, data modeling, and information communication. With the rapid advances in mobile information technologies, LBS have become ubiquitous in our daily lives with many application fields, such as navigation and routing, social networking, entertainment, and healthcare. Several challenges also exist in the domain of LBS, among which privacy is a primary one. This topic introduces the key components and technologies, modeling, communication, applications, and the challenges of LBS.

CP-10 - Social Media Analytics

Social media streams have emerged as new sources to support various geospatial applications. However, traditional geospatial tools and systems lack the capacities to process such data streams, which are generated dynamically in extremely large volumes and with versatile contents. Therefore, innovative approaches and frameworks should be developed to detect an emerging event discussed over the social media, understand the extent, consequences of the event, as well as it time-evolving nature, and eventually discover useful patterns. In order to harness social media for geospatial applications, this entry introduces social media analytics technologies for harvesting, managing, mining, analyzing and visualizing the spatial, temporal, text, and network information of social media data.

CP-06 - Graphics Processing Units (GPUs)

Graphics Processing Units (GPUs) represent a state-of-the-art acceleration technology for general-purpose computation. GPUs are based on many-core architecture that can deliver computing performance much higher than desktop computers based on Central Processing Units (CPUs). A typical GPU device may have hundreds or thousands of processing cores that work together for massively parallel computing. Basic hardware architecture and software standards that support the use of GPUs for general-purpose computation are illustrated by focusing on Nvidia GPUs and its software framework: CUDA. Many-core GPUs can be leveraged for the acceleration of spatial problem-solving.