The Internet of Things (IoT) is now shaping our cities to make them more connected, convenient, and intelligent. However, this change will highly rely on extracted values and insights from the big data generated by our cities via sensors, devices, and human activities. Many existing studies and projects have been done to make our cities smart, focusing more on how to deploy various sensors and devices and then collect data from them. However, this is just the first step towards smart cities and next step will be to make good use of the collected data and enable context-awareness and intelligence into all kinds of applications and services via a flexible big data platform. In this paper, we introduce the system architecture and the major design issues of a live City Data and Analytics Platform, namely CiDAP. More importantly, we share our experience and lessons learned from building this practical system for a large scale running smart city testbed, SmartSantander. Our work provides a valuable example to future Smart City platform designers so that they can foresee some practice issues and refer to our solution when building their own smart city data platforms.

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In this paper we present a context-management middleware for Next Generation Networks (NGN). Our middleware, called ICE, is based on the concept of Context Sessions. In contrast to earlier work in context management, we apply NGN design principles to context management and separate signalling from context exchange. We believe that ICE provides an ideal starting point for more flexible and adaptive management of large scale context information compared to existing approaches. In order to allow for easy integration into NGN networks, ICE is implemented as a service on top of the IP Multimedia Subsystem.