Martin Bauer

Efficiently Managing Context Information for Large-Scale Scenarios

In this paper, we address the data management aspect of large-scale pervasive computing systems. We aim at building an infrastructure that simultaneously supports many kinds of context-aware applications, ranging from room level up to nation level. This all-embracing approach gives rise to synergetic benefits like data reuse and sensor sharing. We identify major classes of context data and detail on their characteristics relevant for efficiently managing large amounts of it. Based on that, we argue that for large-scale systems it is beneficial to have special-purpose servers that are optimized for managing a certain class of context data. In the Nexus project we have implemented five servers for different classes of context data and a very flexible federation middleware integrating all these servers. For each of them, we highlight in which way the requirements of the targeted class of data are tackled and discuss our experiences

Location Models from the Perspective of Context-Aware Applications and Mobile Ad Hoc Networks

Abstract: Location models are crucial for providing location-dependent data to context-aware applications. In this paper, we present two approaches for modeling location information taken from an infrastructure-based and an ad hoc network-based application scenario. From these approaches we derive requirements for a general location modeling language for ubiquitous computing.

Where are you pointing at? A study of remote collaboration in a wearable videoconference system

This paper reports on an empirical study aimed at evaluating the utility of a reality-augmenting telepointer in a wearable videoconference system. Results show that using this telepointer a remote expert can effectively guide and direct a field workers manual activities. By analyzing verbal communication behavior and pointing gestures, we were able to determine that experts overwhelmingly preferred pointing for guiding workers through physical tasks.

From home to world - supporting context-aware applications through world models

In the vision of pervasive computing smart everyday objects communicate and cooperate to provide services and information to users. Interoperability between devices and applications not only requires common protocols but also common context management. In this paper we discuss requirements on the context management based on the Georgia Techs Aware home environment and the global context management perspective of the Nexus project. Our experiences with integrating the aware home spatial service into the Nexus platform show how federation concepts and a common context model can provide applications with uniform context information in different administrative and application domains.

Building a Big Data Platform for Smart Cities: Experience and Lessons from Santander

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 test bed, 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.

IoT Reference Architecture

In this chapter we present our IoT Reference Architecture. This IoT Reference Architecture is, among others, designed as a reference for the generation of compliant IoT concrete architectures that are tailored to one’s specific needs. For other usages of the IoT Architectural Reference Model see Chap. 3.

IoT Reference Model

The first major contribution of the IoT Architectural Reference Model (IoT ARM) is the IoT Reference Model itself. Besides models, the IoT Reference Model provides the concepts and definitions on which IoT architectures can be built. This Chapter introduces the IoT Reference Model as a precondition for working with the Reference Architecture that is introduced in Chap. 8.

Towards the observation of spatial events in distributed location-aware systems

In this paper the event concept is applied to support the interaction between mobile users and distributed location-aware systems. Taking a number of examples, the components of an event specification language are derived that can be used beyond the domain of location-aware systems.

ContextCube - providing context information ubiquitously

Sensing the state of the environment is an important source for context-aware applications. Several approaches exist to provide sensor information to mobile application nodes. As the extreme cases we have pure infrastructures and pure ad hoc networks. In order to allow sensor platforms to serve both of these approaches, we have designed a universal sensor platform and integrated it into an infrastructure-based approach as well as into ad hoc networks. In this paper we discuss the requirements on such a platform, the design, and the experiences.

Modeling of sensor data and context for the Real World Internet

The Internet is expanding to reach the real world, integrating the physical world into the digital world in what is called the Real World Internet (RWI). Sensor and actuator networks deployed all over the Internet will play the role of collecting sensor data and context information from the physical world and integrating it into the future RWI. In this paper we present the SENSEI architecture approach for the RWI; a layered architecture composed of one or several context frameworks on top of a sensor framework, which allows the collection of sensor data as well as context information from the real world. We focus our discussion on how the modeling of information is done for different levels (sensor and context data), present a multi-layered information model, its representation and the mapping between its layers.