UAVNet: A Mobile Wireless Mesh Network Using Unmanned Aerial Vehicles

We developed UAVNet, a framework for the autonomous deployment of a flying Wireless Mesh Network using small quadrocopter-based Unmanned Aerial Vehicles (UAVs). The flying wireless mesh nodes are automatically interconnected to each other and building an IEEE 802.11s wireless mesh network. The implemented UAVNet prototype is able to autonomously interconnect two end systems by setting up an airborne relay, consisting of one or several flying wireless mesh nodes. The developed software includes basic functionality to control the UAVs and to setup, deploy, manage, and monitor a wireless mesh network. Our evaluations have shown that UAVNet can significantly improve network performance.

Body sensor network for in-home personal healthcare

A body sensor network solution for personal healthcare under an indoor environment is developed. The system is capable of logging the physiological signals of human beings, tracking the orientations of human body, and monitoring the environmental attributes, which covers all necessary information for the personal healthcare in an indoor environment. The major three chapters of this dissertation contain three subsystems in this work, each corresponding to one subsystem: BioLogger, PAMS and CosNet. Each chapter covers the background and motivation of the subsystem, the related theory, the hardware/software design, and the evaluation of the prototype’s performance.

USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS

Sensor networks have been an active research area in the past decade due to the variety of their applications. Many research studies have been conducted to solve the problems underlying the middleware services of sensor networks, such as self-deployment, self-localization, and synchronization. With the provided middleware services, sensor networks have grown into a mature technology to be used as a detection and surveillance paradigm for many real-world applications. The individual sensors are small in size. Thus, they can be deployed in areas with limited space to make unobstructed measurements in locations where the traditional centralized systems would have trouble to reach. However, there are a few physical limitations to sensor networks, which can prevent sensors from performing at their maximum potential. Individual sensors have limited power supply, the wireless band can get very cluttered when multiple sensors try to transmit at the same time. Furthermore, the individual sensors have limited communication range, so the network may not have a 1-hop communication topology and routing can be a problem in many cases. Carefully designed algorithms can alleviate the physical limitations of sensor networks, and allow them to be utilized to their full potential. Graphical models are an intuitive choice for designing sensor network algorithms. This thesis focuses on a classic application in sensor networks, detecting and tracking of targets. It develops feasible inference techniques for sensor networks using statistical graphical model inference, binary sensor detection, events isolation and dynamic clustering. The main strategy is to use only binary data for rough global inferences, and then dynamically form small scale clusters around the target for detailed computations. This framework is then extended to network topology manipulation, so that the framework developed can be applied to tracking in different network topology settings. Finally the system was tested in both simulation and real-world environments. The simulations were performed on various network topologies, from regularly distributed networks to randomly distributed networks. The results show that the algorithm performs well in randomly distributed networks, and hence requires minimum deployment effort. The experiments were carried out in both corridor and open space settings. A in-home falling detection system was simulated with real-world settings, it was setup with 30 bumblebee radars and 30 ultrasonic sensors driven by TI EZ430-RF2500 boards scanning a typical 800 sqft apartment. Bumblebee radars are calibrated to detect the falling of human body, and the two-tier tracking algorithm is used on the ultrasonic sensors to track the location of the elderly people.

Das Internet der Dinge unter dem Aspekt der Selbststeuerung-Ein Überblick

In den letzten Jahren wurde die Vision einer Welt smarter Alltagsgegenstände unter den Begriffen wie Ubiquitous Computing, Pervasive Computing und Ambient Intelligence in der Öffentlichkeit wahrgenommen. Die smarten Gegenstände sollen mit digitaler Logik, Sensorik und der Möglichkeit zur Vernetzung ausgestattet werden. Somit bilden sie ein „Internet der Dinge“, in dem der Computer als eigenständiges Gerät verschwindet und in den Objekten der physischen Welt aufgeht. Während auf der einen Seite die Vision des „Internet der Dinge“ durch die weiter anhaltenden Fortschritte in der Informatik, Mikroelektronik, Kommunikationstechnik und Materialwissenschaft zumindest aus technischer Sicht wahrscheinlich mittelfristig realisiert werden kann, müssen auf der anderen Seite die damit zusammenhängenden ökonomischen, rechtlichen und sozialen Fragen geklärt werden. Zur Weiterentwicklung und Realisierung der Vision des „Internet der Dinge“ wurde erstmals vom AutoID-Center das EPC-Konzept entwickelt, welches auf globale netzbasierte Informationsstandards setzt und heute von EPCglobal weiterentwickelt und umgesetzt wird. Der EPC erlaubt es, umfassende Produktinformationen über das Internet zur Verfügung zu stellen. Die RFID-Technologie stellt dabei die wichtigste Grundlage des „Internet der Dinge“ dar, da sie die Brücke zwischen der physischen Welt der Produkte und der virtuellen Welt der digitalen Daten schlägt. Die Objekte, die mit RFID-Transpondern ausgestattet sind, können miteinander kommunizieren und beispielsweise ihren Weg durch die Prozesskette finden. So können sie dann mit Hilfe der auf den RFID-Transpondern gespeicherten Informationen Förderanlagen oder sonstige Maschinen ohne menschliches Eingreifen selbstständig steuern.

Entwicklung von energieautarken, intelligenten Ladehilfsmitteln am Beispiel des inBin

Das autonome, intelligente Ladehilfsmittel verkörpert die Idee des Internets der Dinge in der Intralogistik in Reinform. Am Beispiel des inBin wird das Energy-Harvesting in der Intralogistik betrachtet und gezeigt, dass ein Behälter mit komplexen logistischen Funktionen unter realistischer Umgebungsbeleuchtung durch Solarzellen betrieben werden kann.

Linked services for M2M communication with Enterprise IT systems

Linking the physical world to the Internet, also known as the Internet of Things, has increased available information and services in everyday life and in the Enterprise world. In Enterprise IT an increasing number of communication is done between IT backend systems and small IoT devices, for example sensor networks or RFID readers. This introduces some challenges in terms of complexity and integration. We are working on the integration of IoT devices into Enterprise IT by leveraging SOA techniques and Semantic Web technologies. We present a SOA based integration platform for connecting WSNs and large enterprise business processes. For ensuring interoperability our platform is based on Linked Services. These are thoroughly described, machine-readable, machine-reasonable service descriptions.

A Link Quality and Geographical-aware Routing Protocol for Video Transmission in Mobile IoT

Wireless mobile sensor networks are enlarging the Internet of Things (IoT) portfolio with a huge number of multimedia services for smart cities. Safety and environmental monitoring multimedia applications will be part of the Smart IoT systems, which aim to reduce emergency response time, while also predicting hazardous events. In these mobile and dynamic (possible disaster) scenarios, opportunistic routing allows routing decisions in a completely distributed manner, by using a hop- by-hop route decision based on protocol-specific characteristics, and a predefined end-to-end path is not a reliable solution. This enables the transmission of video flows of a monitored area/object with Quality of Experience (QoE) support to users, headquarters or IoT platforms. However, existing approaches rely on a single metric to make the candidate selection rule, including link quality or geographic information, which causes a high packet loss rate, and reduces the video perception from the human standpoint. This article proposes a cross-layer Link quality and Geographical-aware Opportunistic routing protocol (LinGO), which is designed for video dissemination in mobile multimedia IoT environments. LinGO improves routing decisions using multiple metrics, including link quality, geographic loca- tion, and energy. The simulation results show the benefits of LinGO compared with well-known routing solutions for video transmission with QoE support in mobile scenarios.