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The wide distribution of smart phones allows to inform and interact with citizens in real-time, thus enabling the vision of smart cities. However, the reliability of smart city applications highly depends on the availability of appropriate, accurate, and trustworthy data. To increase the reliability of smart city applications, the European project CityPulse employs knowledge-based methods for monitoring and testing at all stages of the data stream processing and interpretation pipeline. During design-time testing validates the behaviour of applications with regard to different levels of quality of information. During run-time monitoring assesses the reliability of data streams, the plausibility of information, and the correct evaluation of extracted events. The monitored quality is exploited by fault recovery and conflict resolution mechanisms to ensure fault-tolerant execution of applications.
In der Agrartechnik steht Landwirten und Lohnunternehmern eine steigende Anzahl digitaler Dienste zur Verfügung. Eine Modellierung, Ausführung und Steuerung von kooperativen Agrarprozessen ist aufgrund der verschiedenen, zueinander inkompatiblen IT-Lösungen nur eingeschränkt möglich. Es fehlt ein einheitlicher Standard zur Beschreibung dieser Prozesse. Der Beitrag stellt die Beschreibung von Agrarprozessen mit der Business Process Model and Notation (BPMN) dar. Domänenexperten (z.B. Landwirte, Lohnunternehmer, digitale Dienstanbieter) können kooperative Prozessabläufe plattformübergreifend gestalten, ohne dabei Prozessinterna mit anderen Akteuren teilen zu müssen. Als Brücke zwischen der kooperativen Prozessebene und der ausführenden Maschinenebene wird im Beitrag Message Queue Telemetry Transport (MQTT) eingesetzt: Mittels MQTT können Anweisungen und Informationen (z.B. Arbeitsaufträge, Statusdaten) zwischen beiden Ebenen in Echtzeit vermittelt und verarbeitet werden.
Die Unterstützung des Maschinenführers auf der Landmaschine durch digitale Dienste nimmt immer stärker zu. Die Darstellungsmöglichkeiten sind jedoch auf die Größe der eingesetzten Terminals beschränkt. Um Sichteinschränkungen aus der Kabine durch zusätzliche Terminals zu vermeiden, ist der Einsatz von Augmented Reality sinnvoll. Hier lassen sich die vorhandenen Informationen statisch oder dynamisch in das Sichtfeld des Landwirts einblenden. Doch erst durch die in diesen Beitrag gezeigte Overlay Darstellungsebene mit integrierten Informationen lässt sich das Potenzial der Augmented Reality vollständig nutzen.
For Delay-Tolerant Networks (DTNs) many routing algorithms have been suggested. However, their performance depends heavily on the applied scenario. Especially heterogeneous scenarios featuring known and unknown node movements as well as different kinds of data lead to either poor delivery ratios or exhausted network resources.
To overcome these problems this paper introduces Data-Driven Routing for DTNs. Data is categorized according to its requirements into priority queues. Each queue applies an appropriate DTN routing algorithm that fits the data requirements best. Simulation results show that Data-Driven Routing allows high delivery ratios for time-critical data while saving network resources during the transfer of less time-critical data at the same time.
Reliable information processing is an indispensable task in Smart City environments. Heterogeneous sensor infrastructures of individual information providers and data portal vendors tend to offer a hardly revisable information quality. This paper proposes a correlation model-based monitoring approach to evaluate the plausibility of smart city data sources. The model is based on spatial, temporal, and domain dependent correlations between individual data sources. A set of freely available datasets is used to evaluate the monitoring component and show the challenges of different spatial and temporal resolutions.
Long Range Wide Area Network (LoRaWAN) operates in the ISM band with 868 MHz, where the Time on Air (ToA) is regulated in the EU to 1 %. LoRaWAN nodes use the Adaptive Data Rate (ADR) algorithm to adapt their data rates during operation. The standard ADR algorithm works well with stationary nodes, however is very slow in the adaptation for mobile nodes. This paper introduces a new ADR algorithm for LoRaWAN that is supported by higher level meta-data for sensor streams, namely Quality of Information (QoI). With the help of QoI it is possible to provide additional information to the new ADR algorithm, reducing the convergence time and thus improving the Packet Delivery Ratio (PDR) of data from mobile sensor nodes. The new algorithm requires only modifications on network server side and keeps backwards compatibility with LoRaWAN nodes. Results show a significant better PDR compared to the standard ADR in scenarios with a limited number of mobile nodes.
Our world and our lives are changing in many ways. Communication, networking, and computing technologies are among the most influential enablers that shape our lives today. Digital data and connected worlds of physical objects, people, and devices are rapidly changing the way we work, travel, socialize, and interact with our surroundings, and they have a profound impact on different domains,such as healthcare, environmental monitoring, urban systems, and control and management applications, among several other areas. Cities currently face an increasing demand for providing services that can have an impact on people’s everyday lives. The CityPulse framework supports smart city service creation by means of a distributed system for semantic discovery, data analytics, and interpretation of large-scale (near-)real-time Internet of Things data and social media data streams. To goal is to break away from silo
applications and enable cross-domain data integration. The CityPulse framework integrates multimodal, mixed quality, uncertain and incomplete data to create reliable, dependable information and continuously adapts data processing techniques to meet the quality of information requirements from end users. Different than existing solutions that mainly offer unified views of the data, the CityPulse framework is also equipped with powerful data analytics modules that perform intelligent data aggregation, event detection, quality
assessment, contextual filtering, and decision support. This paper presents the framework, describes ist components, and demonstrates how they interact to support easy development of custom-made applications for citizens. The benefits and the effectiveness of the framework are demonstrated in a use-case scenario
implementation presented in this paper.