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Future converged communication systems have to fulfil challenging tasks, promised to be delivered by the fifth generation (5G) of mobile networks. 5G shall enable services on the move with both well-known and new emerging performance requirements, while preserving high security and privacy levels to the customers’ diverse devices and applications. The applications typically demand a specific quality level end user expectation, measured by Quality of Experience (QoE). To enable QoE, the network has to provide the corresponding end-to-end Quality of Service (QoS), described in terms of technical key performance indicators. The capability to offer different services, covering variable use cases for customer groups in a resource efficient manner, is denoted as network slicing. Addressed services shall cover a broad range of vertical business applications. This contribution will focus on selected solution concepts, rated by potential customers, to enable a set of exemplary industrial applications with demanding requirements in terms of throughput, latency, and device density. Such QoE levels are typically demanded by the automotive industry and car manufacturers to achieve cost-efficient production e.g., by wireless process control. Within the empirical survey of selected use cases of 5G in the automotive industry, the topics Remote Access and Predictive Maintenance, Design and Operation of Mobile Sensor Networks, Wireless Process Monitoring, and Wireless Control and Monitoring of Production Logistics receive the highest approval ratings.

The automotive industry is mainly characterized by shorter product life cycles, ever-growing competitive pressure, significant technological advances and massive changes in the political, technological and sociocultural environment. Therefore, innovation management as an enabler for product, process and business model innovations is becoming more and more important in the automotive industry, a statement which is confirmed by massive increase in innovation expenditure. This paper discusses specific innovation methods related to three cooperation fields: supplier, customer and in-house. The research project, presented in this paper, ascertains their particular implementation level in the automotive industry. One of the findings is the growing significance of the in-house innovation method Big Data as a result of enormous data volume increase. Consequently, the Automotive Big Data Platform (ABDP) Reference Architecture is presented in this paper. Big Data will enable the automotive industry to cope with the challenges.

Against the background of significant changes such as increased air traffic, fierce international competition as well as the radically changing political, technological and environmental conditions, the aviation industry keeps looking for product, process and business model innovations. As a result, the importance of efficient innovation management is growing rapidly. This paper discusses specific innovation methods which can be assigned to three cooperation fields: supplier, customer and in-house. The research project ascertains their particular implementation level in the aviation industry. The results are presented in this paper. One of the findings is the critical importance of Big Data as an explicit in-house innovation method. Its growing significance is a result of the enormous data volume increase, which is an exceptional challenge for the industry, nowadays and in the future. Consequently, a concept for a reference architecture is presented in this paper which will enable the aviation industry to cope with the challenges.

Within our society, individuality, comfort and mobility play an important role for working, travelling and living environments. Especially with the connectivity of a car to its environment, e.g. sensors, the communication to another car, to infrastructure communication and provisioning of relevant information to driver, can be considered as valuable technology of the future. An integrated solution for a connected car can be used for a safe, intelligent and comfortable mobility. Although there are significant results from research projects concerning car-to-x, e.g. simTD, and other infotainment and entertainment projects available, an integrated concept that covers general technical requirements, the drivers’ needs and business aspects is hard to find on the market. Significant requirements derived from technical and market insights are evaluated. These findings reflect the introduction of an integrated architecture that covers car-to-x communication, info- and entertainment and IT-security aspects.

How does a future centralized learning platform for students in an academic environment look like? What are the needs and requirements for current and potential academic users? Are Facebook, WhatsApp and Dropbox the winners? Which recommendations can be worked out for a suitable IT landscape and how does an integrated data security concept look like? This paper analyses the needs and requirements for a centralized learning platform from a students’ point of view.

What will the future learning and academic support environment look like for students? What are the resulting requirements for a suitable tool landscape? As an active member of different communities, students already use a set of tools especially for communication and networking purposes. Students do not stop the usage of their social tools within their universities. However, universities provide their own tools for students to be connected with the organization. Which tools are out of fashion? Which tool classes are needed? And how is the degree of integration to be achieved with common community tools and systems? This paper analyses requirements from the student point of view and discusses aspects for the integration into an academic IT infrastructure.

Advertisement turns into recommendation, web services become independent apps, and mobile devices enforce context awareness. Recommendation as a Service (RaaS) turns into an independent application-based business. By analyzing the trends, the paper introduces a multi-dimensional evaluation scheme to characterize recommender systems. The chart is applied to different research implementations, emphasizing their specifics. Requirements and trends for the future are derived.

People on the move have a grown need for real-time information and services anytime and anywhere. In many situations, travelers do not feel at ease and well informed when using public transport. Context information on mobile phones e.g., location and calendar data, can significantly improve the user experience in the current situation. The paper addresses an approach of service offering and usage on mobile phones. It focuses on a typical scenario in public transport that covers trip planning, mobile ticketing and service offering on the way. A general framework, classifying, supporting and analyzing user context information, including practical experiences from a mobile ticketing solution, will be introduced.

Fur marketingrelevante Fragestellungen und fur die strategische Bewertung von Technologiealternativen ist die Untersuchung des Diffusionsverlaufs bei Netzeffektgutern, wie z.B. Telekommunikationsdiensten, von hohem Interesse. Es wird ein Entscheidungsunterstutzungssystem vorgestellt, dass insbesondere Marketingvariable zur Ausgestaltung relevanter Merkmale von netzeffektbasierten Gutern unterstutzt. Ausgehend von dynamischen Nutzenfunktionen wird ein Modellansatz auf Grundlage der Mastergleichung der Physik bzw. den Mittelwertgleichungen vorgestellt, der Wechselwahrscheinlichkeiten zwischen den Produktalternativen ableitet. Die Anwendungsrelevanz des Modellansatzes wird durch entscheidungsrelevante What-If-Analysen verdeutlicht.

Context aware recommender systems (CARS) adapt to the specific situation in which the recommended item will be consumed. So, for instance, music recommendations while the user is traveling by car should take into account the current traffic condition or the driver’s mood. This requires the acquisition of ratings for items in several alternative contextual situations, to extract from this data the true dependency of the ratings on the contextual situation. In this paper, in order to simplify the in-context rating acquisition process, we consider the individual perceptions of the users about the influence of context on their decisions. We have elaborated a system design methodology where we assume that users can be requested to judge: a) if a contextual factor (e.g., the traffic state) is relevant for their decision making task, and b) how they would rate an item assuming that a certain contextual condition (e.g., traffic is chaotic) holds. Using these evaluations we show that it is possible to build an effective context-aware mobile recommender system.