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When it comes to digitalization, construction sites are still at the beginning of an ongoing transformation process. Two major causes are the complexity of construction site environments and the lack of interoperability between the different actors, such as machines and site suppliers that are involved in the construction project. This has direct implications on the efficiency, quality, and production time of construction projects. Thus, there is a strong need to fill this digitalization gap by considering the latest advancements in the Internet of Things (IoT), as well as edge and cloud computing. In this paper, we suggest a data-driven approach for construction sites, in which we extract data from machines, send it to a central data storage with scalable computational resources and analyze it to improve the existing construction processes. For that, we studied requirements of selected construction site processes and designed a communication architecture that scales with the complex characteristics of real-world applications. Additionally, we propose a digital process platform that supports a wide range of users with their different roles on construction sites and builds the foundation for further research, implementation, and evaluation of according construction site innovations. With the proposed platform framework, we extend the construction site towards an integrated Cyber-Physical System (CPS) and contribute to the standardization of communication infrastructures within the construction sector by merging different solutions from the area of information and communication technologies.

Today’s construction sites are still at the beginning of a continuous digital transformation process. Among others, this is due to complex site environments and an existing lack of inter-operability between various site components such as the involved machinery. Consequently, this lack leads to direct implications on the efficiency, quality as well as the production time of construction projects. In order to contribute to filling this gap, we develop a manufacturer-independent digital process platform for construction sites of the future. This paper presents first results after the successful software implementation of the digital process platform. Along the real-world use-case ‘road construction’, we highlight the need for the utilization of Big Data technologies and present the implemented communication infrastructure as well as the user interface of our digital process platform. Finally, we show a proof of concept for the platform along the platform use-case ‘static geo-fencing for construction machines’ and conduct an initial evaluation of that exemplary use-case.

In recent years, Virtual Reality (VR) technology has found their way into higher education. Its power lays in its ability to provide immersive three-dimensional (3D) experiences that help conveying educational content whilst providing rich interaction possibilities. Especially in mining engineering education, VR has high potential to reshape the provided learning content. Field trips, i.e. mine visits, are an integral part of the education and necessary to transfer knowledge to students. However, field trips are time and cost intensive and mines often have tight entry regulations. As a result, the number of field trips is limited. VR-based field trips offer a considerable alternative presupposed they replicate the complex mining environment realistically. In addition, VR mines have the advantage of taking students close to events (e.g. explosions) that are impossible to demonstrate in a real mine. However, generating realistic 3D content for VR still involves complex, and thus time consuming tasks. Therefore, we present the design of a VR Framework for teaching mining students based on 360° video data, its evaluation in three different lectures, and its extension based on the feedback we received from students and teachers from four different universities.

This chapter deals with the integration of Augmented and Virtual Reality (AR/VR) elements into academic mining education. The focus lies on the didactical approach within the EU-funded MiReBooks (Mixed Reality Books) project. The project aims to develop a series of AR- and VR-based interactive mining manuals as a new digital standard for higher education across European engineering education. By combining AR and VR technologies, it is possible to address current challenges in mining education in an innovative way. These virtual applications should make otherwise impossible and dangerous situations accessible to students. Classical paper-based teaching materials are enriched with AR content and translated into pedagogically and didactically coherent manuals for integrative use in the classroom. The authors explore how AR and VR instruments can be effectively integrated into teaching. The results of a broad evaluation of AR/VR-based lectures are presented and discussed in this chapter. The experiences and findings are summarized in a decision matrix for the use of AR/VR-based technologies in teaching.

In the age of digitalization, a huge amount of sentiments are expressed daily on university related topics using social media platforms. Particularly, posted statements from students and teachers can provide a potential source for evaluating universities. Twitter as one of the most popular microblogging platforms is a rich data resource for opinion mining. Stimulated by this fact, ways to analyze Twitter for information in the context of universities are sought. This paper looks at the analysis of social media sentiment as a complementary source for evaluating universities. The extracted results can support university rankings that experience criticism in terms of measuring vital indicators. This paper relays on sentiment analysis methods to analyze opinions published on Twitter. For this purpose, at first, tweets that are related to selected universities in Germany were collected. Second, the tweets were classified based on their sentiment into “Positive” and “Not Positive” tweets. At last, the results were analyzed providing information about the communicative topics at the universities. This paper gives an outlook to further research in context of an automated analysis of social media content in order to support the evaluation of universities.