A worldwide movement in advanced manufacturing countries is seeking to reinvigorate (and revolutionize) the industrial and manufacturing core competencies with the use of the latest advances in information and communications technology. Visual computing plays an important role as the "glue factor" in complete solutions. This article positions visual computing in its intrinsic crucial role for Industrie 4.0 and provides a general, broad overview and points out specific directions and scenarios for future research.

One of the main challenges for the implementation of artificial intelligence (AI) in agriculture includes the low replicability and the corresponding difficulty in systematic data gathering, as no two fields are exactly alike. Therefore, the comparison of several pilot experiments in different fields, weather conditions and farming techniques enhances the collective knowledge. Thus, this work provides a summary of the most recent research activities in the form of research projects implemented and validated by the authors in several European countries, with the objective of presenting the already achieved results, the current investigations and the still open technical challenges. As an overall conclusion, it can be mentioned that even though in their primary stages in some cases, AI technologies improve decision support at farm level, monitoring conditions and optimizing production to allow farmers to apply the optimal number of inputs for each crop, thereby boosting yields and reducing water use and greenhouse gas emissions. Future extensions of this work will include new concepts based on autonomous and intelligent robots for plant and soil sample retrieval, and effective livestock management.

A worldwide trend in advanced manufacturing countries is defining Industrie 4.0, Industrial Internet and Factories of the Future as a new wave that can revolutionize the production and its associated services. Cyber-Physical Systems (CPS) are central to this vision and are entitled to be part of smart machines, storage systems and production facilities able to exchange information with autonomy and intelligence. Such systems should be able to decide and trigger actions, and control each other independently and for such reason it is required the use of Knowledge based and intelligent information approaches. In this paper we present our perspective on how to support Industrie 4.0 with Knowledge based and intelligent systems. We focus in the conceptual model, architecture and necessary elements we believe are required for a real world implementation. We base our conceptualization in the experiences gathered during the participation in different ongoing research projects where the presented architecture is being implemented

This article presents and discusses the implementation of a volume rendering system for the Web, which articulates a large portion of the rendering task in the client machine -- By placing the rendering emphasis in the local client, our system takes advantage of its power, while at the same time eliminates processing from unreliable bottlenecks (e.g. network) -- The system developed articulates in efficient manner the capabilities of the recently released WebGL standard, which makes available the accelerated graphic pipeline (formerly unusable) -- The dependency on specially customized hardware is eliminated, and yet efficient rendering rates are achieved -- The Web increasingly competes against desktop applications in many scenarios, but the graphical demands of some of the applications (e.g. interactive scientific visualization by volume rendering), have impeded their successful settlement in Web scenarios -- Performance, scalability, accuracy, security are some of the many challenges that must be solved before visualWeb applications popularize -- In this publication we discuss both performance and scalability of the volume rendering by WebGL ray-casting in two different but challenging application domains: medical imaging and radar meteorolog

In this paper, we discuss how Cross Reality (XR) and the Industrial Internet of Things (IIoT) can support assembly tasks in hybrid human-machine manufacturing lines. We describe a Cross Reality system, designed to improve efficiency and ergonomics in industrial environments that require manual assembly operations. Our objective is to reduce the high costs of authoring assembly manuals and to improve the process of skills transfer, in particular, in assembly tasks that include workers with disabilities. The automation of short-lived assembly tasks, i.e., manufacturing of limited batches of customized products, does not yield significant returns considering the automation effort necessary and the production time frame. In the design of our XR system, we discuss how aspects of content creation can be automated for short-lived tasks and how seamless interoperability between devices facilitates skills transfer in human-machine hybrid environments.