Abstract
Labour shortage is a reality in agriculture. Farmers are asking for solutions to automate agronomic tasks, such as monitoring, pruning, spraying, and harvesting. The automation of these tasks requires, most of the time, the use of robotic arms to mimic human arms capabilities. The current robotic arm based solutions available, both in the market and in the scientific sphere, have several limitations, such as, low-speed manipulation, the path planning algorithms are not aware of the requirements of the agricultural tasks (robotic motion and manipulation synchronisation), and require active perception tuning to the end-target point. This work benchmarks algorithms from open manipulation planning library (OMPL) considering a cost-effective six-degree freedom manipulator in a simulated vineyard. The OMPL planners shown a very low performance under demanding pruning tasks. The best and most promising results are performed and obtained by BiTRRT. However, further work is needed to increase its performance and reduce planning time. This benchmark work helps the reader to understand the limitations of each algorithm and when to use them. © 2019, Springer Nature Switzerland AG.

Abstract
Particle tracking applied to video passive microrheology is conventionally done through methods that are far from being automatic. Creating mechanisms that decode the image set properties and correctly detect the tracer beads, to find their trajectories, is fundamental to facilitate microrheology studies. In this work, the adequacy of two particle detection methods - a Radial Symmetry-based approach and Gaussian fitting - for microrheology setups is tested, both on a synthetic database and on real data. Results show that it is possible to automate the particle tracking process in this scope, while ensuring high detection accuracy and sub-pixel precision, crucial for an adequate characterization of microrheology studies. © 2019, Springer Nature Switzerland AG.

Abstract
In the Industry 4.0 context, humans are taking up new roles in Cyber-Physical Systems (CPS) since it was realized that they constitute the most flexible part of an automated system. With this new reality, humans are becoming integral parts of CPS, entering in the realm of the Human-in-the-Loop of Cyber-Physical Systems (HiLCPS). In this paper, the challenges and technologies for the integration of humans in CPS environments are briefly discussed, and a practical application of the HiLCPS concept is presented. For this purpose, a human operation workbench is empowered with intelligent decision and assistant systems that use, among others, reasoning algorithms, image processing and speech recognition, to improve the productivity and quality of the tasks performed by humans, particularly focusing the assembly of highly customized products, as well as the training of operators to perform complex assembly, repairing or maintenance tasks.

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Abstract
The topic of Smart Cities involves various aspects of convergence and support to necessarily safe activities, which are dependent on reliable data and reliable sources. The answer could be provided by means of the adoption model of Blockchain technologies for this purpose, applied to the different characteristics of the city from the electronic governance, the contracting of products and services, and the sensing or data collection. The multiple IoT objects and the multiple networks, together with the Blockchain technology, may result in safer and more efficient cities. This paper analyzes and deepens the concept of Smart Cities using Blockchain technology as a platform for safety and reliability of the data. It is intended to reflect critically on this topic, looking through the different aspects involving this concept and the way in which it can implement. It analyzes the Smart Cities and its ecosystems with the generic data models, integrated, with quality data and trusted information.

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