Abstract
Nature inspired metaheuristics algorithms have been the target of several studies in the most varied scientific areas due to their high efficiency in solving real world problems. This is also the case of agriculture. Among the most well-established nature inspired metaheuristics the ones selected to be addressed in this work are the following: genetic algorithms, differential evolution, simulated annealing, harmony search, particle swarm optimization, ant colony optimization, firefly algorithm and bat algorithm. For each of them, the mechanism that inspired it and a brief description of its operation is presented, followed by a review of their most relevant agricultural applications. © Springer Nature Switzerland AG 2019.

Abstract
Steep slope vineyards are a complex scenario for the development of ground robots due to the harsh terrain conditions and unstable localization systems. Automate vineyard tasks (like monitoring, pruning, spraying, and harvesting) requires advanced robotic path planning approaches. These approaches usually resort to Simultaneous Localization and Mapping (SLAM) techniques to acquire environment information, which requires previous navigation of the robot through the entire vineyard. The analysis of satellite or aerial images could represent an alternative to SLAM techniques, to build the first version of occupation grid map (needed by robots). The state of the art for aerial vineyard images analysis is limited to flat vineyards with straight vine’s row. This work considers a machine learning based approach (SVM classifier with Local Binary Pattern (LBP) based descriptor) to perform the vineyard segmentation from public satellite imagery. In the experiments with a dataset of satellite images from vineyards of Douro region, the proposed method achieved accuracy over 90%. © Springer Nature Switzerland AG 2019.

Abstract
Viticulturists need to obtain the estimation of productivity map during the grape vine harvesting, to understand in detail the vineyard variability. An accurate productivity map will support the farmer to take more informed and accurate intervention in the vineyard in line with the precision viticulture concept. This work presents a novel solution to measure the productivity during vineyard harvesting operation realized by a grape harvesting machine. We propose 2D LIDAR sensor attached to low cost IoT module located inside the harvesting machine, to estimate the volume of grapes. Besides, it is proposed data methodology to process data collected and productivity map, considering GIS software, expecting to support the winemakers decisions. A PCD map is also used to validate the method developed by comparison. © Springer Nature Switzerland AG 2019.

Abstract
This paper summarises the joint efforts of a multinational group of six undergraduate students cooperating within the European Project Semester (EPS) conducted at the Instituto Superior de Engenharia do Porto (ISEP). The EPS@ISEP initiative, made available as a part of the Erasmus+ international students exchange programme, employs the principles of problem-based learning, facing students with—albeit downscaled—real-life scenarios and tasks they may encounter in their future professional practice. Participation in the project initiative outclasses most of the traditional courses through a wide spawn of its learning outcomes. Participants acquire not only hard skills necessary for an appropriate execution of the project, but also broaden their understanding of the approached problem through detailed scientific, management, marketing, sustainability, and ethics analysis—all in the atmosphere of multicultural and interdisciplinary collaboration. The team under consideration, based on personal preferences and predispositions, chose the topic of vertical farming and, in particular, to design a domestic indoor gardening solution, appropriate for space efficient incubation of plants. The paper portrays the process, from research, analysis, formulation of the idea to the design, development and testing of a minimum viable proof of concept prototype of the “Vereatable” solution. © 2019, Springer Nature Switzerland AG.

Abstract
This paper reports the collaborative learning experience of a team of five Erasmus students who participated in EPS@ISEP—the European Project Semester (EPS) at Instituto Superior de Engenharia do Porto (ISEP)—during the spring of 2018. EPS@ISEP is a project-based learning capstone programme for third and fourth year engineering, product design and business students, focussing on teamwork and multidisciplinary problem solving as well as on the development of sustainable and ethical practices. In this context, the Team developed a drifting intelligent buoy to monitor the water quality of urban water spaces. Motivated by the desire to build an intelligent buoy for urban water bodies, the Team conducted several scientific, technical, sustainability, marketing, ethical and deontological analyses. Based on the findings, it has derived the requirements, designed the structure and functional system, selected the list of components and providers and assembled a proof of concept prototype. The result is Aquality, an intelligent drifting buoy prototype, designed for private sustainable pools. Aquality monitors the quality of the pool water by measuring its temperature and turbidity, while interfacing with the user through a mobile application. Considering the EPS@ISEP learning experience, the Team valued the knowledge and skills acquired, and, particularly, the collaborative learning and working component of the project, i.e., working together towards one goal while maintaining high motivation and cohesion. © 2019, Springer Nature Switzerland AG.

Abstract
This paper describes the development of a Multi-purpose Urban Sensing Equipment, named Billy, designed by a multinational and multidisciplinary team enrolled in the European Project Semester (EPS) at Instituto Superior de Engenharia do Porto (ISEP). The project is set to design, develop and test an interactive billboard in compliance with the relevant EU regulation and the allocated budget. The Team benefited from the different background, multidisciplinary skills and the newly acquired skills of the members, like marketing, sustainability and design ethics, in activities both inside and outside of the University. The challenge was to design a multi-purpose urban sensing and displaying equipment to inform citizens of nearby environmental conditions. The Team decided to design a system to monitor and display the temperature, humidity, air pressure and air quality of leisure areas, featured with a proximity detection sensor for energy saving. Billy will not only monitor and display this local information, but also the air quality determined by other billboards placed in other locations, creating a distributed urban sensing network. The system has been successfully prototyped and tested using the ESPduino Wi-Fi enabled micro-controller, different sensors and displays (screen and map-based). The results show not only that the prototype functions according to derived specifications and design, but that the team members were able to learn, together and from each other, how to solve this multidisciplinary problem. © 2019, Springer Nature Switzerland AG.