Abstract
This paper describes the journey of a multinational and multidisciplinary team enrolled in the European Project Semester (EPS) at the Instituto Superior de Engenharia do Porto (ISEP) during the spring semester of 2019. The team embraced the idea of repurposing coffee leftovers to cultivate oyster mushrooms and benefited from the background diversity of the team members as well as from newly acquired marketing, sustainability and design ethics skills to consolidate and strengthen the overall feasibility of the project. The project was set to design, develop and test grey oyster mushroom growth kits with an automated monitoring system, using coffee grounds as growing substrate and complying with the applicable regulations and pre-defined requirements. The ulterior aims of the project were to reconnect people with the food they eat and to disseminate sustainable food production processes, which are not only healthy but environmentally friendly. To achieve these goals, the team developed a circular economy business model where grey oyster mushroom growth kits reuse coffee grounds as growing beds and food buckets as containers. The designed growth kits include a controlled fruiting chamber with an integrated monitoring system. This allows easy domestic cultivation, monitoring through a smart phone. Moreover, the proposed solution contemplates information sharing on the mushroom cultivation process, monitoring system and recipes as well as the maintenance of a dedicated discussion forum. Tests have been conducted to test the concept, cultivation process, monitoring system and fruiting chamber from the incubation of mycelium all the way to the harvesting. Results show the feasibility of creating a business based on the devised concept. © 2019 ACM.

Abstract
This paper provides an overview of the development of a solar dehydrator, a project undertaken by a team of six Erasmus students from different countries during the European Project Semester at the Instituto Superior de Engenharia do Porto in the spring of 2019. The main objective of the European Project Semester is to develop teamwork, communication and problem-solving skills through team work and project-based learning. The purpose of the project was to design a sustainable solution to dehydrate and preserve food, build and test the corresponding proof-of-concept prototype, while respecting requirements such as the budget, the use of reusable materials and components or European Union directives. To achieve this goal, the team considered the technological, ethical and deontological, economic and environmental perspectives in the design of the Dryfoo prototype. This paper describes, after a short introduction, the performed research, the development and the testing of the proof-of-concept prototype, as well as the personal outcomes of this learning experience.

Abstract
Tourism crowdsourcing platforms accumulate and use large volumes of feedback data on tourism-related services to provide personalized recommendations with high impact on future tourist behavior. Typically, these recommendation engines build individual tourist profiles and suggest hotels, restaurants, attractions or routes based on the shared ratings, reviews, photos, videos or likes. Due to the dynamic nature of this scenario, where the crowd produces a continuous stream of events, we have been exploring stream-based recommendation methods, using stochastic gradient descent (SGD), to incrementally update the prediction models and post-filters to reduce the search space and improve the recommendation accuracy. In this context, we offer an update and comment on our previous article (Veloso et al., 2019a) by providing a recent literature review and identifying the challenges laying ahead concerning the online recommendation of tourism resources supported by crowdsourced data.

Abstract
Ocean exploration and monitoring with autonomous platforms can provide researchers and decision makers with valuable data, trends and insights into the largest ecosystem on Earth. Regardless of the recognition of the importance of such platforms in this scenario, their design and development remains an open challenge. In particular, energy efficiency, control and robustness are major concerns with implications in terms of autonomy and sustainability. Wingsails allow autonomous boats to navigate with increased autonomy, due to lower power consumption, and greater robustness, due to simpler control. Within the scope of a project that addresses the design, development and deployment of a rigid wing autonomous sailboat to perform long term missions in the ocean, this paper summarises the general principles for airfoil selection and wingsail design in robotic sailing, and are given some insights on how these aspects influence the autonomous sailboat being developed by the authors.

Abstract
This paper describes the design and development of a Smart Companion Pillow, named bGuard, designed by a multinational and multidisciplinary team enrolled in the European Project Semester (EPS) at Instituto Superior de Engenharia do Porto (ISEP) in the spring of 2019. Nowadays, parents spend most of the day at work and become naturally worried about the well-being of their young children, specially babies. The aim of bGuard is to provide a 24-hour remotely accessible baby monitoring service, contributing to reduce parenting stress. The team, based on the survey of related products, as well as on marketing, sustainability, ethics and deontology analyses, developed a remotely interactive Smart Companion Pillow to monitor the baby's health and room air quality. The collected data, once it is saved on an Internet of Things (IoT) platform, becomes remotely accessible. The bGuard pillow, thanks to its shape, reduces the risk of the baby rolling from back to tummy, lowering the risk of Sudden Infant Death Syndrome (SIDS).

Abstract
Wiki-based crowdsourced data sources generally lack reliability, as their provenance is not intrinsically marshalled. By using recommendation, one may arguably assess the reliability of wiki-based repositories in order to identify the most interesting articles for a given domain. In this commentary, we explore current trends in scalable modelling and recommendation methods based on side information such as the quality and popularity of wiki articles. The systematic parallelization of such profiling and recommendation algorithms allows the concurrent processing of distributed crowdsourced Wikidata repositories. These algorithms, which perform incremental updating, need further research to improve the performance and generate up-to-date high-quality recommendations. This article builds upon our previous work (Leal et al., 2019) by extending the literature review and identifying important trends and challenges pertaining to crowdsourcing platforms, particularly those of Wikidata provenance.