Abstract
Fertilization is paramount for agriculture productivity and food security. Plant nutrition pre-established recipes and nutrient uptake are rarely managed by changing the fertilizer composition at the different stages of the plant life cycle. Herein we perform a literature review analysis - since the year 2000 and onwards - of the state-of-the-art capabilities of Nitrogen, Phosphorous, and Potassium (NPK) sensors for liquid fertilizers ( e.g. , hydroponics). From the initial search hits of 1660 results, only 53 publications had relevant information for this topic; from these, only 9 had NPK quantitative information. Qualitative analysis was performed by determining the number of publications for each nutrient, according to sample complexity and existing single, multiplexed or hybrid technologies. Quantitative assessment was performed by extracting the bias and linearity, the limit of detection and concentration ranges of sensor operation, framed into the context of the sensor technology development stage and sample compositional complexity. The most common technologies are colorimetry, ionselective electrodes, optrodes, chemosensors, and optical spectroscopy. The most abundant technologies are for nitrate quantification, from which ion-selective electrodes are the most widely used technology, and sensors for phosphate quantification are the less developed. Most are at low technological levels of development, not dealing with the complexity of agriculture samples due to matrix effects and interference. Measuring the fertilizer composition, nutrient uptake, the state of the chemical network, and controlling the release of nutrients using new functional materials, is one of the most important challenges ahead for the existence of precision fertilization. Intelligent sensing and smart materials are today the most successful strategy for dealing with matrix effects and interferences, being led by ion-selective electrodes and spectroscopy technologies.

Abstract
Job shop scheduling problems are common in the engineering field. In spite of some approaches consider just the most important objective to optimize, several other conflicting criteria are also important. Multi-objective optimization algorithms can be used to solve these problems optimizing, simultaneously, two or more objectives. However, when the number of objectives increases, the problems become more challenging. This paper presents the results of the optimization of a set of job shop scheduling with unrelated parallel machines and sequence-dependent setup times, using the NSGA-III. Several instances with different sizes in terms of number of jobs and machines are considered. The goal is to assign jobs to machines in order to simultaneously minimize the maximum job completion time (makespan), the average job completion time and the standard deviation of the job completion time. These results are analysed and confirm the validity and highlight the advantages of this approach.

Abstract
Diabetes, a chronic condition affecting millions of people, requires ongoing medical care and treatment, which can place a significant financial burden on society, directly and indirectly. In this paper we propose a vision-robotics system for the automatic assessment of the diabetic foot, one the exams used for the disease management. We present and discuss various computer vision techniques that can support the core operation of the system. U-Net and Segnet, two popular convolutional network architectures for image segmentation are applied in the current case. Hardcoded and machine learning pipelines are explained and compared using different metrics and scenarios. The obtained results show the advantages of the machine learning approach but also point to the importance of hard coded rules, especially when well know areas, such as the human foot, are the systems’ target. Overall, the system achieved very good results, paving the way to a fully automated clinical system.

Abstract
Involving people in urban planning offers many benefits, but current methods are failing to get a large number of citizens to participate. People have a high participation barrier when it comes to public participation in urban planning - as it requires a lot of time and initiative, only a small non-diverse group of citizens take part in governmental initiatives. In this paper, a product is developed to make it as easy as possible for citizens to get involved in construction projects in their community at an early stage. As a solution, a public screen is proposed, which offers citizens the opportunity to receive information, view 3D models, vote and comment at the site of the construction project via smartphone - the solution was named Parcitypate. To explain the functions of the product, a prototype was created and tested. In addition, concepts for branding, marketing, ethics, and sustainability are presented.

Abstract
Mild is a smart stress relief solution created by DSTRS, an European Project Semester student team enrolled at the Instituto Superior de Engenharia do Porto in the spring of 2022. This paper details the research performed, concerning ethics, marketing, sustainability and state-of-the-art, the ideas, concept and design pursued, and the prototype assembled and tested by DSTRS. The designed kit comprises a bracelet, pair of earphones with case, and a mobile app. The bracelet reads the user heart beat and temperature to automatically detect early stress signs. The case and mobile app command the earphones to play sounds based on the user readings or on user demand. Moreover, the case includes a tactile distractor, a scent diffuser and vibrates. This innovative multi-sensory output, combining auditory, olfactory, tactile and vestibular stimulus, intends to sooth the user.

Abstract
Small living spaces require ingenious solutions that are functional, ergonomic and, above all, reconfigurable. This project for smart, ergonomic and adjustable furniture was embraced by a team of students from different countries, universities and study areas enrolled in the European Project Semester (EPS) at Instituto Superior de Engenharia do Porto (ISEP). EPS is a design project where international students work in teams to create a solution to a real problem from scratch, analysing the state of the art, the market and the associated ethical and sustainability issues. As a project-based learning process, EPS aims to prepare engineering students to work together in multidisciplinary teams, develop personal skills and address the challenges of the contemporary world. The current project aims to design, simulate and test an ethically and sustainability-driven safe and transformable furniture. Amplea is the adjustable furniture solution developed by five EPS students in spring 2023. It transforms into a kitchen counter, dining table or standing desk. By transforming easily, Amplea’s design provides more comfort and saves space in small living spaces. This paper summarises the research, the design of the solution and the development and testing of the proof-of-concept prototype. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.