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
The possibility to engage in autonomous flight through geolocation-based missions turns Unmanned Aerial Vehicles (UAV) into valuable tools that save time and resources in services like deliveries and surveillance. Amazon is already developing a drop-by delivery service, but there are limitations regarding the client’s id, that can be analyzed in three phases: the approach to the potential receiver, the authorization through the client id and the delivery itself. This work shows a solution for the first of these phases. Firstly, the receiver identifies the GPS coordinates where he wants to receive the package. The UAV flights to that place and tries to locate the receiver on the arrival through Computer Vision (CV) techniques, more precisely Deep Neural Networks (DNN), to continue to the next phase, the identification. After the proposal of the system’s architecture and the prototype’s implementation, a test scenario to analyze the feasibility of the proposed techniques was created. The results were quite good considering a system to look for one person in a limited area defined by the destination coordinates, confirming the detection of one person with an up to 92% accuracy from a 10 m height and 5 m horizontal distance in low resolution images. © Springer Nature Switzerland AG 2020.

Abstract
AppVox is a mobile application that provides support for children with speech and language impairments in their speech therapy sessions, while also allowing autonomous training at home. The application simulates a vocalizer with an audio stimulus feature, which can be used to train and amend the pronunciation of specific words through repetition. In this paper, we aim to present the development of the application as an assistive technology option, by adding new features to the vocalizer as well as assessing it as a usable option for daily training interaction for children with speech and language impairments. In this regard, we invited 15 children with speech and language impairments and 20 with no impairments to perform training activities with the application. Likewise, we asked three speech therapists and three usability experts to interact, assess, and give their feedback. In this assessment, we include the following parameters: successful conclusion of the training tasks (effectiveness); number of errors made, as well as number and type of difficulties found (efficiency); and the acceptance and level of comfort in completing the requested tasks (satisfaction). Overall, the results showed that children conclude the training tasks successfully and helped to improve their language and speech capabilities. Therapists and children gave positive feedback to the AppVox interface.

Abstract
The health centers group (ACES) "Douro Sul II" is creating a Community Support Team for Palliative Care (ECSCP) to provide palliative care services for the ACE's population of 73, 713 registered users. To support these services, a study was carried out and it was planned the development of an Information System (IS) with the main objective of monitoring patients from their homes, providing information to support the operations of the team. The system is based on a platform that controls the flow of information between coordinators, team and the patients, from the use of mobile and web applications. Therefore, the team will be able to respond more quickly to patients requiring support.

Abstract
The usage of unmanned vehicles for professional, recreational and healthy purposes has increased and is a huge signal of their advantages. Among other benefits, they reduce or even cancel the need of having human lives aboard, which means that there is no risk of injuries in dangerous tasks. Although, most of the time the users are near the vehicles, which cannot be possible nor proper for personal or security reasons. Therefore, it is proposed a software solution to allow users to control and monitor unmanned vehicles remotely in real-time just as if they were in the vehicles’ place. Then it follows an implementation to control and monitor remotely-piloted cars of different types. This solution has been applied to a real-case scenario for testing purposes and it has been concluded that the software architecture proposed can be generically applied to different kinds of vehicles with transparency to the users that are able to control, from everywhere and with their own personal devices, whatever vehicles they want. © Springer Nature Switzerland AG 2019.

Abstract
In this article, we present a solution for training the mouse input device handling, in order to improve the users' digital skills. Knowing that the widespread access to the computer and the Internet is still made by the use of traditional devices, such as, the keyboard and mouse device (and these devices does not provide natural interaction between people and technology), it is necessary to train for the correct handling. Specifically, mouse usage requires movement control, hand posture and finger positioning, as well as, precision clicks for different functions (one click, two clicks, drag and click) This training is often done in real interaction situations, that could led to inefficiency of use the digital environments and also user's frustration and discouragement. Thus, using simple and intuitive interfaces and providing a set of activities, we allow users to learn and train the motor coordination and basic movements with the mouse. The main results of the study showed that users had a pleasant experience of interaction, considered the interfaces intuitive and affirmed their availability to use it as a training tool.