Abstract
Much effort is put into Information Technology (IT) to achieve better efficiency and quality of expressing communication between autistic children with the surrounding. This paper presents an application that aims to help the autistic child to interact and express their feeling with their loved ones in easy manner. The major objective of the project is to connect autistic children with their family and friends by providing tools that enable an easy way to express their feeling and emotions. To accomplish this goal an Android app has been developed through which, autistic child can express their emotion based on emoji. Child’s emotions are share by sending the emoji to their relatives. The project aims a high impact within the autistic child community by providing a mechanism to share emotions in an “emotionless world”. The project was developed under the Sustainable Development Goal (SDG) 3: good health and well-being in the society by making the meaningful impact in the life of autistic child. © 2019, Springer Nature Switzerland AG.

Abstract

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
The capability of drones to perform autonomous missions has led retail companies to use them for deliveries, saving time and human resources. In these services, the delivery depends on the Global Positioning System (GPS) to define an approximate landing point. However, the landscape can interfere with the satellite signal (e.g., tall buildings), reducing the accuracy of this approach. Changes in the environment can also invalidate the security of a previously defined landing site (e.g., irregular terrain, swimming pool). Therefore, the main goal of this work is to improve the process of goods delivery using drones, focusing on the detection of the potential receiver. We developed a solution that has been improved along its iterative assessment composed of five test scenarios. The built prototype complements the GPS through Computer Vision (CV) algorithms, based on Convolutional Neural Networks (CNN), running in a Raspberry Pi 3 with a Pi NoIR Camera (i.e., No InfraRed-without infrared filter). The experiments were performed with the models Single Shot Detector (SSD) MobileNet-V2, and SSDLite-MobileNet-V2. The best results were obtained in the afternoon, with the SSDLite architecture, for distances and heights between 2.5-10 m, with recalls from 59%-76%. The results confirm that a low computing power and cost-effective system can perform aerial human detection, estimating the landing position without an additional visual marker.

Abstract
The great potential of Unmanned Vehicles (UV) for services is supported by the evolution of drones and their flexible ability to help us performing dangerous, boring and difficult tasks. The common communication solutions e.g., radio, consider a pilot and a vehicle in the same location. Besides, the alternatives based on Ground Control Stations (GCS) are difficult to configure, which makes it difficult for a common user and a developer to use and/or implement new services for drones. This work proposes a solution with a new messaging protocol to overcome the previous problems, allowing controlling a UV in a remote location after a simple configuration. The implementation of this approach is based on a cloud platform, responsible for UV and user management, and on TCP/IP WebSockets for the user to control remotely located vehicles, anytime and anywhere. This research starts with the analysis of the prior work regarding UV communication technologies and the available GCS. Minding the identified problems, we designed an architecture that represents a cloud platform and multiple users and UVs in different networks. To prototype this architecture, we developed the user interface, the platform and the UV control module. The functional assessment considers a generic simplified and controlled scenario, focusing on the real-time control and video stream. The results confirmed the possibility to control a UV in a different location, in real-time, with an average response time of 25ms. This work provides valuable insights regarding the communication in the fields of anytime and anywhere device control and vehicle-based services.

Abstract
In this paper, we aimed at exploring the use of iconographic navigation to support inclusive and accessible search for Web content through an extension for Google Chrome browser, entitled Extension Icon. Despite Extension Icon was developed to be a solution that allows people with intellectual disabilities to search autonomously using an iconographic navigation, supported by platforms as Vimeo and YouTube, it intends to be an accessible solution for ALL users. Through participatory design, the solution was iteratively developed and with the outcomes it was obtained two versions of this solution. Therefore, in this paper we described the design, implementation and assessment of two Extension Icon versions. Specifically, twenty-eight participants were invited - 18 people with intellectual disabilities and 10 people without of disability - in order to evaluate and participated in the iterative development of the solution. The user preliminary feedbacks showed a major concern regarding the graphical interface therefore it was redesigned to improve and present a more appealing interface. Overall, user tests carried out with the two versions showed and effective, efficient and satisfactory user interaction. © 2020, Springer Nature Switzerland AG.