Abstract
Communication between the different actors present in the school ecosystem is an essential issue. However, in a busy world where parents do not have much time to visit schools regularly, it is crucial to create mechanisms to better monitor student success and school demands. The current pandemic situation caused by the coronavirus has highlighted the role that technologies have in supporting the mission of schools and communication between the various school actors. The interaction between school, students and parents presents a growing and complex challenge. Technology has, in recent years, shaped the concepts of support and monitoring of learning - at school and outside it - as well as the way in which information flows between all actors in the school ecosystem. Emergently, the evolution of mobile applications, combined with the evolution of the capabilities of mobile devices, has enabled the creation of new and more effective intercommunication mechanisms, with ubiquitous approaches and in a predictable scenario of less willingness for physical interaction of the different actors. Based on these premises, this article reflects on the potential of mobile devices and their applications to support new models of intercommunication between parents or school sponsors, students and teachers. In this sense, a conceptual model is proposed that represents a work in progress that aims at creating and evaluating a prototype system capable of improving intercommunication and the overall success of the societal challenges of the school learning system.

Abstract

Abstract
Analyzing the persistence of the innovative activities can improve the understanding of firm dynamics, forecast the effectiveness of different policy actions, reinforce innovation cycles and promote sustainable and responsible innovation ecosystems. Innovation persistence was empirically analyzed for innovation leaders or even followers; still the literature fails to provide evidence for moderate innovators. The present article appraises the innovative strategy of firms operating in this context and their attitudes towards persistence, controlling for firm characteristics such as size, sector, R&D exenditures and human capital intensity. To do so, a balanced panel was built, encompassing three waves of the Portuguese Community Innovation Survey (CIS), (2004 to 2010) including 1099 firms from different areas. The estimation of the random effects probit model, evidenced that persistence hypothesis fails to be corroborated, evidencing no time dependent innovation strategies. Such result suggests that innovation policy programs do not have long-lasting effect on innovative behavior of firms and it is unlikely that incumbent past innovators be the drivers of creative accumulation and future innovation. There is, however, some evidence that new, smaller, innovators might lead the creative wave. In this vein, there might be a rational to encourage public policies targeting start-up firms and new market entrants when innovation is the main primary funding goal. © 2020 Society of Sytematic Innovation.

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
In a context of greater complexity of Smart Factories, the commissioning time for automated systems needs to be shortened. The use of virtual commissioning tools is a good contribution to achieve this goal. Ideally, those tools should be part of a virtual engineering environment sharing same virtual model, the digital twin, through the complete lifecycle of the automated system, namely the project, simulation, implementation and execution/monitoring/supervision and, eventually decommissioning phases. Such vision includes a digital twin with a broader use, which is consistent with the real system and one that can be used after the early design and commissioning phases. Finding a complete set of tools able to comply with the above requirements can be extremely challenging. In this paper we explore the use of the ABB RobotStudio software combined with the OPC UA standard with this vision in mind. Methodologies were defined to integrate both new generation and legacy equipment, as well as robot controllers and guidelines for equipment development. A key result of this work is the development of a set of virtual engineering tools and methodologies based on OPC UA and implemented using RobotStudio in order to accomplish the complete lifecycle support of an automated system, from the project and simulation phases, to the monitoring and supervision phases, suitable for integration in Industry 4.0 factories. Results are described for a test scenario with different devices.

Abstract
Intelligent agriculture in general, but especially when agricultural fields are very heterogeneous, requires a large number of sensors in order to obtain an effective control and thus increase productivity. This need becomes more evident in vineyards on the farms of the demarcated Douro region due to the specificities of the territory and the vineyards themselves. Thus, it is necessary to have low cost sensors which are, essentially, easy to install and maintain. In the present work, a node with these characteristics was developed, which, in addition, is low consumption and communicates wirelessly through a Long Rang Wide Area Network (LoRaWAN) network. To obtain an easy installation, a library of clusters was created for the LoRaWAN network and dedicated to sensors used in agriculture, especially those using an asynchronous serial protocol for intelligent sensors. Three nodes were developed and tested with sensors used in agriculture to measure several environmental parameters (soil and air temperature; wind speed, gust and direction; soil water content, water tension and electrical conductivity; solar radiation; precipitation; atmospheric and vapor pressure; relative humidity; and lightning strikes count). The three nodes send data to a server through an existing gateway on the farm. The data are decoded and sent to an Internet-of-Things analytics platform where it is aggregated, viewed and analyzed. Samples of the data collected are presented. The developed nodes are of small dimensions (85x65x35mm), thus making them easy to handle and install. Energy consumption depends on the distance to the gateway, and the number and type of sensors connected to each node. In the implemented cases, the maximum consumption was approximate to 400 mu A. The development of a cluster based library makes the node plug-and-play. The developed nodes will be a great step forward for the use of wireless sensors in smart agriculture in Douro vineyards.