ResumoNa adolescência, a interação entre adolescentes e pais assume uma nova dimensão. A busca pela autonomia, a construção da identidade e os pares adquirem grande importância. Acresce que o desenvolvimento e utilização de tecnologias, sendo estas necessárias às rotinas das pessoas, tornaram-se suscetíveis de influenciar a interação familiar, particularmente, a comunicação. Mediante estudo qualitativo e realização de entrevista semiestruturada analisou-se a influência das tecnologias na comunicação em famílias com adolescentes. Participaram no estudo 13 mães e respetivos filhos/as. Dos dados sujeitos a análise de conteúdo concluiu-se que as tecnologias influenciam a comunicação entre mães e adolescentes, facilitando-a ou dificultando-a. Palavras-chave: interação familiar, adolescência, comunicação, tecnologia. AbstractIn adolescence, the interaction between adolescents and parents assumes a new dimension. The pursuit of autonomy, the self-identity development and the peers acquire a great importance. Furthermore, the increasingly development and widespread use of technologies, which are necessary to people's dailylife routine, became susceptible to influence family interaction, particularly, communication. Through a qualitative study and a semistructured interview, the influence of technologies in family communication in families with adolescents was analyzed. Thirteen mothers and their offspring participated in the study. From the data subjected to content analysis, it was concluded that technologies do influence communication between mothers and adolescents, whether facilitating or hindering it.

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This work responds to the gap in integrating the Internet-of-Things in Continuous Improvement processes, especially to facilitate diagnosis and problem-solving activities regarding manufacturing workstations. An innovative approach, named Automatic Detailed Diagnosis (ADD), is proposed: a non-intrusive, easy-to-install and use, low-cost and flexible system based on industrial Internet-of-Things platforms and devices. The ADD requirements and architecture were systematized from the Continuous Improvement knowledge field, and with the help of Lean Manufacturing professionals. The developed ADD concept is composed of a network of low-power devices with a variety of sensors. Colored light and vibration sensors are used to monitor equipment status, and Bluetooth low-energy and time-of-flight sensors monitor operators’ movements and tasks. A cloud-based platform receives and stores the collected data. That information is retrieved by an application that builds a detailed report on operator–machine interaction. The ADD prototype was tested in a case study carried out in a mold-making company. The ADD was able to detect time performance with an accuracy between 89% and 96%, involving uptime, micro-stops, and setups. In addition, these states were correlated with the operators’ movements and actions.