Grupo de Investigación Tecnologías para la Sociedad de la Información y el Conocimiento (T>SIC). Campus Sur, Universidad Politécnica de Madrid. Ctra. de Valencia Km. 7, 28031, Madrid, Spain.
Research Group INEXE: Inclusión y exclusión educativa [Inclusion and Exclusion in Education], Universidad Autónoma de Madrid, Cantoblanco. C/ Iván Pavlov 6, 28049, Madrid, Spain.
Sci Eng Ethics. 2018 Aug;24(4):1057-1076. doi: 10.1007/s11948-017-9951-x. Epub 2017 Aug 16.
EDUCERE (Ubiquitous Detection Ecosystem to Care and Early Stimulation for Children with Developmental Disorders) is a government funded research and development project. EDUCERE objectives are to investigate, develop, and evaluate innovative solutions for society to detect changes in psychomotor development through the natural interaction of children with toys and everyday objects, and perform stimulation and early attention activities in real environments such as home and school. In the EDUCERE project, an ethical impact assessment is carried out linked to a minors' data protection rights. Using a specific methodology, the project has achieved some promising results. These include use of a prototype of smart toys to detect development difficulties in children. In addition, privacy protection measures which take into account the security concerns of health data, have been proposed and applied. This latter security framework could be useful in other Internet of Things related projects. It consists of legal and technical measures. Special attention has been placed in the transformation of bulk data such as acceleration and jitter of toys into health data when patterns of atypical development are found. The article describes the different security profiles in which users are classified.
EDUCERE(普遍存在的发育障碍儿童护理和早期刺激检测生态系统)是一个政府资助的研究和开发项目。EDUCERE 的目标是通过儿童与玩具和日常用品的自然互动来检测心理运动发育变化,并在家庭和学校等真实环境中进行刺激和早期关注活动,从而为社会研究、开发和评估创新解决方案。在 EDUCERE 项目中,进行了一项与未成年人数据保护权利相关的伦理影响评估。该项目使用特定的方法,取得了一些有希望的结果。其中包括使用智能玩具原型来检测儿童的发育困难。此外,还提出并应用了隐私保护措施,这些措施考虑到了健康数据的安全问题。这个安全框架可以在其他与物联网相关的项目中使用。它由法律和技术措施组成。特别关注的是,当发现非典型发育模式时,如何将玩具的加速度和抖动等大量数据转化为健康数据。本文描述了对用户进行分类的不同安全配置文件。