Technology can influence the reduction of operational costs, quality control, increase scale or can be a competitive advantage for industry. It influences industry structural changes and could create new industries. On the other hand, without enough investments it can limit the growth of an industrial sector. Therefore, a systemic understanding of the technological scenario is necessary. Several organizations have implemented Technology Surveillance systems (TS) to execute structured processes in order to identify and monitor technologies from formal sources of information, such as scientific articles and patents. However, with the ever smaller cycles of technological innovation and an unprecedented volume of information passing through different digital channels, like portals, specialized databases and social networks, the technological monitoring has become a challenge, especially with the current Big Data scenarios. This work presents a conceptual model and architecture for technology surveillance automated systems from web portals and social networks sources. The model is divided into four key modules (collection, preparation, analysis and diffusion) and two auxiliary ones (parameterization and persistence). To evaluate this approach a case study was carried out in which a computer system prototype was developed and implemented in an organization. The results demonstrated its feasibility and the developed system is still in use today.

技术可以影响运营成本的降低，质量控制，规模的扩大，或者可以成为行业的竞争优势。它影响着产业结构的变化，并可能创造新的产业。另一方面，如果没有足够的投资，它将限制工业部门的增长。因此，必须对技术方案有系统的了解。一些组织已经实施了技术监视系统（TS）来执行结构化的过程，以便从诸如科学文章和专利之类的正式信息源中识别和监视技术。但是，随着技术创新周期越来越短，以及通过门户，专业数据库和社交网络等不同数字渠道传递的信息量空前，技术监控已成为一项挑战，尤其是在当前的大数据场景下。这项工作提出了来自门户网站和社交网络源的技术监视自动化系统的概念模型和体系结构。该模型分为四个关键模块（收集，准备，分析和扩散）和两个辅助模块（参数化和持久性）。为了评估这种方法，进行了案例研究，其中开发了计算机系统原型并在组织中实施。结果证明了其可行性，并且所开发的系统仍在使用中。该模型分为四个关键模块（收集，准备，分析和扩散）和两个辅助模块（参数化和持久性）。为了评估这种方法，进行了案例研究，其中开发了计算机系统原型并在组织中实施。结果证明了其可行性，并且所开发的系统仍在使用中。该模型分为四个关键模块（收集，准备，分析和扩散）和两个辅助模块（参数化和持久性）。为了评估这种方法，进行了案例研究，其中开发了计算机系统原型并在组织中实施。结果证明了其可行性，并且所开发的系统仍在使用中。