This paper traces the expansion of a network of IoT sensors to improve the effectiveness of a centralised control room in Brazil in anticipating natural hazards. This centralised model relies on using IoT data by highly qualified experts replacing previous smaller local structures. We draw on the notion of Situational Awareness to carry out the study. Results show that although the operators were not always familiar with the characteristics of locations, the use of IoT data heightened their situational awareness in the centralised control room by improving perception and comprehension. However, they still relied on local knowledge and learned experiences to support projection and anticipation of risks. The study highlights that although data analytics systems are capable of expanding operators’ perception of local elements, they must be complemented by local richer forms of information, needed to anticipate risks and make critical decisions with major impact on local population.

本文追踪了物联网传感器网络的扩展，以提高巴西中央控制室在预测自然灾害方面的有效性。这种集中式模型依靠高素质的专家使用IoT数据来代替以前的较小本地结构。我们利用情境意识的概念来进行研究。结果表明，尽管运营商并不总是熟悉位置的特征，但物联网数据的使用通过改善感知和理解能力，提高了他们在中央控制室中的态势感知能力。但是，他们仍然依靠当地的知识和经验来支持风险的预测和预测。该研究强调，尽管数据分析系统能够扩展运营商对本地元素的理解，