Intelligent Façade Skinning System Based on Crowd-Sensing and Air-Quality Monitoring

In this paper, a real-time testbed for a cognitive morphing façade is proposed based on crowd-sensing and air-quality monitoring. It is one of the smart systems that employ the concept of the Internet of Things (IoT). Sensor nodes are used to connect the entire physical infrastructure with intelligent technologies for monitoring and control purposes. The proposed system includes two types of IoT nodes: indoor sensor node and outdoor actuator node. The environmental sensing and remote actuation algorithm (ESRAA) is proposed to enable the building to breathe like a lung. While the intelligent façade skinning system (IFSS) operates as “muscles” allowing the buildings to place their profiles into the required configuration. In other words, the façade of the building can be transformed by learning the indoor environment according to indoor air-quality standards. An artificial neural network (ANN)-based model is developed to classify the indoor air-quality and morph the building facade according to various conditions. The obtained results showed that the developed ANN model successfully classified the air-quality with an accuracy of 100% when utilizing an exhaustive search (ES) algorithm to select the optimum number of neurons in the hidden layer of the introduced ANN model.