Implementation of fog computing for data pre-processing in an IoT and cloud computing scenario

Currently, Internet of Things (IoT) is a technological paradigm that is based on the collection of environmental data on a multitude of parameters (climatic, industrial, human, among others) through everyday objects to send it to higher instances such as data centers or cloud computing services, where it is processed and stored. Under this concept, despite the benefits of equipping any device with exceptional capacities, significant congestion is generated in the network as a result of an increasing number of connections. Consequently, fog computing emerges as a valid solution, since by performing local data pre-processing, the transmitted load is reduced. In addition, it grants the possibility of implementing adequate security measures, ensuring the veracity of the information. This research proposes the design of an IoT system for measuring environmental variables, consisting on a WSN, fog computing and cloud computing, which deploys end-to-end encryption techniques. Different tests are carried out, using the concept of living labs, reflected in a Web application that contemplates measurements of three indicators: carbon dioxide levels, polluting particles and environmental noise.