In this article we show the results of the application of an architecture based on Internet of things for the production of vermicompost through an interface that allows to monitor and collect temperature, humidity, and pH data through intelligent sensors that use the cloud computing service. The methodology used for the construction of the architecture was based on a search of the state of the art in open databases. For the implementation of the same, a pure experiment with a dependent variable and two independent ones was built. The results obtained by the measurements made during a period of four months, allowed to create grapHs where the constant temperature changes are observed in a range of 19 to 27 ° C, humidity in the range of 41% to 85% and the pH of 5 to 8.4 in the acid of the substrate. This information obtained in a ubiquitous way, helped the user to generate a weekly plan for irrigation, aeration, and mixing of the vermicompost, in order to reduce time, costs and human effort. It also helped maintain optimal environmental conditions for the reproduction of earthworms.

Cloud computing offers high server-level data processing capacity, while fog computing works using nodes at the edge of the network, enabling real-time data processing with low latency and improved ubiquity, so it can contribute on Industrial Internet of Things (IIoT) applications. This article discusses the technical challenges that have arisen in implementing the IIoT, and how the fog computing paradigm is helping to solve some of them. For this, a review of scientific articles in the Google Scholar and Web of Science databases has been carried out using keywords. The results show that there are various challenges related to interoperability, mixed criticality, latency, fault tolerance, scalability, horizontal and vertical integration, functional safety, legacy industrial systems, and energy efficiency. The main trends to face these challenges are reported. This article proposes a series of opportunity areas for research and development of possible solutions.