Cuerva Distribution needed to have real-time data (<1 minute) from the line cells of its substations and fault detectors in order to obtain instant alerts regarding supply quality: surges or drops in voltages or intensity, neutral currents, etc. Traditionally, all these data are processed through SCADA, a rather rigid system which does not allow for custom events and alarms to be configured. Due to software limitations, it took around 15 minutes for the data to transfer from SCADA to a database.

An enterprise security client wanted to develop a security product to address decentralized IoT security. Numerous reports and articles have been written on the security vulnerability of Industrial Internet of Things (IoT), smart cities, smart buildings, smart home automation, and healthcare. The standard best practices and solutions for cloud security and application security do not adequately address the specific nuances of the Internet of Things, especially for edge-to-edge computing and networking.

Solution approach for monitoring production-critical ultrapure water valves with the aim of detecting possible failures at an early stage and better planning maintenance processes.

Edge computing and edge intelligence shifts data processing, computing applications, and services away from centralized cloud based servers to the edges of a network. This enables analytics to occur at the source of the data where it can trigger events in real time, without time delays as data moved between cloud servers. Existing cloud-based technologies do not solve problems of data analytics, software deployment, or updates and security for remote devices. Edge or Fog Computing solves the problem of managing large amounts of machine-generated data by processing data at the edge of the network and converting it into actionable, useful business information. Software can be deployed at various points in the network to not only automate monitoring and control, but also to apply embedded intelligent agents that can adjust device behaviors in relation to ongoing performance variables, thereby reducing running costs by reducing power consumption during off-cycles, or even detecting imminent failures and notifying technicians to perform preventative maintenance. Edge Computing also allows remote software deployment and secure M2M communication. Edge Computing leverages resources that are not continuously connected to a network, such as laptops, smartphones, tablets, and sensors. It covers a wide range of technologies, from Wireless Sensor Networks and mobile data acquisition to cooperative distributed peer-to-peer ad hoc networking and processing.