Agile Methodologies and IoT, Internet of Things

Being agile in making decisions and implementing changes is essential for a company to be a leader in its sector. Decisions must be oriented towards continuous improvement, both in terms of cost reduction or increased efficiency, as well as innovation and the creation of new products to meet new market demand.

Agile methodologies take on a new meaning and dimension when applied to the foundations of IoT. The paradigm of continuous improvement is currently being imposed, the essence of which is that if you want to improve a parameter magnitude you have to measure it first, i.e.: you cannot improve what you cannot measure.

Industry 4.0 is a hyper-connected and sensorised industry where decisions can be made quickly.

What happens when you have many variables, measurements or history of these measurements?

How can we find patterns, deviations, correlations between these parameters?

How to measure quantities of different nature, with different protocols, on different machinery and in different locations?

How to visualise, interpret and analyse business variables with mechanical or social variables?

How do you make important decisions quickly based on what happens in your production?

What if you also want to know what is happening in the market to make that decision?

Nowadays, it is necessary to have mechanisms to help in this process of measurement and correlation. New technologies allow the replication and deployment of cost-effective sensors on a massive scale and the collection of information from different machines, tools and systems.

Today, we have the capacity and the technology to measure a wide range of variables and parameters.

Not only is it possible to measure these quantities, but we can also collect them digitally, process them automatically, translate them into a common language and transmit them securely.

ELLIOT acts as the brain of the system, as an umbrella that collects this data, and is able to correlate and determine the degree of ascendancy that some parameters have over others, as well as storing them and displaying the history in an agile way and analysing them using innovative Big Data, analytics, machine learning and artificial intelligence techniques. Thanks to these techniques, it will be possible to detect characteristics such as the seasonality of events and occurrences and it will also be possible to define alerts that will launch orders to activate mechanisms and action protocols, among others.

ELLIOT. Open Source IOT middleware with high scalability and very fast integration and with the ability to connect to any existing sensor, device, machine or data source for data extraction.

It enables real-time data management with high variability over time and advanced analytics using technologies such as Big Data and AI.


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