The increasing demographic density and evolution of technologies has led to new habits and ways of conceiving life. At the same time, there has been a parallel increase in energy demand due to its high involvement and relevance in the development and economic growth of our society. The direct effect of energy on productivity, health, education, supply, communication, among others, defines it as a fundamental factor.
It is clear that energy is an essential element, but its negative consequences such as: environmental deterioration, resource depletion and energy dependence, put energy efficiency alternatives and/or solutions in the spotlight.
New technologies are gaining prominence in the face of the alarming need to reduce gas emissions and the development of a more sustainable and ecological economic model. For this reason, companies and institutions are in the process of implementing technology such as Artificial Intelligence and Big Data to improve alternatives.
Energy opportunities
The industrial sector, as the main consumer of energy, seeks to achieve energy efficiency by collecting and visualising data to avoid wasting energy and make intelligent savings.
But what is energy efficiency? This is a term that can be applied both to energy consumption and to production processes, companies and institutions, value chains, etc. It consists of the application of technological solutions that, in addition to providing a competitive advantage, generate a positive impact: environmental, social and economic.
In short, it consists of reducing both energy losses and the consumption of energy and other raw materials, in this case, in production processes.
Artificial Intelligence thrives on Big Data
Without being aware of it, human beings are constant generators of information. Information which is collected and analysed by Big Data systems. This is capable of bringing together enormous amounts of data which interact with each other, and it is precisely the continuous increase in data and the speed of processing that is the trigger for Artificial Intelligence.
In other words, the use of information as a source of learning and its use for the development of solutions to mitigate and even prevent damage is what we now call Artificial Intelligence.
Within the discipline of Artificial Intelligence there are different types; Artificial intelligence, which makes it possible for a machine to simulate human reasoning; Machine Learning (ML) a subcategory of AI where humans prepare machines to recognise patterns based on data and thus make predictions and; Deep Learning (DL) a subcategory of Machine Learning where the machine is able to reason and learn from itself.
In short, the management and processing of massive data is a fundamental tool for companies that implement AI in their processes and seek to position themselves with a high level of competent analytics.
Artificial Intelligence and Big Data in industry
The industrial sector is focusing on the use of intelligent sensors to have a detailed view of each part of the production process, thus collecting data that is processed, stored and subsequently converted into qualitative information.
The use of Artificial Intelligence and Big Data has gained prominence thanks to its excellent application in energy management through data collection, analysis and autonomous optimisation.
- Process improvement and performance optimisation.
- Implementation of predictive maintenance systems that favour service improvement and cost savings.
- Process efficiency thanks to the flexibility and adaptability of working in the cloud.
- Fault alerts and rapid proactivity on production lines.
Its application in factories makes it possible to interpret the information generated and collected, from which algorithms are able to find optimal performance points both in the production area and in the control and administrative management units.
Smart buildings, not without AI and Big Data
The increase in energy demand in overpopulated countries and the scarcity of resources has led to new forms of development in cities, such as the provision of intelligent systems in buildings with the aim of obtaining greater efficiency and reducing environmental impact. This is what gives rise to the Smart Building concept, of which a Smart City or intelligent city is composed.
The implementation of technology to improve energy efficiency in cities is already a fact. Smart buildings collect, process and analyse thousands of data to efficiently manage energy resources and other supplies.
The application of high-impact technology is intended to generate new consumption habits, improve resource management and promote the use of renewable energies. In other words, the city’s infrastructures are adapted to environmental change.
Achieve high energy efficiency with Nexus Integra
Nexus Integra is the platform with which you can centralise your data, obtaining a single management framework and a 360º vision of your organisation. Nexus Integra helps you to reduce consumption and achieve energy efficiency in your building or industrial plant.
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