From home to work and back again — when AI is all around us

Photo by Lukas on Unsplash

The world we live in is in the process of becoming smarter and smarter — at least it feels that way to a person living today. When people in 2100 look back to our present age, it’s very likely that they’ll say “it was just the beginning,” since the exponential growth of change is rushing forward, and no one can tell where it’s going to take us.

Nevertheless, today’s “smartification” is driving companies and their business models. In its basic meaning, the term “smart” is closely connected to intelligence. For someone (or something) to be perceived as smart, you would expect them to possess a certain minimum level of intelligence. Usually, intelligence is considered one prerequisite for being smart. Therefore, for a smart connected world, when things and objects become smart, we need non-human intelligence — artificial intelligence.

When a company like ours provides solutions for buildings, transportation, factories and many other applications where wires are connected, and where lighting, HVAC, control cabinets and whole production lines are automated, AI is one of the “next big things” to consider. In a smart connected world, our homes, our workplaces and the whole city people live in will be smart.

When AI is orchestrating the framework, it starts with electricity

AI now not only offers several opportunities to be part of single solutions or elements in this smart connected world, but can also be an important factor in shaping the whole big picture. Starting with the energy that runs this world, power grids and the energy infrastructure are hoping that AI will help in solving central problems.

With renewable energy sources like wind and solar power, very often the peaks of energy supply do not match the peaks of energy demand, as the basic day-and-night rhythm disperses supply and demand. The idea behind smart grids is to address this problem and is part of many current discussions. Combining the storage, transport and allocation of energy is a challenge that fits perfectly with the strengths of algorithms and machine learning. Recognizing multi-layer patterns within energy consumption throughout the day and between local hot spots, with fluctuating energy production throughout the day, depending on the weather as well as on local conditions, is crucial to success in smart grid design and execution. The solutions to these equations need the power of AI.

This power is enhanced even more when the intelligence becomes increasingly decentralized. We are working on putting intelligence into the control cabinet and even on the individual terminal blocks. If the terminal blocks and control cabinets can already detect abnormalities within the electrical current flow at the smallest unit (e.g. a single machine in a factory or lighting systems in buildings), the predictive and smart analytics of the whole system will benefit.

Photo by Marius Masalar on Unsplash

AI will soon be present at the workplaces of almost all professions

The smart grid is one of the foundational elements of a smart connected world, like harmonized transportation networks, where, e.g., autonomous Porsche cars are combined with public transportation solutions, steered by an AI-controlled system. On this foundation, people build their smart homes, as well as other functional buildings like offices or malls, and, of course, factories. We at WAGO focus on the latter two, functional buildings and factories, to improve the workplaces of both blue and white-collar workers with our solutions. Once again, AI is a promising stack of technology to deal with the challenges of modern buildings and factories.

For offices and public buildings, the parameters of lighting, HVAC, general energy consumption, elevator usage, and general traffic at entries and exits of the building and between floors are only some examples of all the data that can arise. Since data is the fuel of AI, and its performance heavily depends on the quality, frequency and amount of data, it is very important to gather all this information and combine it into one integrated system. Most of the parameters also can depend on user preferences.

Once again, recognizing patterns and optimizing the settings and resource consumption through smart and predictive/preventive management opens the door for AI and its learning algorithms. When your office knows in advance (e.g. due to an intelligent calendar link) which rooms are going to be used tomorrow by which persons, the system can customize a lot of settings in advance more sustainably. The same applies in factories: Some production lines (e.g. in the food industry) need special conditions of temperature, humidity and other variables.

Most of these vary during the day due to weather changes or machine heating. With AI that combines the sensors, machines, weather forecast data and production planning, a predictive climate control system can save a lot of money, when it elevates operations management from simple reactive measures to timely preventive and counteracts deviations from the desired values in advance in a more sustainable way. We support building and factory owners and their users with automation solutions for a smart building and factory management.

Photo by chuttersnap on Unsplash

For example, together with the startup Othermo GmbH, we won the hackathon at the last SPS IPC drives fair this November. The concept that won the prize was an intelligent solution for central heating units to give operators an overview, inform them promptly of incidents and recognize the optimization potential of the plants. The role of AI in this context covers exactly the above-mentioned optimization of a system that consists of several variables influencing heating demand and execution (e.g. current prices, number of people in an meeting vs. room size etc.). The intelligence basically forecast the optimal heating curve based on data patterns.

AI as your consultant and first contact person

As the world becomes more and more complex, all these solutions and offerings for customers need to stay understandable and simple. Therefore, the second big role that AI will play when it is all around us will be in the field of support and consulting. Besides being part of the product or the solution being sold to the customer, AI will be at our side (at home or the workplace) to provide help or answer questions.

The use of AI in support and customer interaction offers some promising examples. Google’s Alexa (and others) is the most obvious example from a B2C perspective. But many other options are imaginable. One of our focal topics, for example, is working on smart tools that will recognize products (e.g. inside a control cabinet) through video or photos to save customers the effort of searching when they need support, so that they can get direct information on their individual situation. Furthermore, (potential) mistakes can be prevented or detected while the solution is in place right in the customer’s environment. Intelligent consulting and support algorithms can respond 24/7 and will improve their performance with every case they deal with.

In summary, there are many ways AI can enhance the use and the variety of solutions that were originally offered by hardware products for automation and electrical interconnections (WAGO). The intelligence within an integrated, customer-specific solution, in combination with intelligence that enhances customer interaction and support, is one of the key cornerstones for future business models. What people are used to from their first smart homes or personalized content and suggestions on sales platforms is appearing in factory and office contexts.

Therefore, soon AI will be all around us, and companies like WAGO will provide the backbone for this dynamic system, since AI is fed by data and connectivity.

Christian Sallach, WAGO

This is a guest contribution by Christian Sallach, Chief Digital & Chief Marketing Officer at WAGO. To find out more about Porsche and Technology, follow us on Twitter, LinkedIn and Instagram.

--

--

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store