The cities of our future could be designed and built by AIs and machine learning

Artificial Intelligence (AI) has been a major buzzword for quite some time — and for good reason. Using machine learning, AI can sort through large volumes of data, learning as they go, and ultimately carry out very complicated tasks in a fraction of the time it would take en entire department of humans.

Many people believe that AI and machine learning have the potential to change business — and perhaps even the rest of human society — forever.

Unsurprisingly, enterprises are already taking advantage of the benefits offered by AI, particularly through the use of machine learning and predictive analytics. In fact, 72% of business leaders have termed AI a ‘business advantage.’

What is surprising is that while only 33% of consumers believe they use AI-enabled technology, the actual figure of consumers using an AI-powered device is around 77%.

How is AI used in building and construction?

In comparison to other logistics-heavy sectors such as healthcare, banking, and finance (where AI is already dominant), the AI market in the building materials and construction space is still relatively small.

However, there are some notable applications for the technology in a number of different categories.

Planning and design

AI-powered architectural design programs are becoming an increasingly important feature of planning and design.

This technology gives professionals the insights they need to effectively design, plan, construct, and manage buildings and infrastructure.

For instance, AI-operated machinery can survey a building site and gather the necessary information required to produce 3D maps, blueprints, and construction plans in a fraction of the time it would take a human survey team.

As a result, a process that once took several weeks to complete can now be carried out in a single day.

Administration

AI can be used to control tasks and manage the overall project once it has begun.

For instance, if an employee becomes sick, they can input their sick days into the system and the AI will adapt the project accordingly and reallocate the task to another employee.

This means that overall project planning can be continuously updated and improved.

Post-construction

AI can also be used inside the structures once they have been built — regardless of their purpose.

For example, many homeowners have installed technology that allows them to control certain aspects of their home, such as the temperature, lighting, and audio-visual equipment, through voice commands.

Many hotels are also incorporating AI into their business models in order to improve their service ratings.

This year, Amazon launched an Alexa system for hotels that can be customized to include vital guest information, such as checkout time and pool opening hours. Alexa can also allows guests to request various services, such as room service.

Training and education

Image recognition software can analyze videos that have been collected on work sites and assess them to identify any unsafe worker behavior.

Organizations can then use this data to improve their training in the future and make workers aware of potential dangers.

AI is about to shake up the $600 billion construction industry

XMaterials has already taken things a step further than its competitors by leveraging machine learning technology to create brand new materials designed to be used as alternatives to the most common building materials we see today, such as concrete, granite, and marble.

XMaterials are already in production and have been proven to be stronger, more affordable, longer lasting, more eco-friendly, and faster to produce than the alternatives.

There are three separate components behind why XMaterials is so advanced:

DigiLab Makes AI-Generated Recipes

DigiLab ensures that locally sourced (and often recyclable) ingredients for XMaterials are mixed in an ideal ratio for the target material properties.

In other words, if you want a highly water-porous concrete alternative, Digilab will tell you what to buy and how, exactly, to mix it all together.

This allows users to customize XMaterials to their specific needs, using geo-navigational technology and a global database of 1,000 mines to find the best materials.

HyperCon Makes XMaterials a Reality Through Machine Learning

HyperCon uses the recipes generated by DigiLab to turn the concept XMaterial into a reality.

HyperCon is powered by DigiLab, and automates every part of the creation process, from mixing, to casting, to drying, to final control, to packing products. This drastically reduces labor costs and reduces human error.

The technology even analyzes product yield to improve recipes for future batches.

The Blueprint Establishes the Strategy, Methodology, and Equipment Needed

The Blueprint provides the exact specifications required for the machinery to operate — including the necessary positioning and modifications.

This is a necessary part of the XMaterials franchise model, which will allow businesses all over the world to create their own XMaterials with a very small margin of error.

The franchise model will work through the XMaterials token, known as XMAT. This is an ERC-20 token built on the Ethereum blockchain.

The future of the construction industry

The use of AI in the construction sector opens up a whole universe of new possibilities in a traditionally old-fashioned industry.

Even without franchising (which we’re also making available to our token holders), the XMaterials has already made about $2 million in its first six months of business.

With the global construction market set to grow to $8 trillion by 2030, propelled predominantly by China, the US, and India, the number of opportunities available seems endless.

Meanwhile, as time progresses and technology continues to improve, who knows what will be possible within the next five years?

If you’d like to learn more, please read the XMaterials whitepaper and join our Telegram group.