To celebrate the 100th edition of AEC Magazine Randall S. Newton explores what Architecture, Engineering and Construction technology might look like in 2036 when the 200th edition rolls off the virtual press
The year 2002 was an interesting one in AEC. In 2002 Autodesk surprised many in the architecture technology community by acquiring startup Revit Technology Corporation for $133 million. In 2002 a patent was issued for building a database of infrastructure assets using lidar. In 2002 vendors of wide-format printers generally rented the largest booths at AEC technology trade shows. In 2002 Bentley Systems was in the initial stages of introducing MicroStation V8. In 2002 the mention of “Robot” in AEC circles was about a brand of structural analysis software. In 2002 this magazine published its first issue.
So much new technology has been introduced in the 17 years since AEC Magazine Issue No. 1 rolled off the press. There were no smartphones, no tablets … mobile workstations in 2002 were bulky, and nothing like the lightweight laptops we have today. PDF was one of several competing standards for publishing AEC documents. Such technologies as 3D scanning, virtual reality, and decent photorealistic visualisation were years away. Many new technologies have been adopted by AEC, yet in many ways AEC has not changed as much as we might have predicted in 2002. Draughting is still more common than 3D modelling; printed documentation is still the norm; construction waste is still a major cost; production and construction workflows have not drastically changed.
To celebrate AEC Magazine Issue No. 100, we have asked industry technologists to cast their vision forward to 2036 — well beyond any vendor’s official roadmap — to when AEC Magazine Issue No. 200 will come out.
Understanding the drivers of change
“From a construction standpoint, 18 years is a relatively short time,” says Nathan King, Research Strategist at the Autodesk Build Space in Boston. “In the past 18 years there has been progress in construction, but not a lot.”
King believes it is important to examine the “drivers and demands” in order to understand what technology innovations will impact AEC. Demand for built infrastructure will increase in places which are the least developed today. It will be challenging to build in these areas, King says. “How do we realise the demand?
There will be shortages of materials and workers. Such a confluence of challenges presents an opportunity to accelerate adoption of technology in construction.” A “compression of adoption” mentality is required if AEC is to meet the challenges, King says. There will be a sharp increase in the use of off-site manufactured building components. “The trend will be toward more complexity in the factory to reduce time on site,” King says. Combining factory production with automation on site “solves issues like staging and sequential construction.”
Some of the required changes are not technological but social, King says. “One challenge is the segregation of the construction industry around trades and the ownership of responsibility. New technology allows us to break down these barriers.” There are “hundreds” of separate industrial processes in AEC, King notes; “we need to combine them around a common goal and a common platform to desegregate a segregated industry.”
Robotics will play a role in 2036, but more likely as exoskeletal devices to increase worker abilities, King says. “We will see a massive reduction of injuries onsite, due to better control, better tracking, and safer working methods. The trend is clear toward more robotics on site.”
AEC in the gig economy
The biggest technological changes in AEC by 2036 won’t be about specific applications like 3D printing or drone scanning, says Thomas Wendling of Jacobs Engineering. Instead, the most radical changes will be in business models. “Look at the platform revolution already taking shape around us,” Wendling says, citing a book of the same name. Companies like eBay. Amazon, Uber, and Airbnb “have learned to meet supply with demand resources external to them.” Companies will create software platforms offering two-sided markets for AEC services “for exchanging engineering knowledge in technical engineering memorandum format.” Such a service would allow his employer, for example, to reach out to external “and generally underutilised” talent.
Wendling says an AEC productivity platform could transform the creation, peer review, and approval of calculations, standard operating procedures, tender requests, and other elements of AEC design / build practice. Such micro contributions are too tedious to manage using existing practices, but could be automated using elements from social media and blockchain. “If you harness the distributed sources of knowledge, you gain. Today a 60 percent talent utilisation is considered standard. We think we can do better.”
Wendling leads the Blockchain Community of Practice at Jacobs, one of many internal think tanks inside the company. As part of an engineering services platform, blockchain would have several roles, which he describes as layers of management. “One layer would be generating tokens for credentials, reputation scores, quality scores, and curation,” says Wendling. “We believe blockchain can be the organisational structure for how knowledge is articulated.”
Wendling sees a second layer of BIM on a blockchain as the autonomous manager of the virtual job site, linked as a digital twin to the physical reality. “Everyone enters and leaves the virtual job site, and it is all recorded on the blockchain” during the design and engineering phases. Wendling says a wider circle of participants will interact with the developing digital model through virtual reality as the physical project takes shape. A third layer would issue and manage smart contracts for construction management. “The BIM layer would connect to this third layer through augmented reality at the actual job site,” says Wendling.
Digital Twins and smart goggles
Researchers at Bentley Systems are taking a look at how two of the technologies Wendling described – digital twins and augmented reality – will impact AEC. Adam Klatzkin imagines the day when “the combination of artificial intelligence and machine learning with digital twins will play a significant role in how physical assets are designed, built, and operated.”
As Bentley’s senior director for Infrastructure Digital Twins, Klatzkin says these technologies will provide the basis for profound advances in AEC practice. “These approaches are only as good as the data available for analysis,” he says. “With the increasing maturation of infrastructure digital twins and the aggregation of their data sets, future AEC professionals will derive real-time feedback and predictive insights such as cost, safety, and performance based on entire portfolios of assets – or even the digital twin of an entire city, state, or nation.”
“By accurately displaying CAD models and metadata in context, both indoors or outdoors, smart glasses will augment the built environment right before your eyes,” says Stéphane Côté, a Bentley research scientist. By 2036 such augmentation will include “IoT live data such as pressure and temperature, AI-powered analytics, hidden asset locations, maintenance history and schedules, assembly procedures, and hazardous areas perimeters.” Users of this smart technology will be able to make changes to designs on site using hand gestures, and get help from intelligent virtual assistants. “Colleagues will virtually teleport near you to help solve issues related to all aspects of the project.”
Real-time data for safety & efficiency
“We see a continued march toward safety and efficiency on site,” says Andy Evans, the product manager for mass data capture at Topcon Positioning. “We expect automated construction sites will be mainstream by 2036.”
Robots will play a major role in construction site automation, Evans believes. “Robots will be reducing the risk to life on site by removing the need for bodies near machinery. Constant positioning and verification will mean projects are completed within the swiftest of timescales.”
Data will be gathered from every direction and used immediately, Evans says. “The Internet of Things will provide us with a truly connected construction site – from planning to long term management. Embedded sensors and software to monitor use of infrastructure assets will feed into a digital twin of a project. Ultimately, smart cities will become a reality as we embrace this type of technology. Data across an entire urban environment can be used to inform projects.”
AI at the job site and in the building
Artificial intelligence (AI), 5G cellular data transmission, and edge computing are buzzword technologies today that will have a huge impact on AEC by 2036, according to Hexagon Chief Technology Officer Claudio Simao. “Process optimisation is the holy grail,” notes Simao. With its roots in metrology for manufacturing and site data for construction, Hexagon is focusing its research on using AI to simplify the complex processes required to use sensor data in real time. The goal is “hyper-connectivity” that starts with data gathered on-site. Edge computing – a distributed computing vision that decentralises data processing to smart devices in the field – will be where AI routines start to make sense of the local sensor data. High bandwidth in the field will be ubiquitous thanks to 5G cellular technology (or its replacement by 2036) allowing distributed use of the data for many purposes in real time. “Edge computing goes straight to distribution of applications,” says Simao.
“AI-driven analytics and positioning modelling” will allow multiple innovations to flourish on the job site, from self-driving equipment to site-aware robotic welders and fastening specialists who can adjust their work without direct human input using constantly updated site data. These devices will have embedded AI technology so the computation driving the devices can be done internally, not at a centralised computer. AI-driven analytics are the goal, but Simao says the bridge from here to there is not clear due to a lack of AI and Deep Learning experts today. “We suffer a lot from lack of data talent,” Simao says, speaking of the industry in general. “There is a lack of knowledge to apply the correct questions.” Today most algorithms and frameworks for Deep Learning – the ability for an AI program to study a data set and make operational decisions – are open source and widely shared because there are so few developers capable of writing custom deep learning routines. Simao says open algorithms are good for getting started, but vendors will need custom AI algorithms they can fine-tune for the application. “An AI model tuned to a specific application must have specific domain knowledge. When we productise, we need full control of the code.”
Cedric Desbordes of CAD developer Graebert GmbH says the use of AI means design and construction documentation software will be much smarter in 2036. Any future CAD software will not replace the need for documenting projects in precise, readable detail. “It is about workflows that will allow users to collaborate with BIM users in a productivity-driven workflow.” By 2036 such workflows will be assisted to a great degree by AI processing. Desbordes envisions a CAD tool smart enough to analyse a picture of a bridge and provide searchable attributes or offer design suggestions based both on aesthetics and structural analysis.
Today there is much discussion about making the building information model – “The BIM” – the central organising technology for the AEC process. Richard Harpham of Katerra is a BIM technology pioneer who thinks the future won’t be nearly so model-centric. “Today the tools make the individual more productive, but we don’t have increased coordination for collaboration.” Harpham was an early employee at Revit, before and after the Autodesk acquisition. “I think the industry will move beyond model centricity. The idea that the model is the centre of all design and construction processes is not sustainable.”
Harpham foresees a “unified data platform” which all participants access in a manner similar to using a browser to access the Internet. “As you browse you gain information and you add information.” AEC data becomes an operational platform where nothing is lost or set aside over time. “Information coordination needs to be more like a snowball.” Harpham says. “BIM only works at the early design stage. The inevitability of drones and robots to deliver a building won’t happen unless the data foundation becomes more reliable.”
New value propositions
By 2036 economic value measurement systems will be based on “formerly intangible values such as collaboration, social, creative, and intellectual capital of people,” says Daniel Robles, CEO and founder of the Integrated Engineering Blockchain Consortium. For AEC, this means a new way to describe the value of infrastructure by measuring the social value and on-going utility of an asset.
Robles framed his initial thought as if looking back from the future to 2036. “It turns out these measurements provided a superior representation of human productivity. Public infrastructure became the intrinsic value upon which public productivity was underwritten.”
Returning to speaking in the present moment, Robles says this vision starts today with the creation of a “decentralised knowledge inventory” for engineering professions. Such an inventory will allow engineers “to shift from a collection of centralised silos into a self-aware global network to adjudicate physical risk in real world systems. … The design IS the smart contract.” This is accomplished through an engineering-specific blockchain which includes “multi-agent game mechanisms to configure human ingenuity” into an intrinsic asset. The result will be a “prioritisation of infrastructure projects for sustainability rather than overt consumption of the Earth’s natural resources.”
Journalist becomes the prognosticator
In 2018 I found myself on the speaking circuit explaining the potential of blockchain for industrial processes including construction. I needed new phrases and concepts to describe where I thought the technology was headed. One was “agora assets,” which I define as “intelligent autonomous buildings, infrastructure, or machines which are situationally aware, interactive, and trustworthy.”
By 2036 such agora assets will routinely interact with humans and each other in ways not possible today. Bandwidth speed and latency issues will be eliminated, making asset-to-asset and asset-to-office communications into real-time transactions.
Light poles will double as giant umbrellas, opening and closing on instructions from a nearby tall building in charge of local weather response services. Self-driving taxis (or dump trucks, bulldozers, etc.) will be owned by “shareholders” who bought a sliver of ownership using blockchain tech but who may never see or use the vehicle, the way individuals and institutions own stocks today. Maintenance, repair, and towing will be contracted directly by the vehicle acting as an autonomous agent for its ownership. Buildings will be able to see, hear, and certify a record of local events. If a self-driving car has an accident in front of an agora building, both the auto and the building can be a witness of record for legal purposes.
By 2036 we will be in the Autonomy Economy era. Perhaps not by 2036, but soon after there will be autonomous tendering. Instead of searching first for real estate, then an architect, etc., the owner/operator will post a Request for Building using a decentralised app connected to a few or a few thousand autonomous construction consortia. Bids will be generated automatically, offering a complete package of land and building. No humans will be directly involved until the potential owner and the winning consortium agree on terms.
The Autonomy Economy will rely on a wide cross section of maturing technologies in five areas: Intelligence, Real-time, Operational, Autonomous, and Distributed (iROAD). The seed technologies for all five elements are in play today, but are years removed from working as a synergistic unit.
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