16: Avvir BIM tool prevents rework by catching mistakes as they happen
Automated construction verification is an emerging field that offers huge potential to bridge the gap between design and as-built reality. US-based start-up Avvir is piloting advanced BIM software that uses artificial intelligence (AI) and algorithms to automatically spot defects during construction.
The "end-to-end monitoring service" compares 3D laser-scan data, captured progressively during the build phase, against the BIM model to highlight any elements that are missing or that deviate from the design.
The tool is aimed at building owners, developers or main contractors that need to keep tabs on quality assurance and quality control issues. Given that rework is responsible for an average of around 10% of total construction costs, the software aims to make it simpler to catch mistakes early on and monitor the progress of different packages against the programme.
Although some main contractors scan sites regularly to compare against BIM, Avvir claims that using algorithms instead of people to analyse the data is much faster and more reliable.
The software is being trialled on several live sites in the US. Subscribers have the option to either scan the site themselves as work progresses, regularly submitting the 3D scan data to Avvir to align with BIM, or Avvir can complete the scanning itself at an additional cost.
The results are displayed in an online portal, says Raffi Holzer, CEO of Avvir: "After X number of hours, clients receive an augmented BIM model that shows, for example, how many columns are out of alignment compared to BIM."
Each deviated element is shown twice: once in solid red to show where it should be built; once in a translucent red to show where it is actually built. Measurements show how far each deviated element is out of tolerance.
Users have the option to either retain the defective element, in which case the BIM is updated to reflect that, or notify the contractor to rectify the problem on site. Once the issue is fixed, the area must be re-scanned and the portal updates to display the element as green.
Avvir's algorithms are accurate but unable to detect 100% of anomalies. Human operators are still required to identify smaller items, such as pipes and electrical conduits.
At present, construction managers spend large amounts of time updating schedules. Avvir can help automate that process by tracking when elements of each package, such as the facade or the steel frame, have been completed and updating the schedule to reflect that. If a particular package is running behind, it can suggest a new completion date, which, if accepted, will automatically update the schedule.
17. Site inspections: Quantum sensing finds underground hazards
Hidden underground obstacles can be a major headache for construction companies because they can take time to find before work takes place. Imagine if we could find such hazards 10 times faster than with current equipment? Quantum sensing is said to be a beyond-the-cutting-edge technology, which could revolutionise how we perform surveys.
Professor Kai Bongs, director at the UK National Quantum Technology Hub for Sensors and Metrology, is part of a team developing the sensors. Measuring at the sub-atomic level, the sensors are so sensitive they can detect the tiny fluctuations in gravity that result from even small underground structures, helping to speed up survey times.
"Quantum gravity sensors will mean we are able to see below the ground deeper and more accurately than ever before," says Bongs. "This will greatly help civil engineers to detect hidden objects, such as pipes, mines, tunnels and sinkholes, helping them to build efficiently and safely on hazard-free land."
18. Commercial property: Reonomy's algorithms supercharge search
Searching for exactly the right type of commercial property can sometimes be a painfully slow process, involving scrolling through seemingly endless and mostly irrelevant listings. Instead, Reonomy's search engine aims to prioritise quality over quantity – it sifts through more than 50 million commercial properties in the US to eventually display a tailored selection of properties, all featuring up-to-the-minute specifications, while validation algorithms are continually run across public data to make sure users are receiving trustworthy information.
"Until recently, commercial real estate has been this elusive, gated industry that's been difficult to break into," says Reonomy's CEO, Rich Sarkis. "With algorithms and machine learning, we can unlock insights and opportunities for everyone."
19. Asset monitoring: digital twins and the building lifecycle
Dr Jennifer Schooling was awarded an OBE for services to engineering and digital construction in January. The director of Cambridge Centre for Smart Infrastructure and Construction (CSIC) and director of Applied Research at the Centre for Digital Built Britain (CDBB) talks all things BIM, "digital twins" and asset monitoring.
Is BIM adoption in the UK progressing?
The government mandate [for all public projects to be built to Level 2 BIM] only came in in 2016. The industry started from a largely paper-based information background and now we're asking everyone to convert to not just digital data capture, but object-based data capture, which is a philosophical change people need time to come to terms with.
What is the biggest challenge for a nationwide roll-out?
Everyone needs to understand that data about an asset, throughout design, construction and ongoing operation, is as important as the asset itself. The biggest benefits of data come when it is used throughout the lifecycle of the asset, so BIM requires the engagement of those who will own and operate the asset to ensure that project teams have the right information requirements to respond to.
Is all the digital twin hype justified?
Digital twins are digital replicas of physical assets that contain all the information captured during design and construction, plus live data generated in operation. This will bring benefits in terms of the ability to make the right operational decisions about the individual asset and to feed learning back when we come to build another asset of a similar type.
CSIC's experiments with sensors have improved the understanding of how assets perform. What is its most exciting recent project?
Sir Christopher Wren's St Mary Abchurch Church in the City of London was in danger of being damaged during construction of a new tunnel as part of Transport for London's capacity upgrade at Bank Underground Station. We kitted it out with a range of novel instrumentation techniques, including fibre optics and photogrammetry, alongside the contracting company's more traditional surveying techniques, to monitor for any movement during tunnelling in real time.
The only negligible impact was expected as a result of tunnel construction, so the information provided by monitoring was used to justify not doing prior remedial works to the church, such as additional grouting. If any movement of concern were detected, action would have been taken, but thankfully nothing was and the technique saved the project a lot of time and money.
In future, this approach could support better-informed decision making around the management of existing assets. It would mean that we can move to a regime where maintenance is carried out when it is needed, which is more cost-effective.
20. Tokenisation: Elea turns property data into digital asset
Elea.labs has developed Property DNA, a platform that captures a data profile of a building using a vast variety of inputs. In March the company utilised the system to "tokenise" a property using blockchain technology – the Hello World building in Zug, Switzerland. Michael Trübestein MRICS, real estate adviser to Elea, explains how it was done.
"Property DNA allows owners and other actors in the real estate industry to store data in an easy and reliable way, creating a unique DNA for every building. The DNA is structured in a decentralised way and is filled with both publicly available data and private data such as Land Registry, rental contracts, tenants, size of a building and floor plans. The owner of the DNA decides if data shall be published or not. As more and more data is added and the lifecycle of the property continues, the DNA continues to grow. The aim of Elea Labs is to push the development of the Property DNA on an international level and make it the basis for benchmarking assets.
"During the tokenisation of a building, a defined number of tokens is issued. These tokens represent a part of a building, similar to a share of a listed company. The token issued can be structured in a cost-efficient, individual way and can be used for financing or investments in a building.
"The tokenisation of a property needs three elements: a reliable data structure so investors know about the buildings they are investing in – proven data is the foundation of every transaction; a transaction platform, as a token has to be created and traded as well as dividends paid out; and a stable digital currency, as many crypto currencies, such as bitcoin and ethereum, are highly volatile and therefore do not fit in the investment portfolios of investors. There are several solutions for this conversion, where for example one US dollar, euro or Swiss franc can be transferred 1:1 into a digital currency. With this – non-volatile – currency, a token of a property can be bought.
"RICS has introduced several data standards, and will introduce more, to facilitate cooperation across the real estate industry to allow for buildings to be tokenised more easily. A common data standard by a global institution with a strong reputation, one which looks at the whole lifecycle of real assets, is the key to a better real estate industry, bringing together the traditional real estate companies and disruptive start-ups. RICS' data standards may serve as the foundation of Property DNA and are therefore of high importance. The institution can also serve as a catalyst and encourage meetings, discussions and an international exchange of ideas. Furthermore, the introduction of real estate standards, such as the data standard, will be an important part of a global approach."