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How to Identify and Detect Risky Work Using AI (Artificial Intelligence)


More people die in building than in any other sector, and the number one cause of death on a job site is falling.

Autodesk’s latest addition to its BIM 360 suite of artificial intelligence (AI) enabled sector tools – Construction IQ – target to decrease these terrible happens. It does this by forecast when drops are likely to occur – as well as any other risk to life, limb, or even just quality of activity.
Autodesk’s data experts hit upon the solution while moving for applications where the useful amount of data storage on now-a-days construction sites could be put to use, thanks to the industry’s eager adoption of mobile tools and observing gadgets.




"Predict being a construction admin and having to contend with the real that every X number of months, someone's moving to die on the job – it's incalculable to most of us in professional jobs," says Pat Kearney, Autodesk’s move on the Develop IQ project.

Construction IQ uses natural language processing (NLP) techniques – algorithms that specify human language (in this case, text notes deploy around construction jobs by contractors and subcontractors on site) to evaluate threat and warn of danger that may go unseen by human safety managers.

Keaney tells me, "Right now we're targeting on audition NLP … we have associate using image identify; there are 360-degree cameras, Internet of Things (IoT) that can observe gasses in the air … in my mind there’s no doubt that within the next five years, this technology is going to be saving lives.”

In fact, indicate recommends that it suddenly already is. I spoke to one develop company, BAM Ireland, which told me that by using Autodesk's BIM 360 solution, they had achieved a 20% reduction in quality and secure problems on site.

They have also influenced the amount of time available to staff to spend retrieving huge risk problems on site by 25%.

All of this has become possible thanks to the outbreak in the number of data produced and developed at construction sites.

"We perceive there are these vast changes occurring in the software industry as a result of things like smartphones and tablets.

"They've only been around 11 or so years, but they've changed the landscape … instead of carrying around reams of paper, you can look at plans on an iPad, and when you do this, you don't just save time, you generate and collect data.

“Everyone has a phone and a high-exception camera in their pocket … so explore that idea to IoT and sensors, most smart people don’t sit around trying to figure out when solid has cured now, they put a sensor in it, and the sensor tells them when it’s ready.”

The next stage was a natural leap – getting this data and creating it available to the AI tools Autodesk developed for its BIM 360 platform meant a move towards a predictive, data-driven model of construction management.

“Our simple theory was there’s got to be value in this data that will help our customers do a more effective job of managing their crazy, chaotic, every-boosting construction projects. That’s what led us to start this exploration.”

This is a perfect example of a boosting similar and productive trend across all industries that are charming in digital transformation. Digitization outputs in a wealth of information that can often prove useful far beyond the initial use cases for which it was collected.

As the program got analysis, there were startup concerns about how willing agencies would be to share the data. These improved to be unfounded, as Keaney explained to me:

“In general, our customers have far exceeded my expectations for willingness and passion for allowing us to help them find value in their data … we said we want to go on an exploration and partner with you guys … if you're interested in what we need is for you to grant us access to your data.

Read more - Why Your Company Needs AI

“When we did that, our customers would get really excited and dig in and want to spend more time with us … we were able to show them things in their data they had never seen before.

“Are there certain companies that were more conservative and wary? Certainly – in the US they were more willing to take a risk, Europe was a little more cautious – which is one of the reasons it was so exciting to see it embraced by BAM Ireland.”

Data covering over 150 million construction issues harvested from 30,000 real-world projects has been used to train the algorithms that BAM used to drive their impressive results in the field of site safety.

Their digital construction operation manager, Michael Murphy, told me how the platform had allowed them to move away from the siloed approach to data the construction and civil engineering firm had traditionally taken.

He said “When we debut, we seek our biggest issue was our data was very irregular, so when we were setting up projects we were being illogical around how we were storing data, or the problem types we were capturing.

“When we engaged with Construction IQ, the first thing we had to do was tackle this inconsistency – that was a big lesson learned.

“This meant we were able to get better insights into the issues and challenges across our projects … whereas previously we may have just been doing something on a mobile phone or an iPad for the sake of doing it on an iPad … we weren’t really getting the benefits of having standardized datasets that we could query, and get better insights from.”

It seems inevitable that as technologies such as machine learning, NLP and deep learning continue to prove their worth, solutions built on them will become increasingly widely adopted across construction, as well as any other industries that can benefit from a consolidated approach to data gathering and analytics.

In the short term, this is likely to save lives, while in the long term, it will contribute to the development of safer working practices and standards.

As Keaney puts it, “I think secure is something that everyone can convince is crucial – nobody should be holding their data off to their chest around these problems, it wouldn’t be good behavior.

"The whole industry shares these problems … and all of this tech is going to save lives; there's no doubt about it … from a safety perspective, the benefits are clear, compelling, and really easy to understand."

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