The construction industry has historically been an under-digitized sector, only beating out agriculture and hunting. Change is upon us and projects are adopting new technology on the job site. Superintendents and project engineers are now armed with powerful mobile apps and photo and video capture devices wherever they are on the job site. Mobile devices with high quality cameras, 360°, and high resolution site cameras are becoming commonplace. Making sure this equipment is used efficiently, by capturing quality photos and videos, can play a significant role in the success of a project.
I’m pleased to welcome Charles (Chuck) Cobb, former general counsel for construction manager William A. Berry & Son, to Smartvid.io as our advisor on construction risk and insurance. He will be working with us closely as we help our customers understand how to best leverage our construction risk analytics data. Chuck's first contribution below explores how contractors can best use insights from AI to reduce actual and legal risks. And, if AI engines like VINNIE proactively detects risks on jobsites, what is a contractor's potential liability if accidents still occur? We’re excited to have Chuck on board to explore these questions and many other important topics for our customers and partners. Josh Kanner, Founder & CEO, Smartvid.io
Data analytics and business intelligence (BI) have been getting a lot of press recently due to their increased use in the construction industry. "Number crunching has always been a big part of construction — a commonly heard phrase is that construction companies are accounting companies which happen to erect buildings," says Bernard Marr, How Big Data And Analytics Are Transforming The Construction Industry. The most significant change recently has been the abundance of data available to analyze.
What does AI actually mean? It’s a term thrown around all the time in media and tech circles used to describe anything from the latest app to full-on doomsday robots. Wikipedia defines AI as “intelligence demonstrated by machines,” versus natural intelligence shown by humans and other animals. Since AI is still nowhere close to the any human-like “intelligence,” its working definition usually refers to software that’s very good at accomplishing narrowly defined tasks.
Properly tracking and documenting progress on a construction project is critical to a well-managed project. Documenting when and how key tasks and activities are completed by specific trades can make schedule updates more straight forward. Capturing this information, however, has traditionally required time-consuming site walks and tedious, paper-based processes that are poorly controlled and inconsistently executed.
Today at ENR’s FutureTech conference in San Francisco, Jit Kee Chin, EVP and Chief Data Officer at Suffolk, announced the results of 6 months of collaboration between our companies. We think it’s groundbreaking and hope you will too.
Without a doubt, keeping workers safe on the job site should be the most important thing to any project team. And yet, today’s job sites that are increasingly large, complex, and rapidly changing make it very challenging to constantly monitor the site for all aspects of safety best practices. Having a second set of eyes that look out for safety hazards can be a valuable tool for project teams -- a key reason why many leading contractors are investing in safety training and assigning on-site safety professionals for their largest jobs. Even so, there are limits to how many site inspections teams can execute in the context of broader responsibilities that include planning and coordination, training, reporting, and incident investigations.
As the construction industry grows so does the risk of injury on the jobsite. Projects are becoming larger and increasingly complex, not to mention the compressed schedules we are all asked to deliver. Each of these factors puts workers at a greater risk of injury in a fast paced, complex environment. All the while, contractors are being asked to reduce costs and take on more risk to complete these projects.
Our end of January release was a big one, headlined by the addition of new safety tags (as featured in ENR), a new integration with OxBlue site camera (now in Beta), and lots of cool new features on web and mobile.
Topics: Product Updates
As we have turned the page on 2017, we wanted to pause to look back at the highlights of the year for Smartvid.io and our mission of bringing machine learning (ML) to construction. More than anything else, we are deeply appreciative of our committed and innovative customers, partners, and employees who are committed to our vision of improving the industry with technology.
Like all firms, it is important for Engineering News Record (ENR) to know if unsafe conditions are being shown in the imagery it releases to the public. For their annual photo competition, the ENR team used our machine learning to review all 763 images submitted for consideration. In this article published by ENR, you can see our ML engine, nicknamed “VINNIE”, found 97 people not wearing gloves, 31 without hardhats, 89 without safety colors and 11 without eyewear. We helped screen the winning pictures and identified two that we recommended be reviewed further.
Don’t be one of the million construction workers who visit the ER this year due to hand injuries.
The construction site is riddled with hazards for your hands and wearing proper gloves might be the only thing between you and a trip to the emergency room. The stats on hand injuries in construction are staggering.