According to the U.S. Dept. of Labor, “construction workers are killed on the job five times more often than other laborers.” This has spurred the idea for construction firms to begin launching data science initiatives – one company aims to use Artificial Intelligence (AI) to predict the likelihood of an injury and intervene.
Suffolk, a Boston-based contractor is developing an algorithm that analyzes photos from its job sites, scans them for safety hazards such as workers not wearing protective equipment, and correlates the images with its accident records. The company is still doing some fine-tuning, but says it could potentially compute ‘risk ratings’ for projects so safety briefings can be held when an elevated threat is detected.
Suffolk is also writing an algorithm that would take data from a variety of sources, including 10 years of scheduling data from its archives, and forecast project delays— which would be highly valuable to building owners and subcontractors. They are also pursuing ways to utilize data from IoT sensors to increase efficiency and safety for their workers.
Bringing Technology to the Masses for Safety and Efficiency
The innovative technologies that Suffolk has started to invest in are not wide spread among construction firms or even across the industry as a whole. However, due to a labor shortage and a desire to boost the industry’s low productivity rates, more firms are investing in data science. Proponents say the budding trend could eventually transform the $13 trillion sector.
Suffolk is one of the pioneers looking to advance construction technologies. Suffolk generates a ton of data, from field reports and job-site photos to supplier contracts and inspection records. In the past, the company couldn’t share their findings easily, so the company struggled to do any type of forecasting.
Luckily, they hired a group of data scientists and experts in data visualization, IT, and operations, who stitched together the company’s data feeds and designed an online dashboard to present the information. The result is a program that lets Suffolk employees look at a single summary chart of all the company’s projects around the country and view details on each one’s finances, safety record, schedule, and more.
This advancement and other digital tools that Suffolk is experimenting with are said to “increase productivity by 14-20% in a few years.” These types of advancements are crucial for the construction industry and can help people make better decisions and shave weeks or months off their project schedules.
Combining a CMMS with Future Technologies
A Computerized Maintenance Management System (CMMS) has the capacity to provide maintenance management and staff with an automated tool capable of scheduling inspections and preventive maintenance, managing inventory and work orders, and retrieving recorded asset history.
Technicians can perform actual work with instructions on handhelds, enter how long it takes to complete work orders, filter through past work orders, and close out of the system. All the information is recorded in real-time, so managers can access the information instantaneously.
The ability to track your work, document it, and send it to managers could be paired with wearable technology to give engineers an elevated view of assets through thermal technology, or the ability to see instructions on assets and use that data to train new hires to increase the efficiency of on-boarding.
A CMMS could also benefit from machine learning by using algorithms to monitor assets like meter readings and the ability to calculate readings by the second which would be humanly impossible to do; this would cut down on extraneous labor costs and allow facilities to allocate dollars elsewhere.
This is demonstrated by Suffolk , which uses machine learning to collect data on projects from around the country and give details on individual items such as safety records, schedules, and financial information, allowing workers to assess problems quicker and complete work faster.
The possibilities are endless on how Internet of Things (IoT), machine learning, Augmented Reality (AR), and Virtual Reality (VR) becoming more prominent in a vast number of industries, and the number of companies that are saving dollars and protecting their workers by utilizing these technologies is growing daily.