The estimated total worth of the construction industry as a whole is around $10 trillion per year. To understand how much $1 trillion is, here’s a look at the math. If you spend $1 per second each day, you will spend $86,400 a day. That means you will spend $31.5 million a year. To spend $1 trillion at this rate, it will take you a mind-boggling 32,000 years! And while the construction industry is obviously worth a lot of money, it still has a $1.6 trillion productivity gap caused by a lack of digitalization. This productivity gap prominently positions the construction industry to gain a lot from AI. Engineers and architect firms can use AI to perform tasks with optimal efficiency and accuracy. Let’s take a look at seven of the biggest ways the construction industry in New Orleans can benefit from AI.
Machine learning optimizes construction management in a number of ways. New Orleans construction professionals use it for image recognition, workflow and schedule purposes, and to enhance their problem-solving capabilities.
The first part of any construction project requires collecting data. This data usually comes from contracts, handbooks, enterprise resource planning, design specifications, machinery, and more. With the data in hand, you can input it into a central database. From there, you can crunch the data using ML algorithms to create data-driven answers to important questions. When used strategically, ML allows you to improve safety management, create time-efficient schedules, perform quality checks, and upgrade design management functions. You can even use it to make ML-based predictions relating to weather conditions. And as everyone knows, weather conditions are a key hindrance to construction projects in New Orleans.
Another way to use ML is for issue tracking and management reasons. Construction projects usually utilize multiple tools to record issues. ML algorithms make it simple to prioritize the issues. This helps construction managers know which issues deserve their attention first. Imagine completing a project will all high-priority issues tackled first. This saves both time and money and helps position you as an industry leader in New Orleans.
There are numerous factors that influence design, and construction managers must account for each of them. Unfortunately, as construction design currently stands, it’s somewhat archaic, especially without the adoption of new technology. This impedes the entire project completion process. With AI, New Orleans contractors can leverage supervised learning systems to collect and analyze environmental, material, and building data. Using deep analysis, contractors can pinpoint the best way to design and build a building.
Let’s say you’re building a new home. With AI, you can give the intended specifications of the home and receive a detailed report outlining what materials to use. Along with suggested materials, you’ll also receive projected costs and a timeline of how long the project will take to complete. More so, you can perform automatic design checks along with quick constructability analyses. You can even optimize the design process by looking at projected costs according to different criteria.
Quality control is essential to the safety of workers and building occupants. But true quality control is tedious. When you combine AI with other innovative technologies, like drones, it becomes possible to improve quality control. Neural networks — the entire basis of AI — combined with drone images allow you to compare construction inconsistencies against various models. This allows you to spot potential threats before they occur. You can save considerable time and money with this form of better quality control.
Without digitalization, you’ll end up with separate data silos when collecting and managing data. This makes it difficult to look at data in real time and even harder to make data-driven decisions. Overall, you’re left with data that proves of little value to your project. With AI, you gain the ability to create a unified data management system. All data goes into the same database on a real-time basis, easily allowing you to make informed decisions as changes take place throughout the project.
Engineers already use 3D printing. Some believe 3D printing will completely remodel the entire construction industry. 3D printing is particularly of benefit during the early and late stages of projects. More specifically, during design and maintenance. With building information modeling (BIM) and other forms of advanced technology, it becomes possible to streamline the entire fabrication process. Engineers can fabricate complete materials and parts both onsite and offsite with 3D printing. This is especially of benefit when projects require customized solutions.
Thanks to natural language processing (NLP), AI agents have enhanced capabilities to understand human expression. Many technologies already use NLP, such as Google Assistant and Siri. In the construction industry, AI agents improve projects by enhancing project coordination. Engineers can turn to their digital assistants to receive answers to project-related questions and capture progress data updates. Digital assistants can also provide warnings related to potential threats. Furthermore, they can give workflow optimization suggestions.
AI powered robotics reduce project costs by cutting down on material installation times, such as bricklaying. Think about how much money you can save on a project if you don’t have to hire bricklayers. You can also use AI powered robotics to carry materials. This greatly reduces the amount of money you have to spend on labor. Lower labor costs translate into lower project costs. Quoting lower project costs will win you more contracts, which turns into higher revenue.
2019 is a year when we will see great advancements in the construction industry thanks to AI. This form of technology is more accessible than ever before as machine learning libraries and BIM have reached advanced levels of maturity. As we start to use AI more and more, construction analysts will perform extensive analyses to determine AI best practices.
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