Thanks in part to the Internet (of Things) and cloud computing, artificial intelligence (AI) has transitioned from science fiction to everyday life. The impact of AI is already felt throughout our daily lives — from automated spam email detection to viewing suggestions on our favorite streaming service to smart speakers that put voice commands into action.
In very simple terms, AI refers to software that uses “learning” algorithms to analyze data, recognize patterns and produce results accordingly, without much human involvement. Machine learning is a subset of AI, in which machines can modify themselves when exposed to data.
For instance, sensor-equipped vehicles can automatically stop when obstacles are detected. AI-based applications are data “crunchers” that can measure jobsite progress and labor productivity against original plans. They can identify errors and risk factors and send alerts, so contractors can take immediate action.
Although the construction industry is sometimes wary of new technology, AI is becoming more and more prevalent on jobsites. Here are four ways it’s impacting our industry:
- Construction cameras/drones. Image recognition and classification algorithms mine images to flag safety hazards / unsafe behavior and inspect sites, structures and infrastructure. One engineering and architectural services firm recently began using AI-equipped drones to identify areas of decay on bridge decks without having to manually inspect them.
- 3D modeling. AI algorithms applied to 3D models can mitigate clashes and detect design errors, minimizing costly rework. For example, a building information modeling (BIM) plug-in currently in beta testing compares building codes against 3D models to find code violations. (The developers, however, are in a legal battle with the International Codes Council about copyright and “fair use” access to codes.)
- Sensors. Collected sensor data is analyzed to identify areas of concern or opportunities for cost savings. Concrete temperature/strength testing software was recently introduced that detects anomalies at various stages of the concrete life cycle (production, delivery, placement, hardening). It compares current sensor conditions to past measurements stored in the sensor company’s database to detect subtle variances from what should be the norm. Accurate, real-time assessment and prediction of concrete performance in these stages is nearly impossible for humans.
- Self-driving vehicles/robots. Already in production, self-operating construction machinery (and yes, robots) automate repetitive manual tasks, such as excavation, freeing employees to oversee them and work on other tasks. Newer 5G cellular phone networks enable users to operate mobile devices at faster speeds and stay connected almost anywhere, so remote operation of equipment located thousands of miles away or even underground may now be possible. This should expedite schedules and reduce health hazards and safety concerns.
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