The PCL Construction Solar Division team working on the Azalea Springs Solar project in Luftkin, Texas, was faced with the challenge of tracking progress and quantities of installed photovoltaic (PV) modules across 2,000 acres of uneven terrain. Previous methods of recording piles, racking and module quantities in Excel required manual effort and often resulted in entry errors and overages.

Project coordinators set out to explore the use of cutting-edge drone and artificial intelligence (AI) technology to get the job done. Their goal was to improve client satisfaction through more accurate and timely progress updates without sacrificing quality.  

The team used drones to capture real-time images of the site conditions, running those images through an AI engine which had already been trained to identify piles, racking and modules. AI analytics were then applied to identifying the quantities and locations of installed elements on-site. The data could then be viewed on a centralized dashboard. 

Using drones and AI, the project team avoided the need to have someone walk or drive the site to record quantities. This method has an average $75,000 to $85,000 return on investment for each project.

Dashboard data is visually represented and can be regularly reviewed in check-in meetings with the client. The drone images can also help to identify deviations of pile, fencing and trench locations from the project plan. This helps to reduce costly rework further along in the project.

In addition to providing a more accurate and efficient method for tracking quantities, PCL also leverages drone technology to:

• Track volume of excavation and backfill.
• Capture thermal imaging to identify broken modules and anomalies that may affect the overall performance of energy production.
• Conduct Light Detection and Ranging (LiDAR) scanning, capturing highly accurate typography.
• Meet environmental compliance by surveying vegetation and seeding large or difficult-to-access areas.

Currently, drones are used to track more than 60% of the key performance indicators (KPIs) needed to stay on top of the project schedule. PCL continues to explore more autonomous methods of capturing solar project data in the future.