The market for residential solar energy is growing. Though only 3% of 84 million eligible homes in the U.S. currently have rooftop panels installed, according to CNBC, more homeowners are choosing to go solar than ever before. The cost of solar is going down while prices from traditional electricity providers are fluctuating, making solar power competitive in many areas, if a not cheaper alternative. Further, the threat of climate change and increasing power outages from outdated grids are inspiring people to pursue more sustainable options. 

This is great news for the residential roofing and solar industry, but it also means that the marketplace is getting more competitive. Now is the time for residential solar providers to invest in technology solutions that can help take customer engagement to the next level by dramatically improving the efficiency of the estimating a systems design process.

Aerial Imagery Isn’t Enough to Really Improve Estimation and Design

When it comes to bidding a project, aerial imagery of a rooftop, captured through manned flights, is fine for calculating rough estimates. This method can provide accuracy of two inches, at best, which is far better than using a tool like Google Maps at approximately six to 12 inches of accuracy. 

Designing for solar installation can be a very manual process that takes hours to complete, even with imagery compiled from a drone flight.

However, aerial imagery does not support the precision required for design of a solar system on an existing roof structure. Images captured by drone flight provide a much better resolution of one tenth of an inch or better. As some leading companies try to wrap more complete design into the customer acquisition process, those left doing rough bids will end up losing market share to innovators. 

But even drone capture, while superior to aerial imagery, can still make for a very manual, time-consuming process for designers. Drone imagery delivers raw data that must be converted into actionable information, including:

  1. A 3D CAD drawing or wireframe of the roof structure,
  2. A map detailing the location, base geometry, and height of every roof obstruction, such as vents, pipes, chimneys, and satellite dishes,
  3. And a detailed depiction of vegetation, especially trees, around the house that can cast shadows on the roof and any panels to be installed. 

This information is critical to properly design the solar panel system and provide an accurate estimate for the amount of power generated per year for a customer. This conversion can take a trained CAD professional at best 30 to 45 minutes per structure, and up to several hours for complex roof structures. Automating these three critical steps can save solar installers significant time and money and provide more predictable design outputs for their customers.  

Pointivo Fosters Efficiency for Estimating and Design 

Pointivo’s Spatial IQ: Residential Roofing + Solar  solution automates the process of creating these three critical inputs to the design process. Our patented system creates a scalable, predictable, and repeatable method for producing accurate depictions to drive the design process at scale. The fully-automated process uses the industry’s most in-depth and fully trained roofing AI models, based on tens of millions of data points collected over the past five years. Pointivo’s measurement accuracy is currently approximately five millimeters, well within design tolerances for residential solar installations. 

In addition to accuracy, Pointivo’s solution offers unprecedented speed. We routinely return completed data required for a design in approximately two hours from the time a house is flown by a drone. 

Pointivo’s solution converts drone capture data into a 3D CAD drawing of the roof, a detailed obstruction map, and depiction of shadow-casting vegetation – in two hours.

Pointivo’s Spatial IQ: Residential Roofing + Solar solution can help grow and differentiate solar installer’s services by improving the efficiency and accuracy of the estimation and design process through AI-driven automation, delivering better results for customers and the bottom line.