Machine Learning is a specific subset of Artificial Intelligence, where the software can improve the effectiveness of algorithms by analyzing great amounts of data. This makes roof damage detection a great application for machine learning, because the software is able to process hundreds of thousands of roof inspections and learn from experience. Each roof inspection benefits from the experience gained in analyzing the previous roof inspection. In contrast to traditional roof inspection models, machine learning brings the following advantages:
Traditional roof inspection models rely on experts. Individuals with years of experience can recognize anomalies and determine if roof damage has occurred. Experts that focus on one geographic area may also bring knowledge of recent weather events or general weather conditions in the area. However, expertise varies by company, region, and the qualifications of the inspector. With machine learning, this problem is eliminated. With an automated approach, the same algorithm is used to analyze each roof report. If the data is collected according to specifications, the algorithm will analyze each roof and arrive at the same conclusions related to roof damage.
As with any automated process, errors related to accuracy can be reduced or eliminated. The machine learning algorithm will not make erroneous errors due to oversight, fatigue, or other human factors. This advantage improves the overall accuracy of damage detection and reporting.
Speed is critical in the roofing industry. Speedy roof repair can protect homes from water damage or other costly damage. Machine learning can reduce the time it takes to submit a claim from weeks to days. One an inspection is complete; the algorithm can quickly analyze the data and build a claim report. A process that one took days can be reduced to hours or minutes.
Weather events commonly affect thousands of houses at once which creates a demand for roof inspections that far exceeds the supply of qualified roof inspectors. With machine learning, much of the required expertise is built into the damage detection algorithm. The algorithm can analyze thousands of rooftops per day, which can shorten wait times and speed up the roof repair process. Reduced wait times can help families get repairs sooner and return to their homes more quickly.
Today, Panton is using damage detection algorithms to manage residential and commercial rooftops nationwide. The algorithm is proving to be an effective means to deliver quality inspection reports in less time and for a fraction of the traditional cost. In addition, the algorithm is gaining experience with each inspection. Panton predicts that most roof inspections will be conducted using machine learning by 2020.
If you’re interested to see how you can leverage machine learning in your business, check out our roof inspections page.
All photos were taken by Panton drone pilots during inspections.