Autonomous 3D Modeling of House Roofs from Remote Sensing Data

点击翻译按钮获取中文摘要

Aerialytic aims to solve an industry-wide lead-qualifying challenge in the solar energy industry, through which we**will enable both homeowners and solar sales companies to overcome barriers associated with utilizing solar**panels, thereby expanding solar energy adoption within Canada and globally.**Currently, solar sales companies are spending 60% of their lead acquisition budget in the solar sales ecosystem.**A solar sales agent needs to manually qualify every single homeowner that inquires about solar panels; this**includes creating a custom design for every home that they believe would reap savings from using solar energy.**This lengthy process is required even for the large number of homeowners (40%) that do not qualify due to**factors such as roof shade or size. These sales funnel inefficiencies result in high operational costs for solar sales**companies and a poor customer experience for homeowners, who must wait up to 2 days to obtain information,**leading to an over 30% drop off-rate due to loss of interest.**Our solution is to automate the qualification process by using tools from Artificial Intelligence. This project will**design and build an end-to-end multi-stage system to automatically extract an accurate roof geometry for a**house from satellite imagery, and provide homeowners with their custom solar design on the spot, along with**information on financial and environmental returns.**Last year over 350,000 homeowners transitioned to solar energy in the US alone; with the help of our technology,**we believe we can amplify this number in the US and across the globe.