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MIT spinoff Raptor Maps uses machine-learning software to improve maintaining solar panels.
Zach Winn | MIT News Office
January 30, 2019
First off the solar industry has grown. It’s grown so that it has some inefficiencies. Smart entrepreneurs see those inefficiencies as business opportunities. Plus, they are trying to create solutions around them. Such is the nature of a maturing industry.
One of the biggest complications emerging from the industry’s breakneck growth is the maintenance of solar farms. Historically, technicians have run electrical tests on random sections of solar cells to find problems. In recent years, the use of drones equipped with thermal cameras has improved the speed of data collection, but now technicians being asked to interpret a never-ending flow of unstructured data.
That’s where Raptor Maps comes in. The company’s software analyzes imagery from drones and diagnoses problems down to the level of cells. The system can also estimate the costs associated with each problem it finds, allowing technicians to rank their work and owners to decide what’s worth fixing.
“We can enable technicians to cover 10 times the territory and pinpoint the best use of their skill set on any given day,” Raptor Maps co-founder and CEO Nikhil Vadhavkar says. “We came in and said, ‘If solar is going to become the number one source of energy in the world, this process needs to be standardized and scalable.’ That’s what it takes, and our customers appreciate that approach.”
Raptor Maps processed the data of 1 percent of the world’s solar energy in 2018. Thereby amounting to the energy generated by millions of panels around the world. And as the industry continues its upward trajectory, with solar farms expanding in size and complexity, the company’s business proposition only becomes more attractive to the people driving that growth.
Therefore, Raptor Maps founding began by Eddie Obropta ’13 SM ’15, Forrest Meyen SM ’13 PhD ’17. As well as Vadhavkar, who was a PhD candidate at MIT between 2011 and 2016. The former classmates had worked together in the Human Systems Laboratory of the Department of Aeronautics and Astronautics when Vadhavkar came to them with the idea of starting a drone company in 2015.
The founders were initially focused on the agriculture industry. The plan was to build drones. Drones equipped with high-definition thermal cameras to gather data. Once with data then they create a machine-learning system. A system to gain insights on crops as they grew.
So the founders began the arduous process of collecting training data. Then they received guidance from MIT’s Venture Mentoring Service and the Martin Trust Center. Then In the spring of 2015, Raptor Maps won the MIT $100K Launch competition.
But even as the company began working with the owners of two large farms, Obropta and Vadhavkar were unsure. Unsure of their path to scaling the company. (Meyen left the company in 2016.) Then, in 2017, they made their software publicly available. Then and only then something interesting happened.
They found that most of the people who used the system were applying it to thermal images. Thermal images of solar farms instead of real farms. It was a message the founders took to heart.
So it seems that Solar is similar to farming. Cause to start it’s out in the open, 2-D. Plus and it’s spread over a large area. Obropta says, “And when you see [an anomaly] in thermal images on solar. Well it usually means an electrical issue or a mechanical issue. So you don’t have to guess as much as in agriculture. So we decided the best use case was solar. And with a big push for clean energy and renewables, that aligned really well with what we wanted to do as a team.”
Obropta and Vadhavkar also found themselves on the right side of several long-term trends as a result of the pivot. The International Energy Agency has proposed that solar power could be the world’s largest source of electricity by 2050. But as demand grows, investors, owners, and operators of solar farms are dealing with an increasingly acute shortage of technicians to keep the panels running near peak efficiency.
Since deciding to focus on solar exclusively around the beginning of 2018, Raptor Maps has found success. Success in the industry by releasing its standards for data collection. Thereby letting customers — or the many drone operators the company partners with — use off-the-shelf hardware. Hardware to gather the data themselves. After the data submitting to the company, the system creates a detailed map of each solar farm. Thereby pinpointing any problems it finds.
“We run analytics so we can tell you, ‘This is how many solar panels have this type of issue; this is how much the power is being affected,’” Vadhavkar says. “And we can put an estimate on how many dollars each issue costs.”
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