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Home - Solar Industry - Canadian startup unveils AI tool to optimize solar panel cleaning
Solar Industry

Canadian startup unveils AI tool to optimize solar panel cleaning

solarenergyBy solarenergyMarch 20, 2026No Comments3 Mins Read
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Swish Solar has an AI-powered tool that optimizes solar panel cleaning schedules to reduce contamination losses and operating costs. The platform uses data analytics and forecasting models to help operators determine cleaning time based on financial impact.

March 20, 2026
Emiliano Bellini

Canadian startup Swish solar energy is developing solar panel cleaning and AI-based optimization technology for utility-scale solar power plants, aimed at reducing pollution losses and reducing costs associated with poorly timed cleaning.

Dubbed SwishOSis the software designed to manage and predict cleaning operations at optimal intervals.

“Because operations teams typically rely on a fixed cleaning schedule regardless of the level of contamination, we started calculating the financial losses caused by poorly timed cleaning routines.” Miswar Syedco-founder of Swish Solar, said pv magazine. “This way of working is expensive, especially in places like Saudi Arabiawhere I grew up. The costs of robots, transport, distilled water and field workers are increasing.”

The company describes SwishOS as an AI-powered analytics platform that models contamination and optimizes cleaning schedules. “Our software is a purely data-driven solution that requires no additional hardware. It uses operational data combined with hyper-local inputs, such as the cost of water, electricity and labor,” said Syed.

The platform allows users to visualize the impact of different cleaning schedules, compare cleaning costs with the value of recovered energy and determine optimal timing. It tracks a running total of performance gains and pollution losses in USD, and can be deployed for individual plants or large portfolios.

“The The platform uses our proprietary time series forecasting models, regression-based models, anomaly detection algorithms and ensemble methods,” explains Ryed. “It can be seamlessly integrated with solar farm management systems and SCADA platforms.”

See also  Korean researchers build tin monosulfide solar cell with an efficiency of 4.81% – SPE

“By translating performance losses into financial terms, the platform helps operators identify when cleanups are economically justified,” he continued. “Rather than relying on fixed schedules, asset owners can make more informed maintenance decisions based on changing environmental conditions and market factors, improving both operational efficiency and revenue recovery.”

According to Syed, SwishOS has won early solar customers North America and the Middle East. Prices follow a sliding scale based on installation capacity, with reduced rates for systems under 1 MW.

Founded in 2024 by Syed and co-founder Amirhossein Boreirithe company has applied for four patents. It has raised $1.5 million in a pre-seed funding round from Canadian and US investors.

Swish Solar also develops SwishScreen, a dirt-repellent, self-adhesive polymer film for new and existing panels. The technology uses an electrical charge to remove dust or snow without water, chemicals or mechanical equipment. The first prototypes are being field tested in Saudi Arabia, although performance details have not yet been announced.

This content is copyrighted and may not be reused. If you would like to collaborate with us and reuse some of our content, please contact: editors@pv-magazine.com.

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