TAYPRO’s robots restore 95–99% efficiency vs. 70–80% with manual methods. In Tamil Nadu’s humid climate, this prevents 15–20% losses from salt and algae.
Yes. Robots deploy post-rain cycles to clear mud streaks and use hydrophobic microfiber to repel moisture. In Maharashtra, this reduced algae growth by 90%.
TAYPRO addresses the critical challenge of dust and debris accumulation on solar panels, which can reduce energy output by up to 30%. In arid regions like Rajasthan or polluted urban areas like Delhi, dust layers block sunlight, create hotspots, and accelerate panel degradation. This leads to significant revenue loss (e.g., ₹2.5 crore/year for a 100 MW plant) and delayed ROI for solar operators. By automating cleaning with AI and robotics, TAYPRO ensures panels operate at peak efficiency, maximizing energy generation and sustainability.
Vibration mode shakes off snow without damage. A 10 MW farm reduced snow-clearing labor costs by ₹15 lakh/year.
A 100 MW plant regains 15–20% efficiency, saving ₹1.8–2.4 crore/year (at ₹3/kWh). In Karnataka, this funded a ₹50 lakh CSR water project.
TAYPRO’s AI models analyze satellite imagery, historical weather data, and on-site IoT sensor inputs (wind speed, humidity, PM2.5 levels) to forecast dust storms 6–12 hours in advance. For example, in Rajasthan, the system detects wind gusts >35 km/h as a precursor to sandstorms, triggering preemptive cleaning to minimize post-storm residue. Accuracy exceeds 90%, as validated in Gujarat’s 2023 cyclone season.
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