Industry: Renewable Energy / Solar Infrastructure
Challenge
High-Risk Manual Operations and Limited Scalability
Manual cleaning of solar panels posed multiple operational challenges — from safety risks at elevated heights to inconsistent cleaning and high OPEX due to continuous human supervision.
- Safety Hazards: Manual work at height increased fall and heat exposure risks.
- Inconsistent Cleaning: Manual control led to uneven cleaning quality and reduced power yield.
- High Labor Cost: Required multiple technicians per site for supervision.
- Poor Scalability: Human dependency limited large-scale deployment.
Solution
Smart IoT-Based Autonomous Solar Cleaning
Sunbio IT Solutions engineered a fully autonomous, IoT-enabled solar cleaning system that minimized risk, optimized performance, and enabled remote control through intelligent sensor integration and cloud connectivity.
- Intelligent Sensor Suite: LiDAR + ultrasonic sensors for obstacle avoidance and safe navigation.
- Real-Time Telemetry: IoT-enabled cloud dashboard for live monitoring and analytics.
- Remote Operation: Centralized scheduling and control via desktop or mobile.
- Smart Power Management: Efficient, autonomous battery utilization for full cleaning cycles.
Results
Zero Safety Incidents and 50% Faster Cleaning Cycles
| Metric |
Before Automation |
After Automation |
Improvement |
| Safety Incidents (at height) | Moderate Risk | Zero Risk | 100% Risk Elimination |
| Cleaning Cycle Time | 8 hrs (Manual) | 4 hrs (Autonomous) | 50% Faster |
| Labor Cost | 2 Supervisors/site | 0.1 Remote Operator | 95% Reduction |
| Energy Loss (Soiling) | 4–6% | <1% | +5–7% Uptime |
By automating the process, Aegus not only eliminated safety incidents but also maximized energy yield and drastically reduced operating expenses.
Next Phase
AI-Driven Predictive Maintenance & Integration
- Predictive Scheduling: Machine learning models to determine optimal cleaning cycles based on soiling patterns.
- SCADA Integration: Real-time cleaning data linked to solar farm performance systems for unified maintenance insight.