MUHAMMAD SYAHZANI

Driven to learn quickly, advance computer proficiency and training in industry operations. Solid background in field and office settings supporting team needs. Flexible and hardworking team player focused on boosting productivity and performance with conscientious and detail-oriented approaches. Meticulous and detail-oriented with excellent observational, organizational and communication skills.

Final year Project: Solar Panel Cleaning and Monitoring Robot

• Designed and developed an autonomous robot for solar panel cleaning and monitoring, addressing efficiency loss due to soiling, which can reduce power output by up to 30%. The prototype measured 27 cm x 23 cm and operated on a 92 cm x 57 cm (0.52 m²) solar panel system.
• Implemented both dry and wet cleaning methods, analyzing power output under dust accumulation levels of 10 g/m², 20 g/m², and 30 g/m². Experimental results showed that after cleaning, power generation improved significantly, reducing efficiency losses. Utilized a solar panel charge controller (MPPT), rechargeable battery, and custom-built cleaning mechanisms.
• The project also focused on cost-effectiveness, reducing maintenance costs compared to conventional robots priced between RM 500 to RM 2000. Future improvements include integrating ultrasonic sensors for edge detection and fully autonomous operation. The system enhances worker safety by minimizing the need for manual cleaning at high altitudes.
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MIcro Smart Wind Farm: Integrated Design Project

• Designed and implemented the Communication and Monitoring System for the wind farm, integrating anemometer, vibration, and temperature sensors with a Remote Terminal Unit (RTU) for real-time performance tracking and predictive maintenance.
• Developed an IoT-enabled Farm Area Network, optimizing RJ45 communication protocols for seamless sensor-to-RTU data transmission and ensuring efficient remote turbine monitoring via SCADA-based control systems.
• Ensured compliance with IEEE 1547 and grid synchronization protocols, enhancing wind farm safety, stability, and energy efficiency while enabling predictive maintenance and optimized power generation.
• Developed and implemented the *Internet of Things (IoT) Monitoring and Control System* for real-time wind turbine performance tracking, predictive analytics, and remote diagnostics to enhance operational efficiency. Integrated *smart grid technology* to anticipate wind strength and direction changes, optimizing turbine adjustments for uninterrupted energy generation. Designed a *secure communication network* between the wind farm and end users, ensuring reliable data transmission, system automation, and enhanced monitoring capabilities.