Abstract
This study investigates the seasonal and temporal optimization of solar energy harvesting in a smart IoT-enabled streetlighting infrastructure by focusing on the theoretical determination of optimal solar panel tilt angles. The proposed system incorporates auto-adjusted solar panels integrated with an IoT network comprising sensors, microcontrollers, and streetlights. A key innovation lies in the implementation of a modified MQTT communication protocol, which enables efficient, localized decision-making and data exchange among components. Simulation results indicate that the modified MQTT protocol significantly reduces communication delay and power consumption compared to the conventional MQTT approach, thereby enhancing the overall system performance. Detailed analysis of solar radiation patterns reveals that direct, diffuse, global, and total radiation levels peak between 11:30 AM and 12:30 PM, highlighting critical time intervals for optimal energy capture. Moreover, the study finds that optimal tilt angles are most pronounced during the winter months of December through February, underscoring the importance of seasonal variation in improving energy collection. These insights contribute to the development of intelligent, energy-efficient, and sustainable urban lighting systems.
Recommended Citation
Paul, Abhijit; Pipalwa, Rishabh; and Mondal, Sabyasachi North - Eastern Hill University, Shillong, India
(2026).
(SI16 No11) Seasonal and Temporal Optimization of Solar Energy Harvesting in Smart IoT Lighting Infrastructure,
Applications and Applied Mathematics: An International Journal (AAM), Vol. 21,
Iss.
3, Article 3.
Available at:
https://digitalcommons.pvamu.edu/aam/vol21/iss3/3