Development of an IoT‐Based Smart Solar Power Optimization System in University Laboratories in Gusau LGA, Zamfara State
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Background of the study:
University laboratories are critical hubs for research and innovation, yet they often face power supply issues that hinder productivity and the integrity of experimental data. In Gusau LGA, Zamfara State, many university labs rely on conventional solar power systems that operate without real-time optimization, leading to energy inefficiencies and frequent power outages. The integration of IoT technology into solar power systems offers an innovative solution by enabling continuous monitoring and dynamic adjustment of power generation and consumption (Ibrahim, 2023). Smart sensors and controllers can collect data on solar panel performance, battery levels, and ambient conditions, transmitting this information to a cloud-based platform where advanced algorithms analyze energy flow. This real-time analysis allows the system to optimize the orientation of solar panels, regulate battery charging cycles, and adjust energy distribution to match laboratory demand (Adeniyi, 2024). The system also predicts potential power deficits and schedules maintenance activities, thereby reducing downtime and improving energy efficiency. Moreover, automated reporting and remote monitoring reduce the need for manual inspections, resulting in significant cost savings and enhanced operational reliability (Udo, 2025). The application of an IoT-based smart solar power optimization system in university laboratories not only ensures a consistent power supply but also contributes to sustainability by maximizing the efficiency of renewable energy resources. As educational institutions increasingly emphasize green energy solutions, the adoption of such technologies becomes imperative for maintaining competitive and innovative research environments.
Statement of the problem:
University laboratories in Gusau LGA experience frequent power interruptions and energy inefficiencies due to the limitations of traditional solar power systems. These systems, which lack real-time optimization, fail to adjust to fluctuations in sunlight, temperature, and laboratory power demands, resulting in inconsistent energy supply (Ibrahim, 2023). The absence of dynamic monitoring and control mechanisms often leads to underperformance of solar panels, reduced battery life, and increased operational costs. Manual maintenance procedures and periodic inspections further delay the identification and resolution of issues, causing disruptions in research activities and compromising experimental outcomes. In addition, the lack of predictive analytics prevents proactive measures to optimize energy production and storage, leaving laboratories vulnerable during periods of low sunlight or high demand (Adeniyi, 2024). Financial constraints and outdated technical infrastructure exacerbate these problems, hindering the effective utilization of renewable energy resources. Without an IoT-based optimization system, university laboratories continue to suffer from unreliable power supply, which negatively impacts research productivity and overall operational efficiency. Addressing these challenges through an IoT-based smart solar power optimization system is critical for ensuring a sustainable and robust energy supply that supports academic and research excellence (Udo, 2025).
Objectives of the study:
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To design an IoT-based system for real-time monitoring and optimization of solar power in university laboratories.
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To evaluate the system’s impact on energy efficiency and reliability.
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To recommend integration strategies for aligning the system with existing laboratory power management practices.
Research questions:
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How effective is the IoT-based system in optimizing solar power generation and consumption?
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What improvements in energy efficiency and reliability are observed after system implementation?
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How can the system be integrated with current power management protocols to enhance laboratory operations?
Significance of the study:
This study is significant as it addresses the critical need for reliable and efficient energy management in university laboratories. The IoT-based solar power optimization system enhances renewable energy utilization, reduces operational costs, and ensures a consistent power supply for research activities. Its implementation promotes sustainability and supports academic excellence, providing a scalable solution for educational institutions.
Scope and limitations of the study:
This study is limited to the design, implementation, and evaluation of an IoT-based smart solar power optimization system in university laboratories in Gusau LGA, Zamfara State. It does not extend to other energy systems or regions.
Definitions of terms:
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IoT (Internet of Things): A network of interconnected devices that share real-time data.
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Solar Power Optimization: The process of maximizing the efficiency of solar energy systems.
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Energy Efficiency: The ratio of useful energy output to total energy input.
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