Evaluation of IoT-Based Smart Elevator Safety Systems in University Buildings in Gusau LGA, Zamfara State
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Background of the study:
Elevator systems in university buildings are critical for ensuring the safe and efficient movement of students, staff, and visitors. In Gusau LGA, many university buildings rely on aging elevator systems that are prone to malfunctions and safety hazards. Traditional maintenance practices are often reactive, addressing issues only after failures occur. The advent of IoT-based smart elevator safety systems offers a proactive approach by continuously monitoring elevator performance, structural integrity, and usage patterns through interconnected sensors and real-time analytics (Ibrahim, 2023). These systems can detect anomalies such as unusual vibrations, temperature fluctuations, or electrical irregularities and immediately alert maintenance teams before a failure occurs (Adeniyi, 2024). By integrating predictive maintenance capabilities, IoT systems enhance safety and reduce downtime, thereby ensuring reliable operation of elevator systems. Furthermore, real-time data collection facilitates compliance with safety regulations and supports efficient management of maintenance schedules (Udo, 2025). This smart approach not only safeguards users but also optimizes operational costs and extends the lifespan of elevator systems. The implementation of IoT-based elevator safety solutions represents a critical advancement in building management, ensuring that university campuses provide safe and reliable vertical transportation.
Statement of the problem:
University buildings in Gusau LGA experience safety and operational challenges with outdated elevator systems that are prone to malfunctions and delays in maintenance (Ibrahim, 2023). The lack of real-time monitoring and predictive maintenance means that potential safety issues often go undetected until a malfunction occurs, leading to increased risk for users and higher repair costs. Traditional elevator maintenance is reactive and fails to leverage modern technology for early fault detection, resulting in inconsistent performance and potential safety hazards. Inadequate integration of safety systems further hampers timely responses during emergencies, leaving building occupants vulnerable. Financial constraints and limited technological upgrades have prevented the adoption of modern monitoring solutions, perpetuating the risk of accidents and service disruptions (Adeniyi, 2024). Without a robust IoT-based safety system, the reliability and safety of elevator operations in university buildings remain compromised, affecting overall building functionality and user confidence (Udo, 2025).
Objectives of the study:
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To design an IoT-based smart elevator safety system for continuous performance monitoring.
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To evaluate the system’s effectiveness in early fault detection and reducing elevator downtime.
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To propose integration strategies for incorporating the system into existing university building management frameworks.
Research questions:
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How effective is the IoT-based elevator safety system in detecting and alerting potential failures?
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What improvements in elevator reliability and safety can be observed post-implementation?
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How can the system be integrated with current building management practices to enhance overall safety?
Significance of the study:
This study is significant as it addresses critical safety issues in university elevator systems by leveraging IoT technology for real-time monitoring and predictive maintenance. The implementation of a smart elevator safety system can reduce downtime, improve user safety, and lower maintenance costs, thereby contributing to a safer campus environment and more efficient building operations.
Scope and limitations of the study:
This study is limited to the evaluation of IoT-based smart elevator safety systems in university buildings in Gusau LGA, Zamfara State. It does not extend to other types of building safety 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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Elevator Safety System: A system designed to monitor and ensure the safe operation of elevator systems.
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Predictive Maintenance: The use of real-time data and analytics to predict equipment failures and schedule timely repairs.
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