THE IMPACT OF ARTIFICIAL INTELLIGENCE IN PREDICTIVE MAINTENANCE OF ROAD INFRASTRUCTURE: A CASE STUDY OF FEDERAL ROADS MAINTENANCE AGENCY, KADUNA STATE
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Background of the Study
Road infrastructure is critical for socio-economic development, facilitating trade, transportation, and connectivity. However, the poor state of roads in Nigeria often leads to accidents, increased vehicle maintenance costs, and reduced economic productivity. The Federal Roads Maintenance Agency (FERMA) plays a pivotal role in maintaining road infrastructure, yet its efforts are often hindered by traditional maintenance methods, which are reactive rather than proactive.
Artificial Intelligence (AI) offers a transformative approach to road maintenance through predictive analytics. By analyzing real-time data from sensors, drones, and historical maintenance records, AI can predict potential road failures, optimize repair schedules, and allocate resources effectively. Predictive maintenance minimizes downtime, reduces repair costs, and enhances road safety.
This study examines the impact of AI-driven predictive maintenance on road infrastructure management at FERMA, Kaduna State.
Statement of the Problem
Road infrastructure in Nigeria faces deterioration due to delayed maintenance and resource inefficiencies. FERMA struggles with traditional maintenance methods, which are reactive and costly. This study investigates how AI-driven predictive maintenance can improve infrastructure management and road safety.
Aim and Objectives of the Study
Aim:
To evaluate the impact of Artificial Intelligence on predictive maintenance of road infrastructure at FERMA, Kaduna State.
Objectives:
- To identify the limitations of traditional road maintenance methods at FERMA.
- To assess the effectiveness of AI-driven predictive maintenance in infrastructure management.
- To evaluate the impact of predictive maintenance on repair costs and road safety.
Research Questions
- What are the limitations of traditional road maintenance methods at FERMA?
- How can AI-driven predictive maintenance improve infrastructure management and road safety?
Research Hypotheses
- AI-driven predictive maintenance reduces the cost of road repairs.
- Predictive maintenance improves the efficiency of road infrastructure management.
- The use of AI enhances road safety by identifying potential hazards proactively.
Significance of the Study
This study provides insights into how AI can revolutionize road infrastructure maintenance, offering practical solutions to enhance efficiency, reduce costs, and improve safety. The findings are valuable for policymakers, FERMA, and similar agencies.
Scope and Limitation of the Study
The study focuses on the application of AI in predictive maintenance at FERMA, Kaduna State. Limitations include access to proprietary maintenance data and the study's focus on a single agency.
Definition of Terms
- Predictive Maintenance: A proactive approach to infrastructure management that uses data analysis to predict and prevent failures.
- Artificial Intelligence (AI): Technology that simulates human intelligence to analyze data and optimize processes.
- Road Infrastructure: Physical roadways, including highways and streets, essential for transportation and connectivity.
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