EVALUATING SMART ENERGY METERS AND ARTIFICIAL INTELLIGENCE FOR MONITORING CONSUMPTION: A CASE STUDY OF RESIDENTIAL ESTATES IN NIGER STATE
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Background of the Study
The efficient monitoring and management of energy consumption are crucial for optimizing energy use and reducing wastage, particularly in residential areas where energy demand is rising. Traditional energy meters provide limited insights, often only displaying cumulative usage without real-time data or actionable feedback. This inefficiency contributes to excessive energy use, higher bills for consumers, and challenges in balancing demand and supply for utility providers.
Smart energy meters, combined with Artificial Intelligence (AI), represent a transformative approach to energy consumption monitoring and management. Smart meters enable real-time tracking of energy usage and provide detailed consumption patterns. When integrated with AI, these systems analyze data to offer predictive insights, optimize energy distribution, and recommend energy-saving measures to users. AI algorithms also assist in detecting anomalies, such as energy theft or malfunctioning appliances, further enhancing system reliability and efficiency.
In Niger State, residential estates are key contributors to electricity demand, yet energy monitoring practices remain outdated. The lack of real-time data and actionable insights hinders energy conservation efforts. This study evaluates the role of smart energy meters and AI systems in monitoring and optimizing energy consumption in residential estates, focusing on their potential to transform energy management in Niger State.
Statement of the Problem
Energy consumption in residential estates in Niger State is often inefficient, leading to high energy costs and increased strain on the electricity grid. Conventional energy meters do not provide detailed or real-time data, limiting residents’ ability to understand and optimize their energy use. This challenge is further exacerbated by irregular billing practices and undetected energy theft, which impact both consumers and utility providers.
Smart energy meters, when paired with AI-driven analytics, offer a solution by enabling real-time monitoring, anomaly detection, and actionable recommendations. However, the adoption of these technologies is limited in Niger State due to high costs, lack of awareness, and technical barriers. This study explores the effectiveness of smart energy meters and AI systems in improving energy monitoring and efficiency in residential estates.
Aim and Objectives of the Study
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To evaluate the effectiveness of smart energy meters and AI in monitoring energy consumption in residential estates in Niger State.
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To identify challenges to adopting smart meters and AI systems in residential areas.
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To assess the cost-benefit implications of implementing these technologies in residential estates.
Research Questions
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How effective are smart energy meters and AI systems in improving energy consumption monitoring in Niger State?
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What are the challenges and benefits of adopting these technologies in residential estates?
Research Hypotheses
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Smart energy meters and AI systems significantly improve energy monitoring and efficiency in residential estates.
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High costs and limited technical knowledge are barriers to adopting these technologies.
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The benefits of smart meters and AI outweigh their implementation costs in the long term.
Significance of the Study
This study highlights the potential of smart energy meters and AI systems to revolutionize energy consumption monitoring in residential estates in Niger State. The findings will guide policymakers, utility providers, and residents in adopting these technologies, promoting energy conservation and efficient billing. It contributes to the broader goal of enhancing energy sustainability in Nigeria.
Scope and Limitation of the Study
The study focuses on residential estates in Niger State, analyzing the role of smart energy meters and AI systems in energy consumption monitoring. It excludes industrial and commercial energy monitoring systems and non-AI approaches. The research may be limited by the availability of smart meter data and the willingness of residential communities to participate.
Definition of Terms
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Smart Energy Meters: Advanced metering devices that provide real-time data on energy consumption and facilitate two-way communication between users and utility providers.
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Artificial Intelligence (AI): Machine learning and data analysis technologies used for predictive analytics and decision-making.
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Energy Monitoring: The process of tracking and analyzing energy usage for efficiency and cost reduction.
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Anomaly Detection: The identification of unusual patterns or inconsistencies in data, such as energy theft or faulty appliances.
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