The book explores the use of artificial intelligence (AI) in power monitoring systems for SMEs to enhance energy efficiency, reduce operational costs, and ensure sustainability. It discusses current energy challenges faced by SMEs, emphasizes real-time monitoring, and highlights the benefits of AI integration. The chapter details the components of an AI-integrated power monitoring system, including data acquisition, analysis, and control strategies. It examines AI techniques like machine learning, deep learning, and predictive analytics for identifying energy usage patterns. The chapter also discusses successful cases of SMEs using AI-based systems, highlighting their optimization of energy consumption and reduced costs.
TopIntroduction
SMEs are crucial for global economic growth, employment, and innovation. However, they face challenges in managing energy consumption due to rising costs, environmental concerns, and operational sustainability. This book chapter explores the integration of Artificial Intelligence (AI) into power monitoring systems, a promising technological solution that could revolutionize SMEs' energy resource management. By minimizing operational costs and reducing environmental footprint, AI can help SMEs reduce their environmental footprint and improve their energy management strategies(Lu et al., 2022).
SMEs face unique energy challenges due to limited resources, requiring efficient resource allocation. Traditional power monitoring systems may not provide real-time insights for optimizing energy usage, reducing downtime, and cutting operational costs. This chapter explores the importance of real-time power monitoring and the role of AI in making it more accessible and effective for SMEs(Brandalero et al., 2020).
AI integration in power monitoring systems can improve energy efficiency, reduce operational costs, and ensure long-term sustainability for SMEs. Technologies like machine learning, deep learning, and predictive analytics enable the identification of energy usage patterns, enabling data-informed decisions. This chapter examines how AI integration in SME power monitoring can enhance energy efficiency, reduce operational costs, and ensure the sustainability of SMEs(Jung et al., 2021).
This chapter discusses the energy challenges faced by SMEs and the importance of effective power monitoring. It highlights the potential benefits of AI integration in power monitoring, emphasizing the value of real-time data in energy management. The chapter then delves into the core components of an AI-integrated power monitoring system, focusing on AI techniques for energy usage analysis(Žigienė et al., 2019). It presents case studies and success stories of SMEs that have improved through AI integration. It also discusses regulatory and ethical considerations surrounding AI in power monitoring. The chapter concludes by anticipating future trends and challenges in AI's role in SMEs' energy management(Nascimento et al., 2021).
SMEs, known for their agility and innovation, face significant energy challenges that hinder their competitiveness and sustainability. With rising global energy demands and environmental concerns, efficient energy use is crucial. Due to limited budgets and resources, SMEs often struggle to do more with less, leading to increased operational costs and hindered market competitiveness(Crockett et al., 2021). AI-driven solutions for power monitoring can create a level playing field for SMEs, allowing them to harness advanced energy management systems previously accessible only to large corporations. Real-time monitoring of energy consumption is vital for SMEs to adapt and respond to changes in usage patterns, mitigating potential issues before they become critical. AI integration brings predictive analytics and anomaly detection to the forefront, enabling SMEs to anticipate equipment failures, optimize energy usage during peak and non-peak hours, and make informed decisions to cut costs and reduce their carbon footprint(Bauer et al., 2020).
AI plays a crucial role in power monitoring, enabling cost savings, efficiency improvements, and environmental sustainability. It can identify energy waste areas and suggest corrective actions, reducing greenhouse gas emissions and promoting a greener business approach. AI-enhanced power monitoring aligns SMEs with evolving energy regulations, ensuring compliance and competitiveness in a world that values sustainability(Grashof & Kopka, 2023). This book chapter explores AI-integrated power monitoring for SMEs, exploring technologies, applications, and benefits. It provides insights into real-world success stories, regulatory and ethical considerations, and future trends. The goal is to provide a comprehensive perspective on how AI can empower SMEs to manage energy resources efficiently, reduce operational costs, and secure a sustainable future.