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@article{166377,
        author = {Deepti Lakshmi Ravi and Dr Bhagya R},
        title = {Non-Intrusive Load Monitoring (NILM): A Comprehensive Review},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {2},
        pages = {853-858},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=166377},
        abstract = {Non-Intrusive Load Monitoring (NILM) has emerged as an indispensable tool in the realm of energy management and smart grid applications, addressing the escalating demand for precise insights into energy consumption dynamics. By disaggregating the overarching power consumption into granular details of individual appliance usage, NILM offers a transformative solution that transcends traditional monitoring methods, devoid of intrusive measures. This paper embarks on a comprehensive journey through the intricate domain of NILM advancements, meticulously dissecting its foundational building blocks, diverse methodological approaches, persistent challenges, and prospective pathways for future exploration. As the energy landscape evolves, NILM remains at the forefront, wielding its potential to revolutionize not only how we consume energy but also how we understand and optimize its utilization across diverse settings. Through an exhaustive examination of its multifaceted facets, this review endeavors to illuminate the profound significance of NILM in shaping the trajectory of sustainable energy management practices and fostering innovation in grid optimization strategies for the digital age.},
        keywords = {NILM, Machine Learning, CNN, Consistent Shape Loads},
        month = {July},
        }