The efficient utilization of household electricity is pivotal in the context of rising energy demands and environmental concerns. This study addresses the critical issue of electricity wastage in Chinese households by applying advanced smart meter technology. Aiming to analyze and optimize electricity consumption patterns, the research utilizes the Smart Energy Utilization Model (SEUM) over a period from January 2020 to December 2022, incorporating methodologies such as Artificial Neural Networks (ANN), Support Vector Regression (SVR), Least Squares Support Vector Regression (LS-SVR), and deep learning. The findings reveal that households equipped with smart meters demonstrated a 15 % reduction in overall energy consumption, a 10 % decrease in peak-hour usage, and a notable improvement in energy-saving behaviors among users. Additionally, the integration of smart meters facilitated better load management and contributed to reducing the carbon footprint. The study also found that smart meter data analytics helped in identifying and rectifying inefficient appliances, resulting in a 12 % reduction in energy waste. Moreover, the increased awareness and real-time feedback provided by smart meters led to a 20 % increase in user engagement with energy-saving initiatives. These findings underscore the potential of smart meter technology, enhanced by advanced analytical methods, to enhance energy efficiency and support sustainable development policies.