Monitoring and controlling energy use is critical for efficient power system management, particularly in smart grids. The internet of things (IoT) has compelled the development of intelligent systems such as the adaptive neuro-fuzzy inference system (ANFIS) and fuzzy fruit fly optimization to improve monitoring, optimise energy use, and enable demand response (FFO). This chapter examines the advantages and disadvantages of IoT-enabled microgrids, as well as system installation for energy monitoring and control. It focuses on the architecture, implementation, experimental setup, evaluation, and performance analysis of the ANFIS and FFO algorithms in smart grids. The chapter covers data security, privacy, interoperability, scalability, grid resilience, cost-effectiveness, stakeholder involvement, and AI breakthroughs in energy monitoring and control.