ADVANCEMENTS IN AI-DRIVEN IOT SYSTEMS FOR SMART HOME ENERGY EFFICIENCY

Authors

  • Nikhil Jain

DOI:

https://doi.org/10.53555/ephijse.v8i3.293

Keywords:

AI-driven IoT, Smart home, Energy efficiency

Abstract

AI driven IoT (Internet of Things) systems have made remarkable improvements in energy efficiency in smart homes thereby providing a ground breaking strategy for adopting sustainable life. Using AI algorithms and the real time data of connected devices, these systems optimize energy usage, minimize the waste, and ultimately make the house more efficient. Thermostats, lighting, and appliances are smart devices that automatically optimize themselves for efficiency once the machine learning models analyze user behavior, environmental data and patterns of energy usage to predict energy needs. An example of one of the key advancements is that predictive analytics have been integrated, so your energy demand is anticipated and settings are adjusted proactively. For instance, AI can teach an AI driven thermostat a household’s schedule and adjust the intensity of the heating and cooling system of your home based on the schedule to maintain comfort while using the least amount of energy. Similarly, smart lighting systems can adjust to natural light level, dimming or brightening according to occupancy and time of day. In addition, these systems aids in grid optimization such that smart homes not only control how its energy is used but also how it interacts with the energy grid as a whole. Demand response capabilities are enabled through this, where smart homes can use consumption adjustments during peak demand times to help stabilize the grid and lower costs. AI driven IoT systems are changing the dynamics of smart home energy efficiency through real time optimization, ability to adjust and learn and seamless interaction with the grid and bring about sustainability and lowering environmental impact.

Author Biography

Nikhil Jain

Smartthings Inc

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Published

2022-05-10