Predictive Maintenance with AI for Smart Homes/strong>
Authors:-Revathi Renjini, Associate Professor S R Raja
Abstract- As homes are increasingly adopt smart technologies, their reliability as well as longevity have become paramount to avoid unnecessary downtime and ensure continuous, efficient operations. By incorporating Artificial Intelligence (AI) and Internet of Things (IoT) technologies this research enhances predictive maintenance and thereby contributing sustainability goals. Sensors are utilized to monitor real-time data like temperature, pressure, and vibrations from connected devices and systems. Using the machine learning models – linear regression and decision trees, this research demonstrates how AI can extract actionable insights from sensor data. This research showcases the potential to create more reliable, sustainable, and efficient predictive maintenance solutions that are not only low-cost and accessible but can be adapted for both small-scale and large industrial applications. These advancements will further enhance the predictive capabilities of the system and support long-term environmental sustainability by continuously optimizing resource consumption and reducing waste generation.
