AI Base Cooling System for Home
Year: 2025
Type: article
Abstract: : As global temperatures increase, the necessity for efficient and sustainable home cooling solutions has surged. Conventional air conditioning units utilize significant energy, resulting in elevated electricity expenses and ecological concerns. This paper examines the creation of an AI-Based Cooling System for Homes, which merges artificial intelligence with intelligent cooling technologies to enhance energy efficiency while preserving indoor comfort. The suggested system utilizes AI algorithms to evaluate environmental data, user preferences, and real-time temperature changes to automatically modify cooling functions. Through the use of IoT-enabled sensors, machine learning models, and adaptive control strategies, the system boosts energy efficiency and lowers carbon emissions. Furthermore, predictive maintenance and smart scheduling enhance system durability and user convenience. The AI-driven method guarantees a balance among comfort, energy savings, and cost-effectiveness, making it a feasible option for contemporary smart homes. From an energy-saving perspective, the AI-based system offers significant advantages. By reducing unnecessary operation time and optimizing appliance usage based on actual demand, it can reduce electricity consumption by up to 30–40% compared to traditional systems. Furthermore, by intelligently managing power cycles and leveraging low-energy cooling methods (like ceiling fans and cross-ventilation when outdoor conditions are favourable), the system helps reduce environmental impact. Security and privacy are also considered in the system's architecture. All data is processed locally or transmitted over encrypted channels, and users retain full control over data sharing preferences. In conclusion, the AI-Based Cooling System for Homes represents a forward-thinking solution for modern households seeking sustainable, cost-effective, and intelligent climate control. By combining AI-driven decision-making with IoT-based automation, the system not only improves user comfort but also promotes responsible energy usage and environmental stewardship. As smart home technologies become more accessible, systems like these are expected to play a critical role in the future of residential energy management and sustainable living. Keywords: AI cooling system, smart home, energy efficiency, IoT, machine learning, adaptive climate control.
Author: Prof. Rakesh Bairagi , Mr. Sumeet Sahare , Mr. Dhananjay Agre , Mr. Tejas Shende , Mr. Amitabh Barai , Mr. Prem Kejarkar
Language: English
Topic: IoT-based Smart Home Systems
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6912086510
FWCI:
Cites:
Cited by:
Related to: