AI-Based Smart Utility Management System

This research explores the development and implementation of an AI-based Smart Utility Management System that allows users to book home services such as cleaning, electrical, plumbing, and more. The system integrates AI-powered features like personalized user experiences, chatbots, predictive analytics, image recognition, and smart scheduling to enhance efficiency and user satisfaction. Additionally, it incorporates non-AI features like user dashboards, loyalty programs, multilingual support, and service provider profiles to improve accessibility and engagement. This paper outlines the system’s methodology, architecture, AI models, and evaluation metrics. The results demonstrate that AI-driven home service management improves user experience, service efficiency, and business scalability. Challenges such as data privacy, AI bias, and service provider optimization are discussed, along with future directions for AI-powered home service platforms.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-03-07
DOI
https://doi.org/10.22214/ijraset.2025.67207
Primary Topic
Power Systems and Technologies
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Based Smart Utility Management System

Nikita Ishwar Dhanvijay
International Journal for Research in Applied Science and Engineering Technology
Power Systems and Technologies
article

AI-Based Smart Utility Management System

Nikita Ishwar Dhanvijay
article en

Abstract

This research explores the development and implementation of an AI-based Smart Utility Management System that allows users to book home services such as cleaning, electrical, plumbing, and more. The system integrates AI-powered features like personalized user experiences, chatbots, predictive analytics, image recognition, and smart scheduling to enhance efficiency and user satisfaction. Additionally, it incorporates non-AI features like user dashboards, loyalty programs, multilingual support, and service provider profiles to improve accessibility and engagement. This paper outlines the system’s methodology, architecture, AI models, and evaluation metrics. The results demonstrate that AI-driven home service management improves user experience, service efficiency, and business scalability. Challenges such as data privacy, AI bias, and service provider optimization are discussed, along with future directions for AI-powered home service platforms.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(3)
Openalex Percentile: Top 97%
Power Systems and Technologies
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