Home Services Recommendation System using Machine Learning for Urban Areas

Abstract

The Kotlin-based on-demand home service system streamlines household tasks by offering services such as repairs, cleaning, gardening, and plumbing. In today's fast-paced world, it provides quick solutions for maintaining a clean and hygienic living environment. The Housekeeper Finder app is a prominent player in this space, utilizing advanced machine learning algorithms to deliver personalized service recommendations based on user preferences. It includes essential services like cooking, laundry, and elder care, along with a robust feedback system to improve service quality. Users can easily book services from anywhere, leveraging GPS technology to connect them with nearby providers. The "Domestic Android Application for Home Services" further enhances accessibility through location-based service requests and mapping capabilities for a seamless user experience across platforms.A s cities transition into Smart Cities, integrated information systems open new avenues for urban service recommendations, fostering liveability and sustainability. Recommendation systems analyse user behaviour to provide tailored suggestions using techniques like collaborative filtering and hybrid methods. In response to the challenges of modern work culture, the e-commerce landscape now offers easy access to essential services via mobile applications, ultimately transforming how households address their needs and promoting safer, cleaner living space.