Internship Management & Job Recommendation System for Students
This project introduces an Internship Management System integrated with a Job Recommendation Portal...
This project introduces a modern Bike Rental System equipped with a recommendation algorithm to help users find the best bike based on their preferences and usage patterns. Developed using PHP/Node.js, MySQL/MongoDB, and JavaScript, the platform enables users to browse available bikes, check pricing, book rentals, and get personalized suggestions based on past bookings, location, peak demand, and bike popularity.
The system enhances convenience for both users and bike rental companies by optimizing the booking process and improving decision-making with intelligent recommendations. It helps first-time renters choose suitable bikes and supports businesses in increasing rentals and improving customer satisfaction.
The Bike Rental System provides a complete rental workflow—from bike listing, availability checking, and location-based search to booking and payment. The recommendation engine evaluates factors such as bike category, user interest, frequently viewed models, and historical bookings to suggest the most relevant bikes.
Admins can manage bike inventory, pricing, service schedules, and booking records. Users receive a clean interface for browsing and booking while also benefiting from guided recommendations.
Digitalize bike rental operations
Provide intelligent bike recommendations to users
Improve rental decision-making and customer experience
Manage bookings, availability, and fleet updates efficiently
Offer a scalable platform for bike rental agencies
Bike Listing with Photos, Pricing & Specs
Availability Check & Easy Booking System
Smart Recommendation Algorithm (Popularity + User Behavior)
User Dashboard (Rentals, History, Wishlist)
Admin Panel for Bikes, Pricing & Bookings
Location-Based Bike Search
Real-Time Inventory Updates
PHP/Node.js Backend with MySQL/MongoDB
The system simplifies the bike rental process while delivering personalized suggestions to enhance user engagement. It showcases strong skills in full-stack development, recommendation logic, and rental workflow automation—making it a standout BCA final-year project.
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