Budget Analysis and Smart Job Recommendation
Managing finances and securing part-time jobs is a daunting task for international students studying abroad. This paper introduces novel EduVoyage AI framework, which bundles budget analysis and intelligent job recommendation into one solution for smooth financial planning and efficient job matching. The system leverages Google Gemini AI in generating realistic country-based estimates of budgets by weighing in factors such as tuition fee, choice of accommodation, lifestyle, and course durations. Dynamically calculating tuition and living expenses, travel, and others enables the system to provide personalized financial insights to students wishing to pursue studies in various foreign countries. The job recommendation module will use Gemini AI to generate relevant part-time job opportunities based on local visa regulations, wages, and working hour restrictions. Salary ranges in local currencies are provided along with the working hours, requirements, and benefits of the jobs so that they are compliant with international student work policies. In cases where the job recommendations from AI become unavailable, fallback job listings will be provided to ensure that job recommendations continue to be generated. The whole framework is deployed as a cloud-hosted API, which corresponds to its real-time performance, scalability, and accessibility. The system operates on the MongoDB database for data persistence, with Express.js on the backend API and React for frontend interface-to-date interactive user experience. EduVoyage AI equips international students to make informed decisions on financial and employment matters through estimation of finances, wise job recommendation, and real-time insights. Benchmark evaluations indicate that the system reliably improves the accuracy of budget planning and expeditious search for jobs, ensuring better financial standing and career opportunities for students studying abroad.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-05-22
- DOI
- https://doi.org/10.5281/zenodo.15486539
- Primary Topic
- Diagnosis and treatment of tuberculosis
- Type
- article
- Field-Weighted Citation Impact
- 0.00