• Yash Ingle
• Shrikant Shinde
• Abhijit Lavhale
• Vedant Hedau
• Ayush Bendale

Urbanization has led to an increasing demand for efficient parking solutions, prompting the development of various parking reservation and navigation systems. However, existing solutions often suffer from drawbacks such as limited accuracy in predicting parking availability and lack of user-friendly interfaces. Previous parking prediction solutions often faced challenges with accuracy and usability, limiting their effectiveness and adoption. Our project, employees LSTM deep learning, our system significantly improves real-time forecasting by analyzing historical data. The integration with Google Maps API further enhances user experience by providing seamless navigation system to navigate through reserved spots. Moreover, the user-friendly interface ensures accessibility and ease of use for all users, regardless of their technical proficiency. Our project aims to optimize parking utilization, offering a transformative solution to the complexities of urban mobility.

Long Short-Term Memory (LSTM), Parking Reservation, Navigation system, Deep Learning, Google Maps API

"Smart Parking Reservation and Navigation Application using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.f773-f781, May-2024, Available :http://www.jetir.org/papers/JETIR2405586.pdf

"Smart Parking Reservation and Navigation Application using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppf773-f781, May-2024, Available at : http://www.jetir.org/papers/JETIR2405586.pdf