In the sustainable global goals, economic growth is one of the major challenges faced by any part of the world. Odisha, one of the developing eastern state of India, has many well-known tourist places which can contribute to revenue generation and economic growth. Recently, its government has planned to make some tourist places as "eco-retreat centers" which can attract more tourist to these places. To achieve this objective, the tourist feedback must be analyzed thoroughly which will enhance both quality of service and growth in tourism sector. In this context, an aspect-based sentiment analysis framework is proposed based on Google map reviews given by tourists on Konark tourist spot. Initially, the online reviews are scrapped using Selenium. Then a transfer learning method is proposed utilizing and fine tuning BERT model. The performance is compared with other state-of-the-art models. Further, to enhance the reviews scrapping speed, an Incremental Review Aggregator (IRA) algorithm is proposed. Prompt engineering and few-shot learning with GPT3 is also proposed for better understanding of the aspects. Finally, a web-based application is developed to automate the tasks.