International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Unveiling Urban Amenities: A Study on Automated Detection Techniques

Abstract

This project delves into the realm of automated property analysis through the lens of amenity detection using the Detectron2 framework. Leveraging the advancements in computer vision and deep learning, the project aims to develop a robust model capable of accurately identifying and categorizing various amenities within room images. Termed "Amenity Detection using Detectron2," the endeavors seeks to streamline the process of property assessment by automating the identification of indoor amenities. Through a combination of sophisticated algorithms and innovative technology integration, the project showcases the potential of AI-driven solutions in revolutionizing real estate analysis. By providing a comprehensive tool for amenity recognition, this research endeavors to empower property analysts, interior designers, and real estate professionals with efficient and accurate insights into property features.

Country : India

1 Kunal Pohakar2 Parth Pisat3 Mohammad Rahil4 Yash Rawool5 Prof. Sonali Deshpande

  1. Student, Smt. Indira Gandhi College of Engineering, Ghansoli, Navi Mumbai, Maharashtra, India
  2. Student, Smt. Indira Gandhi College of Engineering, Ghansoli, Navi Mumbai, Maharashtra, India
  3. Student, Smt. Indira Gandhi College of Engineering, Ghansoli, Navi Mumbai, Maharashtra, India
  4. Student, Smt. Indira Gandhi College of Engineering, Ghansoli, Navi Mumbai, Maharashtra, India
  5. Professor, Dept. of AI & ML, Smt. Indira Gandhi College of Engineering, Ghansoli, Navi Mumbai, Maharashtra, India

IRJIET, Volume 8, Issue 4, April 2024 pp. 229-235

doi.org/10.47001/IRJIET/2024.804033

Full Paper
Download

References

  1. Kawano, S., Imanishi, T., Ikeda, Y., Nishi, H. and Uchiyama, E., 2016. Implementation of Household\'s Amenity Maintaining System Based on Behavior Estimation. Procedia Environmental Sciences, 34, pp.582-593.
  2. Solomon Cheung, Y.S. and Zhang, F., 2019, December. An Intelligent Internet-of-Things (IoT) System to Detect and Predict Amenity Usage. In CS & IT Conference Proceedings (Vol. 9, No. 17). CS & IT Conference Proceedings.
  3. Mahesh, Batta. \"Machine Learning Algorithms-A Review.\" International Journal of Science and Research (IJSR). [Internet] 9 (2020): 381-386.
  4. Arman F, Hsu A, Chiu MY. Image processing on compressed data for large video databases. In Proceedings of the first ACM international conference on Multimedia 1993 Sep 1 (pp. 267-272).
  5. Wan, X., Ren, F., & Yong, D. (2019, December). Using Inception-Resnet v2 for face-based age recognition in scenic spots. In 2019 IEEE 6th International Conference on Cloud Computing and Intelligence Systems (CCIS) (pp. 159-163). IEEE.
  6. Bhatia, Yajurv, Aman Bajpayee, Deepanshu Raghuvanshi, and Himanshu Mittal. \"Image Captioning using Google\'s Inception-resnet-v2 and Recurrent Neural Network.\" In 2019 Twelfth International Conference on Contemporary Computing (IC3), pp. 1-6. IEEE, 2019.
  7. Latha, H.N., Rudresh, S., Sampreeth, D., Otageri, S.M. and Hedge, S.S., 2018, December. Image understanding: Semantic Segmentation of Graphics and Text using Faster-RCNN. In 2018 International Conference on Networking, Embedded and Wireless Systems (ICNEWS) (pp. 1-6). IEEE.
  8. Kumar, K. S., Subramani, G., Thangavel, S. K., & Parameswaran, L. (2021). A mobile-based framework for detecting objects using ssd-mobilenet in an indoor environment. In Intelligence in Big Data Technologies—Beyond the Hype (pp. 65-76). Springer, Singapore.
  9. Younis, A., Shixin, L., Jn, S., & Hai, Z. (2020, January). Real-time object detection using pre-trained deep learning models MobileNet-SSD. In Proceedings of 2020 the 6th International Conference on Computing and Data Engineering (pp. 44-48).
  10. Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, & Hartwig Adam, https://scholar.google.com.my/citations?view_op=view_citation&hl=tr&user=yFMX138AAAAJ&citation_for_view=yFMX138AAAAJ:abG-DnoFyZgC

Copyright @ 2026-2017 IRJIET. All Right Reserved.

Developed by Byzero Technologies