Smart E-Auction Platform with AI Chatbot and Automated Systems: Review

References

[1] Abood, Israa Nasir, and Ghaidaa Abdul Aziz Al- Talib. "Waste Classification Using Artificial Intelligence Techniques: Literature Review." Technium, vol. 5, 2023, pp. 49-59.

[2] Ambika, M., and K. E. Kannammal. "Deep Learning Approaches for Waste Classification: A Comprehensive Review and Analysis." International Journal of Creative Research Thoughts (IJCRT), vol. 11, no. 6, 2023, pp. c940- c943.

[3] Chu, Yinghao, et al. "Multilayer Hybrid Deep- Learning Method for Waste Classification and Recycling." Computational Intelligence and Neuroscience, vol. 2018, 2018, 5060857,

[4] Dsouza, Justin John. "Waste Management Using Machine Learning." International Journal of Research Publications and Reviews, vol. 5, no. 10, 2024, pp. 1050-1055.

[5] Kaya, Volkan. "Classification of Waste Materials with a Smart Garbage System for Sustainable Development: A Novel Model." Frontiers in Environmental Science, vol. 11, 2023, 1228732,

[6] Lu, M., and F. Li. "Survey on Lie Group Machine Learning." Big Data Mining and Analytics, vol. 3, no. 4, 2020, pp. 235 -258,

[7] Pawar, Abhishek S., et al. "SMART SORT: AI- POWERED WASTE SEGREGATION USING EDGE IMPULSE STUDIO." International Journal of Creative Research Thoughts (IJCRT), vol. 12, no. 5, 2024, pp. k925-k936.

[8] Pillai, Kiran S., et al. "Municipal Solid Waste Management: A Review of Machine Learning Applications." E3S Web of Conferences, vol. 455, 2023, 02018,

[9] Rajubhai, Pavar Tarunkumar. "AI-POWERED SMART WASTE MANAGEMENT: TRANSFORMING URBAN SUSTAINABILITY." International Research Journal of Modernization in Engineering Technology and Science, vol. 7, no. 3, 2025, pp. 9422-9425.

[10] Chan, Jia Yi, and Chong Fong Kim. "AI- Powered Waste Classification Using Convolutional Neural Networks (CNNs)." International Journal of Advanced Computer Science and Applications, vol. 15, no. 10, 2024, pp. 67-75.

[11] Xia, Wanjun, et al. "Application of Machine Learning Algorithms in Municipal Solid Waste Management: A Mini Review." Waste Management & Research, vol. 40, no. 6, 2022, pp. 609-624,

[12] Khan, Haroon Ahmed, et al. "Enhancing Trash Classification in Smart Cities Using Federated Deep Learning." Scientific Reports, vol. 14, 2024, 11816,

[13] Gunaseelan, Jenilasree, Sujatha Sundaram, and Bhuvaneswari Mariyappan. "A Design and Implementation Using an Innovative Deep- Learning Algorithm for Garbage Segregation." Sensors, vol. 23, no. 18, 2023, pp. 7963-7981,

[14] Ramos, Edgar, Arminda Guerra Lopes, and Fábio Mendonça. "Application of Machine Learning in Plastic Waste Detection and Classification: A Systematic Review." Processes, vol. 12, no. 8, 2024, p. 1632,

[15] Belsare, Karan, et al. "Wireless Sensor Network- Based Machine Learning Framework for Smart Cities in Intelligent Waste Management." Heliyon, vol. 10, 2024, e36271,

[16] Alourani, Abdullah, M. Usman Ashraf, and Mohammed Aloraini. "Smart Waste Management and Classification System Using Advanced IoT and AI Technologies." PeerJ Computer Science, 2025, e2777,

[17] Olawade, David B., et al. "Smart waste management: A paradigm shift enabled by artificial intelligence." Waste Management Bulletin, vol. 2, 2024, pp. 244-263,

[18] Fang, Bingbing, et al. "Artificial intelligence for waste management in smart cities: a review." Environmental Chemistry Letters, 2023,

[19] Guo, Hao-nan, et al. "Application of machine learning methods for the prediction of organic solid waste treatment and recycling processes: A review." Journal of Cleaner Production, vol. 278, 2021, 123971,

@article{1712791,
      author = {Ekatva Awasthi, Divyashree S, Gagan M, Gurunandan},
      title = {Smart E-Auction Platform with AI Chatbot and Automated Systems: Review},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {6},
      pages = {1090-1094},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1712791.pdf},
      abstract = {The growing need for transparency, security, and fairness in online auction systems has highlighted the limitations of conventional centralized platforms, which are often prone to data manipulation, fraudulent activities, and lack of trust among participants. This research proposes a Blockchain-powered E-Auction Platform that leverages smart contracts and decentralized ledger technology to ensure secure, transparent, and tamper-proof bidding processes To enhance user engagement and communication, the platform integrates an AI-powered chatbot that acts as an intelligent mediator between buyers and sellers. The chatbot assists users throughout the auction process?answering queries, providing product details, guiding new participants, and facilitating smooth negotiation, this ensure a proper negotiation and commnucication between the buyer and the seller at all points of time.},
      keywords = {E-Auction, Blockchain, Smart Contracts, Decentralization, Transparency, Security, AI Chatbot, Buyer-Seller Interaction, Web Application, , Automation, Fair Bidding, Digital Marketplace},
      month = {December},
      doi = {https://doi.org/10.64388/IREV9I6-1712791}
  }