IJRTI
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.14

Issue per Year : 12

Volume Published : 11

Issue Published : 117

Article Submitted : 21307

Article Published : 8476

Total Authors : 22301

Total Reviewer : 802

Total Countries : 156

Indexing Partner

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: Smart Waste Management through IoT, Chat bots, and Large Language Models
Authors Name: SIDDHARTH PATEL
Download E-Certificate: Download
Author Reg. ID:
IJRTI_206260
Published Paper Id: IJRTI2509073
Published In: Volume 10 Issue 9, September-2025
DOI:
Abstract: The ongoing rapid growth of urbanization and industrial dynamics has made waste management issues more challenging to address globally, demonstrating the limitations of existing systems. With static schedules, no regular monitoring and minimal community involvement inefficiencies have resulted in delays, increased costs, and detrimental environmental impacts. This paper presents an integrated framework that leverages the Internet of Things (IoT), chatbots, and Large Language Models (LLMs) to overcome realised constraints. IoT-based smart bins provide a multitude of real-time data related to fill levels, hazardous emissions, disposal habits, while chatbots promote community input, awareness, and complaints resolution in multiple languages. LLMs process the variety of data received to produce predictive analytics and improve waste collection practices. The prototype was tested on residential, commercial, and industrial sites. The impact on waste management was sizeable - a 35% improvement of collection efficiency, a 20% improvement of fuel efficiency; community satisfaction was improved; and the data resulted in improvements in collection methods and schedules. In conclusion, the study demonstrates that IoT - chatbots and LLMs can help to convert waste management into a far more predictive, data and community engaged process. In addition to modus operandi gains efficiency, the framework approach is also environmentally beneficial relative to existing models, and offers communities an easy, scalable transition to a more robust smart city model.
Keywords: Smart Waste Ecosystems, Predictive Sanitation Systems, IoT–LLM Synergy, Intelligent Resource Optimization, Citizen-Centric Waste Solutions, Urban Sustainability Technologies.
Cite Article: "Smart Waste Management through IoT, Chat bots, and Large Language Models", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 9, page no.a655-a659, September-2025, Available :http://www.ijrti.org/papers/IJRTI2509073.pdf
Downloads: 0001457
ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2509073
Registration ID:206260
Published In: Volume 10 Issue 9, September-2025
DOI (Digital Object Identifier):
Page No: a655-a659
Country: BHOPAL, MADHYA PRADESH, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2509073
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2509073
Share Article:

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from www.ijrti.org
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX DOAJ : Directory of Open Access Journals
DRJI Index Copernicus International Scribd DocStoc

ISSN Details

ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI.ONE
How to Get DOI?

Conference

Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Join RMS/Earn 300

IJRTI

WhatsApp
Click Here

Indexing Partner