 |
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)
|
Issue: July 2026
Volume 11 | Issue 7
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor 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 : 122
Article Submitted : 25330
Article Published : 9497
Total Authors : 25208
Total Reviewer : 873
Total Countries : 172
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | Agentic AI and Geospatial Intelligence Framework for Smart Government Infrastructure Monitoring, Predictive Analytics, and Decision Support Systems. |
| Authors Name: | PALAGUMMI SYAM KUMAR , N JEEVANA DHEEPA , G. KRUPA HAVILAH , KOYYALA SRAVANI |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_213450
|
| Published Paper Id: | IJRTI2606069 |
| Published In: | Volume 11 Issue 6, June-2026 |
| DOI: | |
| Abstract: | Smart government infrastructure management requires real-time monitoring, accurate prediction, and efficient decision-making to ensure sustainable development and optimal resource utilization. Traditional monitoring systems often suffer from limited automation, delayed analysis, and lack of integrated geospatial intelligence, leading to inefficiencies in infrastructure planning and maintenance. This paper proposes an Agentic AI and Geospatial Intelligence Framework for smart government infrastructure monitoring, predictive analytics, and decision support systems. The proposed framework integrates autonomous AI agents with geospatial data processing techniques to continuously analyze infrastructure conditions using satellite imagery, GIS data, and sensor-based inputs. Agentic AI modules are designed to independently perform data collection, anomaly detection, predictive modeling, and recommendation generation with minimal human intervention. The predictive analytics component leverages machine learning techniques to forecast infrastructure risks such as structural degradation, construction delays, and cost overruns. Additionally, a decision support system is developed to assist government authorities by providing intelligent alerts, visualization dashboards, and optimized action strategies based on real-time geospatial insights. Experimental evaluation demonstrates that the proposed framework enhances prediction accuracy, reduces response time, and improves decision efficiency compared to conventional monitoring approaches. The integration of Agentic AI with geospatial intelligence provides a scalable and adaptive solution for modern smart governance challenges. |
| Keywords: | Agentic AI, Geospatial Intelligence, Smart Government Infrastructure, Infrastructure Monitoring Systems, Predictive Analytics, Decision Support Systems, Artificial Intelligence Agents, Geographic Information Systems, Real-time Data Analytics, Machine Learning for Prediction, Remote Sensing Data Analysis, Smart City Technologies, Autonomous AI Systems, Risk Prediction and Assessment, Data-driven Governance |
| Cite Article: | " Agentic AI and Geospatial Intelligence Framework for Smart Government Infrastructure Monitoring, Predictive Analytics, and Decision Support Systems.", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 6, page no.a674-a692, June-2026, Available :http://www.ijrti.org/papers/IJRTI2606069.pdf |
| Downloads: | 00088 |
| 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: IJRTI2606069
Registration ID:213450
Published In: Volume 11 Issue 6, June-2026
DOI (Digital Object Identifier):
Page No: a674-a692 Country: Amalapuram, Andhra Pradesh, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2606069 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2606069 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
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
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2026 - All Rights Reserved - IJRTI | |||