International Journal of Innovative Computer Science and IT Research

E-ISSN: 3067-1108

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Monthly Scholarly International Journal

Call for Paper Volume 2 Issue 9 September 2026 Submit your research before last 3 days of this month to publish your research paper in the issue of September.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 2 Issue 9
September 2026

Submit your research paper

Robotics and AI in Disaster Recovery: Autonomous Assessment, Infrastructure Inspection and Emergency Logistics

Author(s) Natt Leelawat
Country Thailand
Abstract Disaster recovery depends on timely situational assessment, safe infrastructure inspection, reliable communication, and equitable delivery of emergency supplies. Conventional recovery operations are often constrained by damaged roads, unstable structures, hazardous materials, disrupted communication, incomplete information, and continuing environmental threats. Robotics and artificial intelligence can strengthen these operations through aerial mapping, ground-based inspection, automated damage recognition, structural monitoring, route optimization, and last-mile logistics. This paper develops an integrated framework for applying robotics and AI across post-disaster assessment, infrastructure inspection, and emergency distribution.
A conceptual and simulation-based methodology compares initial damage-assessment completion times under conventional and robotics–AI-integrated configurations. Forty-eight illustrative incident observations are modeled, with twenty-four observations in each configuration. Conventional assessment records a simulated mean completion time of 13.7 hours, compared with 5.4 hours for the integrated configuration, representing an illustrative reduction of 60.5%. These values are not operational evidence and do not support causal inference.
The analysis indicates that autonomous systems may accelerate data collection, but their effectiveness depends on validated sensing, interoperable information, human command authority, communication resilience, cybersecurity, community knowledge, and transparent prioritization. The study proposes a staged deployment model combining mission definition, technology verification, supervised field operation, multi-source data fusion, accountable decision-making, and post-mission evaluation. It concludes that robotics and AI should extend the reach and safety of emergency personnel rather than operate as unaccountable substitutes for human judgment.
Keywords disaster robotics, artificial intelligence, damage assessment, infrastructure inspection, emergency logistics, unmanned aerial systems, humanitarian response, resilient recovery.
Field Engineering
Published In Volume 2, Issue 9, September 2026
Published On 2026-09-05
View / Download PDF File

Share this



E-ISSN: 3067-1108
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJICSITR DOI prefix is
10.00000/IJICSITR

Downloads
Research Paper Format Copyright Permission and Undertaking Form

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJICSITR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +1-872-302-3851 editor@uscse.com