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The Advancement of an Automated Guided Vehicle (AGV) For Fire Surveillance System
Örebro University, School of Science and Technology. (Digitalized product and production development)ORCID iD: 0000-0001-6869-7180
Örebro University, School of Science and Technology. (Digitalized product and production development)ORCID iD: 0000-0002-2014-1308
2026 (English)In: Computational Intelligence in Surveillance Systems Using Image Processing / [ed] Jay Kumar Pandey; Mritunjay Rai; Momina Shaheen; Faizan Ahmad, Elsevier, 2026, p. 249-262Chapter in book (Refereed)
Abstract [en]

The development of sophisticated fire monitoring systems is a result of the growing demand for fire prevention and management in large indoor buildings. Since they can monitor fire-prone regions in real time and move autonomously, automated guided vehicles (AGVs) have shown great promise as a solution. This chapter elaborates on the creation of an AGV specifically designed for fire monitoring. The AGV guarantees a thorough coverage with its mecanum wheels for 360° mobility, a camera, and flame sensors for early detection. Risks of external interference are reduced by the mapping line following sensors and automated guidance. It also has an alarm system with timely fire detection notifications and a WIFI video transmission module, which is a major improvement in proactive fire monitoring for improved safety in a variety of scenarios. By lowering human interaction, speeding up detection, and offering extensive surveillance coverage, this work seeks to improve fire safety. Where constant human monitoring is unfeasible, the AGV-based fire surveillance system provides a scalable and effective solution for commercial and industrial sites.

Place, publisher, year, edition, pages
Elsevier, 2026. p. 249-262
National Category
Mechanical Engineering Robotics and automation
Research subject
Mechanical Engineering
Identifiers
URN: urn:nbn:se:oru:diva-123248DOI: 10.1016/B978-0-443-36408-2.00021-7ISBN: 9780443364099 (electronic)ISBN: 9780443364082 (print)OAI: oai:DiVA.org:oru-123248DiVA, id: diva2:1993492
Available from: 2025-08-30 Created: 2025-08-30 Last updated: 2026-03-19Bibliographically approved

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Patil, Rajesh V.Löfstrand, Magnus

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CiteExportLink to record
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Citation style
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