{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T16:15:25Z","timestamp":1778256925231,"version":"3.51.4"},"reference-count":46,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2023,7,17]],"date-time":"2023-07-17T00:00:00Z","timestamp":1689552000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Regional Development Fund through the Operational Program \u201cScience and Education for Smart Growth\u201d","award":["UNITe BG05M2OP001-1.001-0004-C01\/28.02.2018"],"award-info":[{"award-number":["UNITe BG05M2OP001-1.001-0004-C01\/28.02.2018"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>An accident during the transport of liquefied petroleum gas (LPG) via a tanker vehicle leads to the leakage of a flammable substance, causing devastation. In such a situation, the appropriate action with the shortest possible delay can minimize subsequent losses. However, the decision-making mechanism remains unable to detect the occurrence of an accident and evaluate its extent within the critical time. This paper proposes an automatic framework for leakage detection and its consequence prediction during the external transportation of LPG using artificial intelligence (AI) and the internet of things (IoT). An AI model is developed to predict the probable consequences of the accident in terms of the diameter of risk contours. An IoT framework is proposed in which the developed AI model is deployed in the edge device to detect any leakage of gas during transportation, to predict its probable consequences, and to report it to the remotely located disaster management team for initiating appropriate action. A prototype of the proposed model is built and its performance is successfully tested. The proposed solution would significantly help to identify efficient disaster management techniques by allowing for quick leakage detection and the prediction of its probable consequences.<\/jats:p>","DOI":"10.3390\/s23146473","type":"journal-article","created":{"date-parts":[[2023,7,18]],"date-time":"2023-07-18T01:46:02Z","timestamp":1689644762000},"page":"6473","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["AI-Enabled IoT Framework for Leakage Detection and Its Consequence Prediction during External Transportation of LPG"],"prefix":"10.3390","volume":"23","author":[{"given":"Amiya","family":"Dash","sequence":"first","affiliation":[{"name":"School of Engineering and Technology, BML Munjal University, Gurugram 122413, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuvabrata","family":"Bandopadhay","sequence":"additional","affiliation":[{"name":"School of Physical Sciences, Banasthali Vidyapith University, Rajasthan 304022, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2157-3487","authenticated-orcid":false,"given":"Soumya Ranjan","family":"Samal","sequence":"additional","affiliation":[{"name":"Faculty of Telecommunications, Technical University of Sofia, 1756 Sofia, Bulgaria"},{"name":"Department of Electronics and Communication Engineering, Silicon Institute of Technology, Bhubaneswar 751024, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3226-5639","authenticated-orcid":false,"given":"Vladimir","family":"Poulkov","sequence":"additional","affiliation":[{"name":"Faculty of Telecommunications, Technical University of Sofia, 1756 Sofia, Bulgaria"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,17]]},"reference":[{"key":"ref_1","unstructured":"(2022, January 02). 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