Short Paper: AI-Driven Disaster Warning System: Integrating Predictive Data with LLM for Contextualized Guideline Generation DOI

Md. Abrar Faiaz,

Nowshin Nawar

Published: Dec. 19, 2024

Language: Английский

Accuracies of large language models in answering radiation protection questions DOI Creative Commons
Eren Çamur, Turay Cesur, Yasin Celal Güneş

et al.

Journal of Radiological Protection, Journal Year: 2024, Volume and Issue: 44(2), P. 024501 - 024501

Published: May 20, 2024

Language: Английский

Citations

6

Reinventing instructional laboratory with ChatGPT: Radiation measurement by smartphone DOI
Chitnarong Sirisathitkul, Yaowarat Sirisathitkul

Innovations in Education and Teaching International, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 16

Published: Feb. 14, 2025

Language: Английский

Citations

0

Combination of Large Language Models and Portable Flood Sensors for Community Flood Response: A Preliminary Study DOI Open Access
Tinghai Ou, Tsun-Hua Yang,

Pei‐Zen Chang

et al.

Water, Journal Year: 2025, Volume and Issue: 17(7), P. 1055 - 1055

Published: April 2, 2025

The effectiveness of early warning systems can help people take action to mitigate the impact extreme weather events once warnings are issued. developed by public agencies usually issue standard messages that, in many situations, may not affect all who receive messages. In long run, this lead behaviors respond relevant warnings, resulting inefficiency. Users demand faster and more customized information that matches their needs, such as “How does me right now?” or “What I do impact?” This study proposes a decentralized framework at community level includes custom Internet Things (IoT) sensors for timely monitoring large language models (LLMs) generation user-defined have advantages easy installation, low cost, affordable maintenance fees. trained LLMs expedite processing given specific prompts generate response users. addition, is established within serverless environment, enabling rapid deployment scalability. integration IoT demonstrates how system performs detect flooding deliver real-time, efficient, localized action-ready different scenarios. combination significantly enhances responsiveness during flood events.

Language: Английский

Citations

0

From Epidemiology to Education: The Bernard Wheatley Award for 2024 DOI
M C Thorne

Journal of Radiological Protection, Journal Year: 2025, Volume and Issue: 45(2), P. 020201 - 020201

Published: April 11, 2025

Language: Английский

Citations

0

Artificial Intelligence as Enabler for Adoption of Sustainable Nuclear-Powered Maritime Ships: Challenges and Opportunities DOI Open Access
Miltiadis Alamaniotis, Dinos Ipiotis

Sustainability, Journal Year: 2025, Volume and Issue: 17(8), P. 3654 - 3654

Published: April 18, 2025

Decarbonization stands as one of humanity’s most pressing challenges, demanding collective efforts from multiple sectors to meet established goals. The transportation industry plays a pivotal role in this endeavor, with the maritime sector offering significant potential reduce emissions. As cornerstone global goods and commodity transport, is uniquely positioned contribute meaningfully drive for lower carbon Artificial intelligence (AI), its profound influence across diverse domains, anticipated play vital supporting nuclear shipping on path decarbonized future. Specifically, AI provides tools make power ships more economically viable solution while enhancing safety security systems. This paper explores an enabler adopting nuclear-powered ships, delving into challenges opportunities associated their implementation. Ultimately, it highlights AI’s fostering sustainable solutions, which align achieving decarbonization

Language: Английский

Citations

0

Generative AI in Cyber Security of Cyber Physical Systems: Benefits and Threats DOI
Harindra S. Mavikumbure, Victor Cobilean, Chathurika S. Wickramasinghe

et al.

Published: July 8, 2024

Language: Английский

Citations

2

Short Paper: AI-Driven Disaster Warning System: Integrating Predictive Data with LLM for Contextualized Guideline Generation DOI

Md. Abrar Faiaz,

Nowshin Nawar

Published: Dec. 19, 2024

Language: Английский

Citations

0