KEYNOTE SPEECH

2024. 7. 23.(TUE) AM 10:15-11:05  - International Conference Hall(2F)

Speaker : Young-Woo Kwon (Kyungpook National University)

Title :  Disaster Analysis and Management using IoT, Cloud, and AI (From IoT to Cloud via AI)

Abstract:

The increasing number of disasters necessitates advanced solutions for disaster analysis and management. In this talk , I introduce a comprehensive framework that leverages the Internet of Things (IoT), cloud computing, and artificial intelligence (AI) to enhance disaster preparedness, response, and recovery efforts. IoT devices, such as sensors and cameras, are deployed to monitor environmental conditions, infrastructure, and human activities. The collected data is transmitted to the cloud, where it is stored, aggregated, and preprocessed. AI algorithms, including machine learning and deep learning models, are then applied to analyze the data, identify patterns, predict potential risks, and generate actionable insights.

By harnessing the power of IoT, Cloud, and AI, we aim to improve situational awareness, enhance response capabilities, mitigate the impact of disasters, and accelerate recovery efforts. We also discuss the potential benefits, challenges, and future directions for disaster analysis and management.

2024. 7. 23.(TUE) PM 13:30-14:20  - Conference Room 1(1F)

Speaker : Wen-Huang Cheng (University Distinguished Chair Professor of National Taiwan University)

Title : Launching a New AI Era with Large Vision Model (LVM) Agents

Abstract:

This talk will delve into the latest advancements in the field of artificial intelligence (AI), particularly the breakthrough achievements of large vision model (LVM). LVMs have demonstrated unprecedented capabilities in understanding and generating natural language, images, and complex data. Additionally, we will focus on LVM based AI Agents, an emerging research area. The introduction of AI Agents signifies a new height in AI applications; they can autonomously learn, make decisions, and execute tasks, significantly enhancing the practicality and intelligence of systems. However, in practical applications, AI Agents also face numerous technical challenges, such as the hallucination problem of large models, which can lead to the generation of incorrect information. This presentation will summarize the latest research progress and application challenges of LVMs and AI Agents, helping technology practitioners and researchers better grasp and utilize these cutting-edge technologies, and explore the infinite possibilities of the new era of artificial intelligence.