Atsiliepimai
Aprašymas
The two-volume set LNICST 648 and 649 constitutes the refereed post-conference proceedings of the 10th EAI International Conference on Smart Objects and Technologies for Social Goods, GOODTECHS 2024, held in Can Tho, Vietnam, during December 19–20, 2024.
The 17 full papers and 27 short papers included in these volumes were carefully reviewed and selected from 102 submissions. They focus on a wide range of advancements in smart technologies aimed at promoting social good. Key topics include cutting-edge research in Internet of Things (IoT) security, innovative applications of artificial intelligence in domains such as healthcare, education, and environmental monitoring, and energy-efficient systems. They were organized in topical sections as follows:
Part I: Advances in Artificial Intelligence, Machine Learning, and Blockchain Applications Across Diverse Domains
Part II: Innovations in Energy-Based Models, and Advanced Predictive Systems Across Diverse Domains
EXTRA 15 % nuolaida su kodu: ENG15
Akcija baigiasi už 4d.09:55:29
Nuolaidos kodas galioja perkant nuo 10 €. Nuolaidos nesumuojamos.
The two-volume set LNICST 648 and 649 constitutes the refereed post-conference proceedings of the 10th EAI International Conference on Smart Objects and Technologies for Social Goods, GOODTECHS 2024, held in Can Tho, Vietnam, during December 19–20, 2024.
The 17 full papers and 27 short papers included in these volumes were carefully reviewed and selected from 102 submissions. They focus on a wide range of advancements in smart technologies aimed at promoting social good. Key topics include cutting-edge research in Internet of Things (IoT) security, innovative applications of artificial intelligence in domains such as healthcare, education, and environmental monitoring, and energy-efficient systems. They were organized in topical sections as follows:
Part I: Advances in Artificial Intelligence, Machine Learning, and Blockchain Applications Across Diverse Domains
Part II: Innovations in Energy-Based Models, and Advanced Predictive Systems Across Diverse Domains
Atsiliepimai