Building a Sustainable Development Education System for Large Organizations Based on Artificial Intelligence of Things

This paper proposes building a sustainable development computing system for large organizations based on AI and IoT. The system leverages AI to calculate the carbon emissions caused by large organizations' activities and utilizes IoT devices to monitor and compute environmental coefficients. The system also employs automated devices to achieve net-zero carbon emissions. By integrating weather forecast information from meteorological agencies to understand external environmental conditions, and by consulting a knowledge database to devise appropriate response strategies, the AI system can activate relevant equipment to improve both the organization's living environment and carbon emission processes. The feasibility and practical application of this system will be demonstrated through actual simulations to enhance its viability and effectiveness.

Authors

Institutions

Publication Details

Journal
Journal of Organizational and End User Computing
Published
2024-11-29
DOI
https://doi.org/10.4018/joeuc.361716
Citations
16
Primary Topic
Fire Detection and Safety Systems
Type
article
Field-Weighted Citation Impact
5.83
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Building a Sustainable Development Education System for Large Organizations Based on Artificial Intelligence of Things

Hsin‐Te Wu, Mu‐Yen Chen, Jianping Li
16 citations
Journal of Organizational and End User Computing
Fire Detection and Safety Systems
5.83
article

Building a Sustainable Development Education System for Large Organizations Based on Artificial Intelligence of Things

Hsin‐Te Wu, Mu‐Yen Chen, Jianping Li
article en
16 citations

Abstract

This paper proposes building a sustainable development computing system for large organizations based on AI and IoT. The system leverages AI to calculate the carbon emissions caused by large organizations' activities and utilizes IoT devices to monitor and compute environmental coefficients. The system also employs automated devices to achieve net-zero carbon emissions. By integrating weather forecast information from meteorological agencies to understand external environmental conditions, and by consulting a knowledge database to devise appropriate response strategies, the AI system can activate relevant equipment to improve both the organization's living environment and carbon emission processes. The feasibility and practical application of this system will be demonstrated through actual simulations to enhance its viability and effectiveness.

Journal of Organizational and End User ComputingVol. 36(1)
National Taitung University (TW), National Cheng Kung University (TW)
Openalex Percentile: Top 3%
Fire Detection and Safety Systems
5.83
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Building a Sustainable Development Education System for Large Organizations Based on Artificial Intelligence of Things — Hsin‐Te Wu, Mu‐Yen Chen, et al. · Journal of Organizational and End User Computing (2024) | TGRS Research Map | TGRS