Parameter selection of the G-IoT-enabled model for a sustainable campus
The development of G-IoT-enabled models for sustainable campuses represents a significant step towards achieving eco-friendly and efficient educational environments. Integrating G-IoT technologies into the development of sustainable campuses has become an increasingly essential task for enhancing en...
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| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | en |
| Published: |
IEEE
2024
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| Subjects: | |
| Online Access: | https://umpir.ump.edu.my/id/eprint/43731/1/1_Parameter_Selection_of_the_G-IoT-Enabled_Model_for_a_Sustainable_Campus.pdf https://umpir.ump.edu.my/id/eprint/43731/ https://doi.ieeecomputersociety.org/10.1109/ICoCSIM65098.2024.00050 |
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| Summary: | The development of G-IoT-enabled models for sustainable campuses represents a significant step towards achieving eco-friendly and efficient educational environments. Integrating G-IoT technologies into the development of sustainable campuses has become an increasingly essential task for enhancing energy efficiency and reducing environmental impact globally. Despite this imperative, the complexity of selecting optimal parameters for developing a G-IoT-enabled model poses a notable challenge. This paper introduces an approach for selecting parameters essential to developing a G IoT-enabled model aimed at fostering sustainable campus environments. This study conducts a comprehensive overview to identify parameters involved in developing this model toward energy efficiency from existing works. By identifying parameters related to energy efficiency, CO2 emission, sensors, and renewable energy integration, the study aims to provide a model for a campus that enhances sustainability and operational performance. The outcomes of this study emphasize the importance of precise parameter selection in the efficacy of G-IoT systems for the sustainable campus. This research is a crucial step towards realizing eco-friendly campuses, showcasing how G-IoT can transform traditional campuses into sustainable systems by integrating parameters. |
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