Abstract
In fast-growing industrial societies, large amounts of emitted dust and energy (e.g., fossil fuels) consumed by human activities can cause climate change, problems to human health, and resource depletion. In particular, due to a considerable amount of dust emissions and energy consumption, energy-intensive construction sites are causing global environmental problems capable of destroying the environment and possibly damaging the health of both construction workers and the surrounding population. Therefore, this study aimed to develop a framework for reducing dust emissions and energy consumption on construction sites. The proposed framework was developed in six steps: (i) Step 1: Selection of the key factors affecting dust emissions and energy consumption on construction sites; (ii) Step 2: Development of real-time monitoring devices for dust emissions and energy consumption using sensor networks; (iii) Step 3: Development of real-time evaluation methods for dust emissions and energy consumption using big data; (iv) Step 4: Establishment of real-time improvement solutions for dust emissions and energy consumption using machine learning; (v) Step 5: Systemization of real-time monitoring devices, evaluation methods and improvement solutions for dust emissions and energy consumption; and (vi) Step 6: Development of an intelligent system for automatically managing dust emissions and energy consumption on construction sites. As a result, an intelligent system can be developed capable of automatically managing dust emissions and energy consumption from construction sites by using the proposed framework. The proposed framework can be used at a construction site to conduct real-time monitoring, evaluation, and the minimization of dust emissions and energy consumption depending on the characteristics of the construction site. In addition, it can also be used to reduce other various environmental issues (i.e., noise and vibration) and economic issues (i.e., cost of litigation, additional construction), which are often produced in the construction phase.
Original language | English |
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Pages (from-to) | 5092-5096 |
Number of pages | 5 |
Journal | Energy Procedia |
Volume | 158 |
DOIs | |
Publication status | Published - 2019 |
Event | 10th International Conference on Applied Energy, ICAE 2018 - Hong Kong, China Duration: 2018 Aug 22 → 2018 Aug 25 |
Bibliographical note
Funding Information:This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean (MSIP; Ministry of Science, ICT & Future Planning) (NRF-2018R1A2A1A19020868).
Publisher Copyright:
© 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of ICAE2018 - The 10th International Conference on Applied Energy.
All Science Journal Classification (ASJC) codes
- Energy(all)