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.
|Number of pages||5|
|Publication status||Published - 2019 Jan 1|
|Event||10th International Conference on Applied Energy, ICAE 2018 - Hong Kong, China|
Duration: 2018 Aug 22 → 2018 Aug 25
All Science Journal Classification (ASJC) codes