IoT-Driven Environmental Monitoring and Healthcare System: Shipbreaking Industry Perspective

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    IoT-Driven Environmental Monitoring and Healthcare System: Shipbreaking Industry Perspective

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    IoT-Driven Environmental Monitoring and Healthcare System Shipbreaking Industry Perspective2.pdf (17.28Mb)
    Date
    2023-07-29
    Author
    Ahmed, Afsana
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    Abstract
    coastal region of Bangladesh has ecological importance with high bio diversity. Although Bangladesh is one of the world’s top shipbreaking coun tries, business activities have seriously harmed the coastal ecosystem. The workers are subject to a hazardous environment that leaves them suscep tible to a wide range of health disorders. The main goal of this study is to represent the situation of the shipbreaking industry regarding environ mental pollution and realize the health condition of the workers. In this work, we have proposed an Internet of Things (IoT) based outdoor envi ronment monitoring system where we have collected real-time data using 5 parameters like - temperature, humidity, dew point, surface pressure, and PM2.5 from Sitakunda Shipbreaking Industry. Cloud server have been used to upload and keep long-term storage of IoT data. We have also collected 2373 past data for the last 7 years (January 2016-June 2022) from NASA Power View, US Console Dhaka, and the Ministry of Environment Forests Bangladesh. We have made a health survey of different 6 hospitals in the Chittagong division for the health dataset, which is the unique and most challenging part of our work. From these past datasets and health surveys, we have analyzed the environmental pollution and also found in which sea son the risk factor of worker’s health in the shipbreaking industry is “high”, “medium” or “low”. Then, we have built our model using various Machine Learning (ML) algorithms e.g., Decision Tree, Random Forest, KNN, Ex tra Tree Classifier, and Ensemble Method, and find better accuracy which is - 78.96%, 81.78%, 76.36%, 80.69%, and 80.04% respectively, where the Random Forest Classifier gives the best accuracy. Finally, based on our implementation a solution is identified to detect the affected rate of the environment and the healthy environment margin. This solution is mainly based on the Sitakunda area which will help to estimate and send the threats about shipbreaking industries to the public.
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    http://dspace.uiu.ac.bd/handle/52243/2826
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