Browsing by Author "Faysal, Md Anowar Hossen"

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    A Cost-Effective IoT Device for Protecting People from the Dangers of Environmental Risk in Bangladesh
    (Daffodil International University, 2022-07-29) Rimi, Mahmuda Mahfuz; Ahmed, Md Rasel; Hossan, Sakhawat; Rahaman, Md Masudur; Faysal, Md Anowar Hossen; Foysal, Md. Ferdouse Ahmed
    The factors of population growth, unplanned urbanization, vehicles, factories, and brick kilns are constantly making air quality concerns. In addition, due to lack of public awareness, people are continually facing various kinds of unintended accidents, for example, gas cylinder poisoning. The main objective of our paper is to create a low-cost Internet of Things (IoT) based system that can measure atmospheric air quality and gas leakage. Sensitive data will be stored on the server via the Internet of Things (IoT) device, which will visualize the data from the server via the website and the Android app. Moreover, by understanding the state of the environment, the user will be informed about the environment through Android apps and websites to protect himself from the grip of air pollution and protect himself before an accident like a gas cylinder.
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    A Data Analysis Technique to Find the Environmental Effect on Egg Production in the Poultry Farm Using ML and IOT
    (Daffodil International University, 2022-05-18) Siddika, Ayesha; Faysal, Md Anowar Hossen; Ahmed, Md Rasel; Rahaman, Md Masudur; Ali, Mohammad; Foysal, Md. Ferdouse Ahmed
    Environmental maintenance of the poultry house is essential for maintaining the excellent health of the poultry as the rate of egg production is disrupted due to illness. Our main objective is to find real-time environmental impact using IoT and machine learning to ensure optimal egg production in the poultry industry, an unimaginable change for the poultry industry. Environmental data such as Temperature, Humidity, Ammonia, Light Intensity, Noise which affect the egg production, have been measured through low-cost IoT devices. The collected data has been kept on the online server. Through our website and Android app, we will send messages to poultry farmers by combining the collected environmental data with standard data to be aware of the status of their poultry farms. The server analyzes the stored data using machine learning algorithms on how to maximize egg production based on poultry farm environment conditions. As a result, the poultry industry can be transformed into a profitable industry with unimaginable changes.