Kruekaew, Boonhatai

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Kruekaew, Boonhatai
Alternative Name
Kruekaew, B.
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Email
boonhatai.kr@kmitl.ac.th

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    Item type:Publication,
    STRAWBERRY SEEDLING CULTIVATION WITH SMART FARM
    (2025-01-01)
    Kruekaew, Boonhatai
    ;
    Palananda, Attapon
    ;
    Kimpan, Warangkhana
    In Thailand, the main planting areas are in the upper northern region. It is difficult for strawberry to be cultivated in the central region of Thailand due to inappropriate weather conditions. Because the strawberry seedlings are delicate and sensitive to alterations in temperature and weather, they require extra care than mature plants while cultivation before planting. Therefore, modifications to strawberry seedling cultivation may result in more strawberry plantings. Consequently, one of the most beneficial choices is a smart farming. This research focuses on the cultivation of strawberry seedlings in tropical areas of Thailand using an intelligence model and Internet of Things. The prototype system focuses on automatic watering and lighting, and an environmental adaptation system that combines sensors to control water, air, and lighting. The physical characteristics data from all devices in prototype system are collected, and then analyzed using machine learning methods to automatically control the environment within the prototype system to be suitable for growing strawberry seedlings. Moreover, the real-time data will be displayed on a dashboard with various notification systems. The experimental results indicated that using machine learning models can control the suitable temperature and humidity for strawberry seedlings cultivation. The appropriate temperature and soil moisture are between 31-32 degrees Celsius and 70 percent, respectively.
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    Automation 4.0 for Water Level Monitoring System
    (2023-01-01)
    Kimpan, Warangkhana
    ;
    Palananda, Attapon
    ;
    Kruekaew, Boonhatai
    This paper proposed the concept of using automation 4.0 for monitoring the water level. The water level warning system specifications are to measure the water level using ultrasonic sensors and measure the amount of rainfall using a weighing rain gauge. The system automatically controls the measurement of the level of the flood using a Programmable Logic Controller (PLC) via PROFINET. Then the water level is monitored, and the results will be displayed through HMI technology via Web panel trainer, Node-Red dashboard, and transfer data via PROFICLOUD. Moreover, the warning information will be sent via LINE notification on mobile to people who live near water sources or staff in charge of preventing disasters.