Development of IOT-Based Indoor Plant Growth Optimization System/ Alwyn Kylle Q. Cabatuando. Kervy P. De Leon, Stephen Hiroshi M. Koizumi, and Jomarie Carl Pantin..-

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Cabatuando, Alwyn Kylle Q [Author]

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TextPublication details: Manila: Technological University of the Philippines, 2024.Description: xii, 141pages: 29cmContent type:

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Dissertation note: College of Industrial Technology..- Bachelor of Engineering Technology major in Computer Engineering Technology: Technological University of the Philippines, 2024. Summary: The integration of technology with traditional gardening practices has led to the development of smart plant pots, offering an advanced approach to plant care. Traditional methods of plant monitoring often rely on visual cues which can be subjective and lead to under or over-care. The development of an IoT-based Indoor Plant Growth Optimization System is designed to monitor the Plant’s health and environmental status. The development of an IoT-based Indoor Plant Growth Optimization System is equipped with various sensors and features. The core components include a microprocessor, temperature sensor, soil moisture sensor, light sensor, humidity sensor, pH level sensor, light system, and self-watering mechanism. The microprocessor serves as the brain of the device and a Wi-Fi module that interacts with a mobile device that sends data to the user for analysis and to have a result. A mobile application that interprets the data sent by the microprocessor, shows the everyday record of the plant status that can be stored in the database. The history of everyday data is shown in the mobile application for better monitoring and transcript of records. Through the integration of the components and capabilities, the IoT-based Indoor Plant Growth Optimization System empowers users to effectively monitor and manage plant health, optimizing conditions, and reducing the risk associated with improper care. A data-driven approach to plant care enables users to make an informed decision based on objective information. It aims to highlight the potential benefits of the device and its significant contribution to the environment. Keywords: plant monitoring, sensors, microprocessor, mobile application, data-driven

List(s) this item appears in: CIT-BET- Computer Engineering Technology

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Item type	Current library	Shelving location	Call number	Status	Date due	Barcode
Bachelor's Thesis CIT	TUP Manila Library	Thesis Section-2nd floor	BTH QA 76.9 C33 2024 (Browse shelf(Opens below))	Not for loan		BTH0005471

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Bachelor's Thesis

College of Industrial Technology..- Bachelor of Engineering Technology major in Computer Engineering Technology: Technological University of the Philippines, 2024.

Includes bibliographic references and index.

The integration of technology with traditional gardening practices has led to the
development of smart plant pots, offering an advanced approach to plant care. Traditional
methods of plant monitoring often rely on visual cues which can be subjective and lead to
under or over-care. The development of an IoT-based Indoor Plant Growth Optimization
System is designed to monitor the Plant’s health and environmental status. The
development of an IoT-based Indoor Plant Growth Optimization System is equipped with
various sensors and features. The core components include a microprocessor, temperature
sensor, soil moisture sensor, light sensor, humidity sensor, pH level sensor, light system,
and self-watering mechanism. The microprocessor serves as the brain of the device and a
Wi-Fi module that interacts with a mobile device that sends data to the user for analysis
and to have a result. A mobile application that interprets the data sent by the
microprocessor, shows the everyday record of the plant status that can be stored in the
database. The history of everyday data is shown in the mobile application for better
monitoring and transcript of records. Through the integration of the components and
capabilities, the IoT-based Indoor Plant Growth Optimization System empowers users to
effectively monitor and manage plant health, optimizing conditions, and reducing the risk
associated with improper care. A data-driven approach to plant care enables users to make
an informed decision based on objective information. It aims to highlight the potential
benefits of the device and its significant contribution to the environment.
Keywords: plant monitoring, sensors, microprocessor, mobile application, data-driven

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