02933nam a22003017a 4500 OSt 20260610144440.0 260610b |||||||| |||| 00| 0 eng d English TUPM TUPM rda Cabatuando, Alwyn Kylle Q. Author 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..- Manila: Technological University of the Philippines, 2024. xii, 141pages: 29cm. rdacontent rdamedia rdacarrier 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 Engineering Technology Plant Monitoring Microprocessor De Leon, Kervy P. Author Koizumi, Stephen Hisroshi M. Author Pantin, Carl Jomarie Author lcc BTH CIT 0 0 0 lcc 0 0 TUP TUP Bachelor's Thesis CIT-2F 2026-06-10 Donation BTH-5471 0 BTH QA 76.9 C33 2024 BTH0005471 2026-06-10 2026-06-10 BTH CIT 31492 31491