Thesis Bachelor of Science in Electronics Engineering University of Rizal System-Morong 2024

This undergraduate thesis aimed to design and develop an automatic monitoring and control hydroponics system for mustard green. The study thoroughly discusses the design and development process of the device, covering aspects such as dimensioning, incorporation of a dashboard interface, and evaluation of its functionality. Additionally, the research includes the creation of a user's manual for the device, providing essential information to users on proper operation and maintenance. This research project was conducted at the University of Rizal System Morong Campus during the School Year 2023-2024, with the testing procedure taking place in Angono, Rizal. This thesis utilized developmental methodology which is essential for this research as it allows the crafting of customized solutions for automated monitoring, thereby enhancing comprehension of their practical implementation in mustard green vertical farming. This methodology provides the solutions to meet specific vertical farming requirements, facilitating a thorough assessment of their effectiveness. It promotes continuous refinement and adaptability, thereby enriching knowledge in Brassica juncea farming and broader agricultural and automation domains. In this study, the researchers employed weighted mean as statistical tool to treat the data gathered from the questionnaire. For data collection, the researchers utilized both a questionnaire and a daily log sheet as tools. They employed simple random sampling to choose respondents from diverse groups, including farmers, end-users, and experts. Concurrently, the daily log sheet was employed to track the daily progress of mustard greens, documenting parameters like number of leaves and their length. This approach facilitates comprehensive monitoring of the growth process, enabling detailed analysis and insights into the development of mustard greens over time. As part of the research survey, the questionnaire checklist was given to respondents who are engaged in agricultural sector like farmers, experts and end-users. The Automated Monitoring Device and Control of Hydroponic Vertical Farming for Mustard Greens garnered high levels of acceptability across various criteria. Respondents rated the device’s functional suitability, performance efficiency, usability, reliability, and maintainability as Very Much Acceptable, with average weighted mean scores ranging from 4.66 to 4.74. The results indicate a significant level of approval for the Automated Monitoring Device and Control of Hydroponic Vertical Farming for Mustard Greens among participants in the agricultural field, highlighting its effectiveness in meeting various operational criteria. Based on the summary of the design outcome, the researchers found out that the developed device for automated monitoring and control of vertical hydroponics farming for mustard green is capable of nurturing the plant growth while ensuring the optimal nutrient distribution. Additionally, the dashboard interface serves as an efficient tool for monitoring environmental conditions within the device and managing various features including lighting, fans, and fertilizer distribution. The plant successfully grown inside the device and resulted with an average leaf length of 3.4 cm. The level of acceptability of the device according to ISO25010 was scored to have an average of 4.69 which indicates that the device is Very Much Acceptable which was agreed by the respondents of experts, end-user, and farmers. In addition, observations on the growth parameters of mustard greens revealed that the length of leaves typically increased by 2-3 centimeters within a span of 5 days, accompanied by a rise in the number of leaves in some instances. These parameters were crucial for tracking the development of mustard greens and informing adjustments to cultivation practices when necessary. For further improvements, the researchers recommend integrating solar panels into the device to ensure continuous operation while minimizing electricity usage. Additionally, future iterations could incorporate features like supplementary grow lights and plant color sensors to enhance functionality and enable real-time monitoring of plant health.