IMPLEMENTATION OF AN INTERNET OF THINGS- BASED AUTOMATIC DRIP IRRIGATION SYSTEM IN VEGETABLE GARDENS FOR IRRIGATION EFFICIENCY

Gardening management is not an easy task as it often involves various challenges. One of the prominent challenges faced by vegetable gardens in Indonesia is the inefficiency of the irrigation system and the declining workforce managing the gardens over the years. This issue was also identified in...

Full description

Saved in:
Bibliographic Details
Main Author: Stanic Prasetyo, Edwin
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/75783
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Institut Teknologi Bandung
Language: Indonesia
Description
Summary:Gardening management is not an easy task as it often involves various challenges. One of the prominent challenges faced by vegetable gardens in Indonesia is the inefficiency of the irrigation system and the declining workforce managing the gardens over the years. This issue was also identified in one of gardens, Forum Komunikasi Gunung Geulis (FKGG) garden, located in Jatiroke Village, Jatinangor District. The manual irrigation process at the FKGG garden is further exacerbated by limited labor resources, leading to poorly maintained plants and unmet water requirements. Based on the observations conducted at FKGG garden, a solution was popped up to implement an automatic drip irrigation system based on the Internet of Things (IoT) for vegetable gardens. The objective of this project was to determine, design, and develop an embedded system capable of automating plant watering in vegetable gardens for irrigation efficiency. The idea was executed by defining requirements, designing the system, and developing the necessary components. The successful implementation of this final project resulted in an automatic drip irrigation system that utilized various hardware components such as microcontrollers, solenoid valves, and water flow sensors. The system was also connected with the database from Firebase, enabling data transmission and retrieval. Through testing, the implementation achieved 100% and 97.5% success rates for functional and non-functional requirements, respectively. Furthermore, a comparison between the system and the current watering solution demonstrated that the system could improve irrigation efficiency by up to 90% in terms of time.