Development and Evaluation of an IoT-Based Water Quality Monitoring System for Sustainable Smart Farming Using a Data Analytics Dashboard

• Main Author: Ballistair, Qallie Konsil
• Format: Final Year Project Report
• Language: English
• Published: Universiti Malaysia Sarawak, (UNIMAS) 2023
• Subjects: QA Mathematics
• Online Access: http://ir.unimas.my/id/eprint/44146/1/Ballistair%20Qallie%20ft.pdf; http://ir.unimas.my/id/eprint/44146/

Data analytics plays a crucial role in enabling precision agriculture within the era of Smart Farms. This study investigates the significance of a data dashboard in managing IoT-based Smart Farms, specifically emphasizing water quality monitoring. Although Smart farms offer promising alternatives to traditional agriculture, they often encounter challenges related to complexity. To address this, the study proposes a comprehensive tool for data comprehension, visualization, and management within IoT Smart Farms. This tool has the potential to simplify transitions to smart farming, enhance operations, and optimize resource utilization and efficiency. The evaluation results demonstrate that over 90% of participants expressed a positive perception of the proposed dashboard, highlighting its potential to improve resource use and efficiency. This research contributes to the advancement of sustainable farming practices and effectively addresses the demands posed by global population growth.