Development of a Mobile App for Precision Irrigation Management in Crops

Thesis Abstract

Water management efficiency in agriculture remains a critical global challenge, particularly as climate variability and water scarcity intensify pressure on crop production systems. Despite advances in irrigation technologies, the adoption of precise and data-driven irrigation practices remains limited, primarily due to lack of accessible decision-support tools tailored for diverse farming contexts. This study aims to develop, implement, and evaluate a mobile application designed to enable farmers to optimize irrigation management through real-time data acquisition, analysis, and actionable recommendations. The specific objectives include (1) designing a user-friendly mobile app integrating soil moisture sensors, weather data, and crop-specific irrigation models; (2) assessing the usability and acceptance of the app among smallholder and commercial farmers; (3) evaluating the app’s effectiveness in improving irrigation efficiency and crop yield; and (4) identifying barriers and facilitators influencing adoption. The research follows a mixed-methods approach, combining qualitative and quantitative techniques. The quantitative component employs a quasi-experimental design involving a sample of 150 farmers stratified into treatment and control groups. Participants are selected through stratified random sampling from irrigated farming regions with varied crop types. Data collection instruments include structured questionnaires, soil moisture sensors, and app analytics logs, alongside crop yield records. The qualitative component involves semi-structured interviews with 30 farmers and extension officers to explore perceptions and contextual challenges related to app usage. Data analysis encompasses descriptive statistics, paired t-tests, and multiple regression analyses to evaluate the impact of the app on irrigation efficiency and crop productivity. Thematic analysis is utilized to interpret qualitative data, guided by the Diffusion of Innovations Theory and the Technology Acceptance Model (TAM), which frame the investigation of user acceptance and behavioral factors. It is anticipated that the developed mobile app will significantly improve irrigation scheduling accuracy, leading to a measurable reduction in water usage—expected to be around 20%—without compromising yields. The app is also expected to facilitate timely irrigation decisions, resulting in increased crop yields by approximately 15% and cost savings for farmers. The integration of real-time sensor data with weather forecasts is projected to enhance user confidence and decision-making efficacy. Findings will demonstrate the importance of tailored technological solutions in fostering sustainable water use and productivity enhancement in agriculture, particularly within resource-constrained settings. This study contributes to the existing body of knowledge by providing a validated model for mobile-based irrigation decision support, grounded in empirical evidence from diverse farming contexts. It advances understanding of technology adoption dynamics in rural agricultural settings and underscores the value of integrating geospatial and sensor data with user-centric app interfaces. Additionally, the research offers practical insights into designing scalable, cost-effective, and context-specific ICT solutions for sustainable agriculture. The main conclusion highlights that the mobile app significantly enhances irrigation management practices, driven by increased accessibility, contextual relevance, and user engagement. It recommends scaling up the intervention across different regions and crop systems, emphasizing the necessity for capacity-building initiatives and policy support to maximize technology adoption. Further research should explore long-term impacts, integration with broader farm management systems, and the potential for incorporating machine learning algorithms to refine predictive capabilities. Overall, this study affirms that targeted ICT interventions can transform traditional irrigation practices, substantially contributing to sustainable resource use and food security amid mounting environmental challenges.