Design and Evaluation of an IoT–Augmented Reality-Based Smart Agriculture Information System

Abstract

This study aims to design and evaluate a Smart Agriculture Information System model that integrates Internet of Things (IoT) and Augmented Reality (AR) technologies to enhance irrigation efficiency and support data-driven decision-making processes. A mixed-method approach was employed within the Design Science Research (DSR) framework, involving 32 participants consisting of farmers, agricultural extension officers, and system administrators. The system was developed by deploying IoT-based sensors to monitor real-time field conditions, including soil moisture (45%–72%), temperature (24–31°C), and pH levels (5.5–6.8). These data streams were further integrated with an AR application to provide contextual, in-situ visualization for users in the field. The findings indicate a significant improvement in irrigation decision-making efficiency, as reflected by a reduction in processing time from approximately ±15 minutes to ±9–10 minutes, equivalent to an efficiency gain of around 33–35%. Furthermore, the system enhances the accuracy of land condition monitoring and enables more adaptive irrigation management based on dynamic environmental parameters. Usability evaluation using the System Usability Scale (SUS) yielded an average score of 78, which falls into the “good” category, indicating a favorable level of acceptance among users, including those without technical backgrounds. The primary contribution of this study lies in the development of an integrative IoT–AR model that supports precision irrigation through real-time data utilization and interactive visualization. These findings reinforce the implementation of Agriculture 4.0 by emphasizing not only technological innovation but also user interaction aspects. However, the study is limited to a relatively small-scale implementation and does not directly measure its impact on crop yield productivity