Artificial Intelligence-Based Irrigation Monitoring Information System For Enhancing Irrigation Rehabilitation Work Supervision
Abstract
The rehabilitation of irrigation networks plays a critical role in enhancing agricultural productivity and supporting national food self-sufficiency targets as mandated by Presidential Instruction No. 2 of 2025. Traditional monitoring practices still rely on manual reporting, inconsistent documentation, and non–real-time inspections, leading to data inaccuracies and limited transparency. These challenges highlight the need for a more reliable, timely, and objective monitoring system. SIMORI (Irrigation Monitoring Information System) is introduced as an AI-powered digital solution capable of providing real-time data, detecting anomalies, and generating accountable automated reports. This paper explores the relevance and urgency of SIMORI as a strategic instrument to enhance transparency, accountability, and monitoring quality in irrigation rehabilitation projects, thereby accelerating national food security objectives.
Fields of Study & Subjects
Smart Agriculture and AI
Engineering and Agricultural Innovations
Environmental Monitoring and Data Management
Publication details
- Journal / source
- Jurnal Indonesia Sosial Sains
- Volume
- 7
- Issue
- 1
- Pages
- 93–100
- Publication date
- 14 January 2026