Project Overview
The DAIF project revolutionizes agricultural productivity in Cambodia through an innovative smart greenhouse management system. By integrating cutting-edge remote sensors, wireless LoRa communication, and semi-automated fertigation/irrigation functions via a comprehensive web platform, we're transforming digital agriculture for students, farmers, and agri-tech stakeholders.
Smart Agriculture
AI-powered greenhouse systems for optimal crop monitoring and resource management
LoRa Technology
Long-range wireless communication enabling data transfer up to 500m without internet
Automated Systems
Semi-automated fertigation and irrigation with precise resource calculations
Knowledge Transfer
Comprehensive training programs for farmers and students across Cambodia
Project Objectives
Primary Goal
Build a data-driven smart greenhouse system enabling real-time crop monitoring and automated fertigation/irrigation through AI-integrated sensors and web control.
DAIF Control Development
Develop sensor-based DAIF control boxes with comprehensive environmental monitoring capabilities.
Wireless Communication
Enable wireless LoRa-based communication for reliable data transmission across farm areas.
Web Integration
Integrate web-based fertigation tools for intelligent resource management and decision support.
Capacity Building
Train farmers and students on DAIF system operation and smart agriculture practices.
Sustainability
Ensure long-term sustainability through Public-Private Partnerships and commercialization strategies.
Key Activities
Control Box Development
Designed and assembled 4 control boxes equipped with 10 environmental sensors to monitor soil and air conditions for precise agricultural decisions.
LoRa Communication System
Built bandwidth systems enabling data transfer between devices over 500m using LoRa technology, functioning even without internet connectivity.
Fertigation Integration
Created and embedded fertigation and irrigation calculation functions into v-gro.com to help estimate resource requirements semi-automatically.
Demonstration Greenhouse
Constructed a demonstration greenhouse in Kandal province, planted 5 crop varieties, and operated using the DAIF system.
Training Programs
Conducted 10-day training for 5 students and 5 farmers, followed by additional training in Takeo province with 20 more farmers.
National Workshop
Held a national workshop with 45 attendees, including researchers, farmers, and private sector representatives to showcase project outcomes.
Key Outcomes
DAIF Systems Deployed
Four smart sensor-based control boxes were successfully developed and deployed in greenhouses to enable data-informed agriculture.
Wireless Communication Success
Devices were connected using LoRa communication, transferring data over a 500m range without the need for internet connectivity.
Web Platform Integration
Fertigation and irrigation functions were built into the v-gro.com platform to support semi-automated decision-making processes.
Knowledge Transfer Achievement
Farmers and students were trained in system use, enhancing agri-tech literacy and practical competence across Cambodia.
Stakeholder Engagement
The public workshop increased awareness among academia, SMEs, and farming communities about smart agriculture technologies.
Partner Organizations
Institute of Technology of Cambodia (ITC)
Lead technical institution providing research expertise and infrastructure
Royal University of Agriculture (RUA)
Agricultural research and education partner
Khmer Modern Farming
Private sector partner for modern farming techniques
ITALab
Technology development and innovation laboratory
Cambodian Quality Horticulture (CQH)
Quality assurance and horticulture expertise
Khmer Organic Cooperatives (KOC)
Organic farming cooperative network
Eco Agri Center (EAC)
Sustainable agriculture and environmental solutions
TEIN*CC
Network infrastructure and connectivity support
Challenges & Gaps
Language Accessibility
The system's English-only interface limits access and usability for Khmer-speaking farmers, creating a significant barrier to adoption.
Technical Complexity
Fertigation and irrigation tools require detailed technical data unfamiliar to non-experts, making operation challenging for traditional farmers.
Communication Range Limitations
Though 500m range was achieved, wireless signals weaken in dense vegetation or with physical obstructions, limiting deployment flexibility.
Digital Literacy Gap
Many farmers experience difficulty operating the technology without significant training support and ongoing technical assistance.
Limited AI Integration
While semi-automated, the system lacks advanced AI features like disease detection, pest identification, or nutrient deficiency analysis.
Future Directions
Khmer Language Support
Localizing the interface and tutorials in Khmer will significantly improve accessibility for rural users and increase adoption rates.
Mobile Applications
Developing Android/iOS apps will enhance user interaction, especially for farmers with smartphones, providing on-the-go monitoring capabilities.
AI-Driven Features
Incorporating modules for pest detection, disease identification, and irrigation prediction will improve automation and accuracy significantly.
Expanded Demonstrations
More on-ground demos and workshops across provinces will increase adoption and scale, reaching more farming communities nationwide.
Commercialization via PPP
Explore business models with ITC and local firms to make DAIF systems widely available through sustainable market mechanisms.