GUL.AI

16 Sep 2021 3:05 PM

The Gul.ai project is envisioned to contribute to solving the growing lack of interest of the Filipino youth in agriculture which may have long term effects in food security in the country. The project’s primary goal is to encourage the Filipino youth to consider taking up areas of study and research, and eventually career paths, that would lead to the fusion of information and communications technology (ICT) and agriculture. Through innovation in this fusion, we will be able to ensure our future generation’s food security.

 

About Project GUL.AI


The Gul.ai Project aims to promote to the Filipino youth the study and practice of agriculture and crop science, and their fusion with ICT for research and development and operations. The design and implementation of the Gul.ai System adopts an Internet-of-Things approach to the gathering of relevant environmental data and the provisioning of these data for long-term storage, near real-time visualization for monitoring, and later analysis. The eventual availability of gathered environmental data and corresponding plant growth observations will allow for the generation of Artificial Intelligence models that can eventually be used as presets for growing crops in further versions of the system.  

The current design and implementation of the Gul.ai System aims to provide teachers and their students with a system that they can use to design and carry out experiments on crops. The system's current use case is intended to serve as a tool for teachers and their students in teaching and learning about technical concepts relating to agriculture engineering, crop science, and ICT. This use case directly addresses the goal of the project. 


CONTACT US

gul.ai@asti.dost.gov.ph

 

Partnerships


The Gul.ai laboratory-scale prototype was deployed in the University of Rizal System (URS) Tanay Campus, College of Agriculture last November 2022 where the prototype underwent its first real environment testing and use case validation with the agriculture engineers and crop scientists of the URS. 

 

Project Staff


Joanna G. Syjuco - Project Leader ​/ Technical Lead

Roxanne S. Aviñante - Technical Staff/ Researcher

Michelle P. Neverida - Technical Staff/ Lead Business Analyst

John Kevin C. Abonita - Technical Staff/ Lead Quality Engineer

Vanesa O. Osiana - Technical Staff/ Project Management

Nia Bernise F. Fabay  - Technical Staff/ Developer

Elisa C. Espares - Adminstrative Support/ Division Assistant

Abegail F. Bactol - Project Manager

Genio Brylle C. Viernes - Mobile App and Touch Panel Developer

Joel C. Carizo- Internet-of-Things Engineer

Meynardson B. Magoli - Internet-of-Things Engineer

Patrick Lloyd B. Chavez - Software Quality Assurance/ Tester

Rodolf E. Esguerra - System Administrator

King Harold B. Sabado - Business Analyst/ UI/ UX

Justine B. Patiño - Backend Software Engineer/ Web App Developer

Leonard B. Ramos - Frontend Software Engineer/ Web App Developer

Christian James E. Barimbao - Software Quality Assurance/ Tester