A Development of Web Based Plantation Information System with IoT for iGrow Organization

Abstract

Agriculture and agro-based industries have long been the mainstay of the Malaysian economy. However, the use of the latest technology is still not widely used despite its advantages. The study's main focus is on agricultural soil type data. This includes land classification that is still done manually with the help of human experts from the Office of Agriculture, or individuals with skills and experience. It is common knowledge that soil type plays an important role for agriculture to get optimal yields. Therefore, a database that stores soil type information is important to speed up the classification process and support the decision-making of the appropriate crop type for the soil type. Therefore, to overcome the centralized information difficulties mentioned above, a centralized database and web information system have been developed in this project. The methodology used is the Agile Scrum methodology. Python is a programming language and PhpMyAdmin and Firebase as databases. The system assists the trainee community in collecting soil data and conducting agricultural analysis based on district and plant types using rule-based algorithms. The developed system help individuals who want to start farming by examining the condition of the soil to cultivate crops. The system also implements the use of IoT where trainees can register their sensors to make soil analysis and view results through a channel module. The combination of information technology and IoT is seen to give positive results in this area.