#brms

Bamboo is an important renewable resource with significant ecological and economic value, particularly in regions where it contributes to rural livelihoods and sustainable agriculture. However, traditional bamboo farming practices often rely on manual monitoring and limited data, which can reduce efficiency in resource management and crop productivity. This study proposes the design and architecture of an Internet of Things (IoT)-enabled Bamboo Resource Management System (BRMS) aimed at supporting sustainable bamboo cultivation in Northeastern Cagayan, Philippines. The system was developed using a design-oriented research approach that integrates stakeholder feedback, field observations, and analysis of existing bamboo farming challenges. The proposed framework consists of four main stages: requirement identification, system architecture design, hardware and software selection, and development of a comprehensive data model. The system utilizes IoT sensors and GPS technology to collect real-time environmental and spatial data from bamboo plantations. These data are transmitted through cellular and Wi-Fi networks and stored in a cloud-based MySQL database. Data analysis is conducted using Python-based analytical libraries to generate actionable insights for resource management. A web-based dashboard developed using PHP, JavaScript, and Bootstrap enables users to monitor plantation conditions and access decision-support information through an interactive interface. The proposed BRMS architecture demonstrates how IoT technology and data analytics can improve monitoring, resource allocation, and decision-making in bamboo farming. The system provides a scalable framework for integrating digital technologies into sustainable agricultural practices and may serve as a model for smart farming applications in other crop production systems.