E-Baboyan: A Multi-Modal IoT and
Vision-Based System
For Precision Feeding and Micro-Climate Swine Management
E-Baboyan is an advanced, autonomous agricultural hub designed to modernize swine management. By combining precision gravimetric feeding, automated thermal regulation, and cloud-synced visual analytics, the system drastically reduces manual labor while proactively protecting herd health.
Dual-Core Processing
Powered by an ESP32-32E master controller and an Arduino Uno logic co-processor communicating via high-speed UART. The system features a responsive 2.8-inch TFT touchscreen for local environmental monitoring and hardware state verification.
Precision Feeding
Utilizes HX711 load cell telemetry and an automated mechanical trough to dispense exact feed payloads. Hardware-level feed schedules sync directly from the cloud backend to guarantee portion accuracy and prevent under-feeding.
Thermal Regulation
Actively monitors ambient conditions using DHT22 sensors. The localized logic controller automatically triggers misting pumps to cool the herd during temperature spikes, governed by strict humidity fail-safes to prevent respiratory distress.
Vision & Telemetry
Dedicated ESP32-CAM nodes provide autonomous image capture to allow remote behavioral monitoring. All raw hardware telemetry, scale mass data, and environmental variables are securely transmitted to the cloud via REST APIs.
The Capstone Research Team
Siti Sheena Mediana
Project Manager • Documentation • Data Analyst
Driving project methodology, data analysis formulation, rigorous behavioral testing validation, and official structural capstone manuscript compilation.
James Khail Gerona
Lead Hardware, Embedded, & Full Stack System Developer
Lead programmer & hardware engineer. Responsible for full-stack API integration, C++ firmware routing, UI gateway design, and custom embedded electronics fabrication.
Mary Grace Apdo
QA Tester • Technical Writer
Spearheading agricultural research parameters, system documentation, and ensuring hardware outputs align precisely with optimal swine mortality reduction metrics.