Development of iot monitoring system for pig pens/
Trishalyn B. Canto, Angelo James L. Forbes, Stephen Gabriel T. Onahon, Carlos Alfonzo R. Rumbaoa, Jay Mark M. Santos, and Leoniel R. Valenzuela.--
- Manila: Technological University of the Philippines, 2025.
- xiv, 132pages: 29cm.
Bachelor's thesis
College of Industrial Technology.--
Includes bibliographic references and index.
Small-scale piggery operations, backyard pigpens, face significant challenges including too much labor work, poor waste management, and inconsistent feeding practices that impact animal welfare and operational efficiency. Traditional backyard farming environments often lack proper monitoring systems, leading to not ideal conditions of pigpen and increased health risks for livestock. With this, the researchers intended to address these limitations by developing IoT Monitoring for pig pens. An integrated monitoring system tailored specifically for small-scale piggery operations like the backyard piggery farms, which combines real-time environmental monitoring, automated farm management, and remote supervision capabilities. The system integrates MQ-135 gas sensors for ammonia level detection and DHT11 sensors for temperature and humidity tracking, along with ESP32-CAM modules for live video streaming and a comprehensive mobile application interface. The prototype was developed using the Agile Scrum methodology with iterative sprints, daily stand-ups, and continuous feedback integration to ensure alignment with user requirements. The researchers conducted extensive testing including unit tests, integration assessments, performance evaluations, user acceptance testing with farmers, and on-site trials in actual pigpen environments. Results demonstrate that the system adheres to ISO 25010 software quality standards with strong performance across key metrics, particularly, functionality, accuracy, and reliability. The MQ-135 gas sensor showed an average percentage error of 2.88% compared to reference ammonia levels, while the DHT11 resulted an average percentage error of 2.10% for temperature and 1.83% for humidity, confirming high sensor reliability. Software testing using a structured test matrix for core features such as user login, sensor display, and automated controls yielded an average pass rate of 100%, verifying expected behavior and functional correctness. The mobile application provides real-time sensor readings, manual controls, automation features for cleaning and feeding, and alert notifications when environmental thresholds are exceeded. This innovation contributes to enhanced animal welfare, improved operational efficiency, and sustainable pig pen management through intelligent IoT connectivity and remote monitoring capabilities, aligning with modern agricultural technology standards and practical farming needs.