Abstract
Thermal stress remains a major challenge for poultry production, particularly in regions characterized by high ambient temperatures and humidity. Despite advances in environmental monitoring, practical and affordable tools capable of automatically diagnosing thermal comfort conditions in poultry houses remain limited. Therefore, this study aimed to develop, calibrate, validate, and technically evaluate two low-cost sensor systems for automated thermal stress assessment in broiler and laying hen facilities. Two prototypes based on psychrometric principles were developed using Arduino
®
platforms. The systems used dry-bulb temperature, relative humidity, and local atmospheric pressure to calculate specific enthalpy and classify thermal stress conditions in real time. S1 featured local data processing and storage using a memory card, whereas S2 incorporated wireless communication and cloud-based monitoring capabilities. Sensor calibration was performed under controlled laboratory conditions using a commercial HOBO U12–012 data logger as the reference instrument, generating 17,280 observations over a 24-h period. Field validation was subsequently conducted in a reduced-scale broiler house. Calibration results demonstrated high agreement with the reference sensor, with coefficients of determination ranging from 0.9684 to 0.9970 for temperature and relative humidity measurements after model adjustment. Both prototypes accurately monitored environmental conditions during field validation and successfully implemented the proposed thermal stress classification algorithm. The systems automatically generated thermal stress levels and environmental diagnoses, providing practical decision-support information for poultry-house management. The technical evaluation also indicated that both systems were substantially less expensive than commercial alternatives, with S2 offering additional advantages in terms of reduced size, lower cost, and remote real-time monitoring capability. These findings demonstrate the feasibility of integrating low-cost environmental sensing, automated thermal stress classification, and real-time monitoring into poultry production systems. Overall, the proposed sensors represent reliable, affordable, and scalable tools for precision poultry farming, with potential to support environmental management, bird welfare, and production efficiency.