Dependability Evaluation of a Smart Poultry Monitoring System with Disaster Recovery Mechanism

The Internet of Things (IoT) has changed how poultry farming is carried out, offering various advantages to farmers. One notable benefit is the real-time monitoring of bird breeding tasks, ensuring the well-being of the animals. Farmers can enhance their operations through task automation by incorporating an edge server for local sensor data processing. Tasks automation enables farmers to make informed decisions, improving production efficiency, bird quality, and agribusiness profits. However, poultry farming faces challenges, with disaster recovery a critical concern. Potential events like fires, power outages, or equipment failures can significantly impact birds and production. Consequently, continuous monitoring of birds is vital, and any disruptions must be minimized to uphold system integrity. This study introduces Stochastic Petri Nets (SPN) models to evaluate the availability and reliability of an intelligent bird breeding system. The system integrates a disaster recovery solution for uninterrupted operations. Furthermore, a sensitivity analysis is conducted on the components of the smart poultry system to pinpoint the most relevant one to the system's availability in the proposed architecture. This analysis can aid system architects in developing distributed architectures, considering points of failure and recovery measures. The study results demonstrate the system's high availability and reliability, enabling farmers to make informed decisions and improve the overall productivity of their farms.