Fog-Based IoP Application Monitoring and Failure Detection

Due to the increase of IoT (Internet of Things) applications and connected devices, for the purpose of solving daily human activity, systems complexity is increasing. And system failures are inevitable, some errors will always occur. Additionally, system failure detection in IoP (Internet of Plant) applications is essential and crucial for maintaining system reliability and ensuring optimal system functionalities. This paper presents monitoring and automating failure detection in fog computing microservices for IoP applications. It employs tools and techniques to proactively identify and notify about system issues before they impact irrigation systems and disrupt critical crop growing conditions. The proposed approach significantly reduces system complexity by 20% compared to traditional methods. The proposed method effectively identifies and mitigates errors such as overloading, crashes, and timeouts. Furthermore, implementing this approach resulted in improved system reliability by 23%. We assessed four microservices patterns in precision irrigation, evaluating query response times, hardware efficiency, and system health.