## 6 Monitoring and Ensuring System Reliability  
Autonomous irrigation systems, promising as they are, must be built on a foundation of reliability and resilience. This means not only ensuring that the systems themselves function correctly, but also anticipating and mitigating potential points of failure, from faulty sensors to unpredictable environmental conditions--and even malicious intrusions. In this section, the strategies and techniques are explored for monitoring system status, building resilience against faults and failures, and implementing closed-loop control to adapt to changing conditions. Enhancing irrigation system resilience involves incorporating redundancy of critical components, such as sensors, controllers, and communication protocols [147]. For example, [PERSON] et al. [148] addressed the challenges of rural irrigation by proposing a photovoltaic (solar energy) system integrated with a Z-source inverter motor drive to power irrigation pumps. This setup includes a fault-tolerant circuit to handle switch failures, demonstrating the effectiveness of this redundancy strategy. Implementing failover mechanisms, which automatically switch to backup components when primary systems fail, ensures a smooth transition and minimizes disruptions. [PERSON] and [PERSON] [149] developed a green fault tolerant IoT-enabled mobile sink data collection scheme that provides fault-tolerant data collection in sensor networks through an AI-based rendezvous point selection and rotation mechanism. Simulations and testbed results validated the efficiency of this approach. Future advances include AI-driven self-healing systems that can automatically identify and recover from faults [150]. Distributed architectures and edge computing contribute to resilience by decentralizing key functions and data flows, enabling localized control even during central failures [151; 152]. For instance, [PERSON] and [PERSON] [153] proposed a resilient fog-based IoT system for smart irrigation that maintains operation even during internet disconnections by storing and analyzing data locally at the edge. Their data value extraction mechanism reduced fog storage usage by 23-48% depending on crop growth stage. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Strategy** & **Description** & **Citations** \\ \hline Secure Device Provisioning & Implement strong authentication mechanisms, such as multi-factor authentication and hardware security modules, to prevent unauthorized access & [144] \\ \hline Encryption and Secure & Employ robust encryption algorithms and secure communication protocols to protect data confidentiality & [145] \\ Communication Protocols & and integrity & \\ \hline Regular Firmware and Software Updates & Maintain a regular update schedule for firmware and software to address vulnerabilities and mitigate emerging threats & [144] \\ \hline Network Segmentation and & Divide the network into smaller, isolated sub-networks and implement access control mechanisms to limit the impact of a security breach & [146] \\ \hline Intrusion Detection and & Implement intrusion detection and prevention systems & \\ Prevention Systems & (IDPS) to monitor network traffic and system activity, identifying and blocking suspicious behavior & [144] \\ \hline Security Audits and Penetration Testing & Regularly conduct security audits and penetration testing to identify vulnerabilities before they can be exploited & [144] \\ \hline User Awareness and Training & \
\begin{tabular}{c} Educate farmers and irrigation managers about \\ cybersecurity best practices to minimize human error and \\ promote security awareness \\ \end{tabular} & \\ \hline Incident Response Planning &
\begin{tabular}{c} Establish a comprehensive incident response plan to \\ effectively handle security incidents and minimize \\ their impact \\ \end{tabular} & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Best practices and strategies for securing automated irrigation systems.