## 6 Monitoring and Ensuring System Reliability
### Case Study 3: [PERSON] et al. [160]  
[PERSON] et al.'s implementation represents a significant advancement in precision irrigation, integrating multiple data sources for optimized water management. The system's components and benefits are outlined in Table 9.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Aspect** & **Details * \\ \hline Step 1: Real-time data collection and transmission & Soil moisture data sent from SU to BSU every 2 min via 434 MHz RF; two-way wireless communication between base station, valve, and sensor units \\ \hline Step 2: Data storage and processing & Sensor data processed by PIC microcontrollers in BSU, VU, and SU; BSU logs all sensor data and valve status on SD card for local monitoring \\ \hline Step 3: Predictive modeling and irrigation scheduling & Soil moisture threshold-based control; BSU evaluates soil moisture data and sends control signals to VU for valve actuation \\ \hline Step 4: Application of insights & Solenoid valves controlled by VU based on signals from BSU; real-time soil moisture feedback used to trigger irrigations \\ \hline System security, robustness, and monitoring & BSU switches to scheduled irrigation if no data received from SU; duplicate soil moisture sensors at each SU for redundancy; all units solar-powered for uninterrupted off-grid operation \\ \hline Cost and ease of use & Low component costs enable cost-effective implementation; designed for cost effectiveness and use by growers; data logging enables performance analysis and irrigation optimization over time \\ \hline Benefits and limitations & Reduces time spent by workers on irrigation management; maintains optimal soil moisture levels in root zone of trees; no significant yield increase after 1 season; lack of remote monitoring and control capabilities \\ \hline \hline \end{tabular}  
* SU: sensor unit; BSU: base station unit; RF: radio frequency; PIC: peripheral interface controller; VU: valve unit.  
\end{table}
Table 8: Key aspects of the fully autonomous irrigation system.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Aspect** & **Details * \\ \hline Step 1: Real-time data collection and transmission & Control nodes report valve status and flow meter data hourly via wired RS485 bus; cellular link between central computer and cloud platform \\ \hline Step 2: Data storage and processing & Irrigation analytics and scheduling performed in cloud and transmitted to central computer; cloud platform aggregates and cleans flow meter and valve data for analysis \\ \hline Step 3: Predictive modeling and irrigation scheduling & Water delivery optimized based on yield and water efficiency objectives; irrigation amounts calculated from satellite NDVI data and reference evapotranspiration; management zones delineated based on historical yield data and NDVI \\ \hline Step 4: Application of insights & Solenoid valves in control nodes directly controlled by central computer commands; weekly irrigation scheduling adapted based on latest satellite imagery \\ \hline System security, robustness, and monitoring & Redundant power and communication lines between control nodes; solar-powered control nodes and backup batteries for continuous operation \\ \hline Cost and ease of use & Costs about USD 5000/hectare, with an estimated 2.5 years ROI for wine grapes; 1.6–2.5 year payback estimated for various high-value crops; optimum control resolution of 30 m to balance costs and benefits \\ \hline \hline \end{tabular}
\end{table}
Table 9: Key aspects of the fully autonomous irrigation.