# Energy Consumption Analysis of LPWAN Technologies and Lifetime Estimation for IoT Application
## 7 Real-Time Application Use-Case  
In Section 4, we calculated the energy consumption of different LPWAN technologies in an ideal environment. However, in real time measurement there are several factors that impact the energy consumption as mentioned in Section 5. We deployed a LoRaWAN based network in a greenhouse [42] based out in Belgium to monitor the environment as shown in Figure 22a. In this setup, we used imec's OCTA-Connect platform board which has onboard temperature and humidity sensors. It is mounted with LoRaWAN shield for the communication. The sensor device measures the sensing values after each five minutes and forwards the message to the gateway. The LoRaWAN Kerlink gateway is installed inside the greenhouse with an ethernet and power connection. It receives the message from the installed sensors and forwards the data to the things-network. In most of the applications, it is very difficult to change the batteries or charge them during the deployed phase. This is at times avoided to maintain the security and sanity of the devices or the deployment is at the remote location. For example, Figure 22a shows the deployment of a sensor box in a tomato greenhouse where hygiene is of utmost priority to avoid any plant disease. Same way, Figure 22b shows the sensor setup that is deployed to locate the water leakage across the water grid. This deployment is mostly spread across outskirts and remote location which makes the battery replacement a strenuous task.  
The energy consumption of the end-device differs from idle case to the state in deployment due to factors such as: sensors attached to the end-device, exposure to the environment, extra time in computation, and behavior of battery. For this deployment, in addition to the idle energy consumption of LoRaWAN message there is additional task for taking the measurement from the sensors and processing the message frame. Also, it was observed that the temperature inside the sensor box increases which affects the overall energy consumption due to the generated heat. The current consumption for the sensing setup (Figure 22a), is shown in Table 8. There is some time and energy invested in reading sensor values. As per the length of the message and protocol-dependent configuration settings the radio transmission consumes energy. In our case, its LoRaWAN data rate, spreading factor and power configurations. We have used SF 9 for our experiments and exhausted a Li-Ion battery of 15,000 mAh capacity for 60,480 messages in approximately 7 months. This is much less when compared with the calculations presented in Table 1. In the ideal case, the device should have lasted for approximately 10.9 years with a packet transmitted in every 5 min. This behaviour of the device in real time can be traced back to a hardware and software imperfections in the device design which increased the inactive (idle) mode energy consumption of the device to 6 mA. Where the end-device used for the empirical evaluation in Section 4 has a inactive mode current of 80 \(\upmu\)A. Along with this, the shelf time and self discharging of the batteries could have contributed to the deterioration in the over all life time of the device.  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Phase** & **Time** & **Avg. Current (mA)** \\ \hline Sensor reading & 82.28 ms & 13.24 \\ Radio transmission & 249.8 ms & 46.08 \\ Inactive mode & 5 min & 6.01 \\ One total message & 2.3 s & 10.92 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Power consumption analysis for LoRaWAN message used for the Greenhouse monitoring application.  
Figure 22: (**a**) Deployment of LoRaWAN based sensor network at the greenhouse; (**b**) Sensors deployment in remote locations i.e., underground water grid.