## 4 Results and Evaluation
### Assessing Energy Footprint and Battery Efficiency  
The energy footprint of the proposed IoT nodes has been thoroughly studied as it is of vital importance in order for the final user to have easy access to \"fresh\" soil measurements for a long period. For this reason, the board settings implemented included a voltage divider for reporting the battery voltage powering the sensor node. As already mentioned, this information was part of the LoRa packet payload, periodically delivered from the sensor nodes to the sink/gateway. These battery voltage data extracted from the corresponding log files were utilized to form curves indicating the voltage changes over time. In this regard, Figure 14a illustrates the voltage drop (in volts) over time (in minutes) of the battery of node #A1 (red line) and the voltage fluctuations of node #A2 (in blue) for a time period close to 7000 min (i.e., four days and five nights). As it can be inferred from the graphs, the voltage of node #A1 dropped continuously at a slow but steady rate, as it had all its parts underground and no photovoltaic panel assistance, while node #A2 periodically replenished its battery charge, benefited by the small solar panel attachment, thus gradually leading to a fully charged state. It can also be seen that the voltage drop rate of both nodes is almost the same during the nights (as the curves evolve in parallel), while during day 4, the voltage rise due to the sun was less intense as clouds were present in the sky. In an attempt to better capture the short-scale dynamics of the sensor nodes (micro-analysis), an auxiliary measuring circuit was assembled according to the specifications in [42]. Specifically, an Arduino Nano board was utilized to calculate the voltage drops over a resistor of known value, connected in series with the sensor node, via a separate 16-bit precision ADC module (namely, an ADS1115 unit) capable of differential measurements, connected to the Nano through its I2C interface. This auxiliary prototype real-time measuring system capturing the average consumption of the sensor nodes is depicted in Figure 14b. The adoption of Arduino for microcontroller selection, programming, and inspection facilitated the fast extraction of results and their visual representation via the Serial Monitor and Serial Plotter components of the Arduino IDE environment. Consequently, for the node under testing, the corresponding average consumption traces could be easily extracted, with a typical time resolution close to 20 sps and an average resolution of 125 uA. The investigation focused on the behavior of the sensor nodes, as typically, the sink/gateway node had a permanent power supply and its amperage consumption was almost constant, i.e., close to the 250 mA level. Specifically, the consumption of a sensor node during sleep was close to 250 uA, while at idling it was close to 7 mA (with the LoRa radio and the unnecessary modules disabled), as shown in Figure 14c. The soil instruments hosted caused an additional amperage drain between 8 mA and 48 mA, approximately, according to their type, with the older ML2 being the greediest one. It must be noted that not all amperage amounts were attributed to the soil instruments due to the complex nature of the charge pump and the multiplexer/demultiplexer circuits. Meticulous experiments involving ohmic resistors close to the soil instrument impedance and accurate multimeters revealed that a percentile close to 45% of the values shown at the interface of the prototype emerge measuring unit corresponds to the actual current passing through the soil instruments.