# Survey for Soil Sensing with IOT and Traditional Systems
## 3 RF-Based Soil Sensing Systems in Internet of Things (IoT)
### LoRa-Based Soil Sensing Systems  
The work of [16] is the first practical deployment of soil moisture measurement using LoRa signals in open environments. In their study, the authors introduce a system that utilizes LoRa signals to measure soil moisture without the need for specialized sensors embedded in the soil. An overview of their system is depicted in Figure 7. The antennas of the LoRa nodes are embedded in the soil. The LoRa nodes act as transmitters, whereas the LoRa gateway functions as a receiver, capable of connecting to multiple LoRa nodes. In contrast to signal types such as RFID or Wi-Fi, the LoRa gateway, which functions as a receiver, boasts greater capacity owing to its employment of modulated chip signals. This results in reduced interference among numerous concurrently transmitted LoRa chirp signals, each utilizing distinct wavelengths, bandwidths, or chip slopes. Conversely, signal categories like Wi-Fi exhibit heightened contention among concurrently transmitted signals at the receiving terminal.  
Their novel approach extends beyond merely using LoRa for data transmission in smart agriculture; they incorporate a cost-effective RF switch to alter the signal propagation path length, enabling precise moisture sensing. The soil moisture can be accurately determined with the transmission of a single LoRa packet from the node to the gateway. The underlying principle is that the soil's dielectric permittivity, which is closely linked  
Figure 7: LoRa -based soil moisture sensing system.  
to its moisture level, can be derived from the phase readings of LoRa signals, as outlined in Equations (5) and (6) in the work of [13]. To tackle the synchronization challenges between the LoRa transmitter and receiver, they introduce a cost-effective switch that outfits the LoRa node with dual antennas. Experimental results with standard LoRa nodes indicate that their system can reliably gauge soil moisture with an average error of just 3.1%, matching the performance of premium soil moisture sensors. Field evaluations confirm the system's capability to accurately detect soil moisture from a distance of 100 m between the LoRa gateway and node. Moreover, the system demonstrates resilience to interruptions from pedestrians and moving vehicles, highlighting its robust performance in outdoor environments.  
Table 4 provides a comparative summary of various IoT-based soil sensing technologies, evaluating them on metrics such as Cost, Coverage Range, Central Frequency, Energy Consumption, Node Capacity, and Prediction Error. The table reveals that soil moisture sensing systems utilizing LoRa or LTE technologies tend to offer a larger coverage range. Additionally, solutions based on LoRa or RFID excel in terms of energy efficiency and sensor node capacity. These systems are also relatively cost-effective compared to traditional soil reflectance spectroscopy, making them promising candidates for deployment in remote areas without the need for pre-processing steps. The future direction for these enhanced systems involves expanding their capability to detect a broader range of soil attributes.