Towards Dense and Scalable Soil Sensing Through Low-Cost WiFi Sensing Networks

Abstract

Precision agriculture uses precise sensor data collected throughout farmland to give farmers better insight into their land, allowing for greater crop yields and reduced resource usage. However, existing solutions require high hardware costs thus limiting large scale deployments. To address that, we propose a low-cost and scalable solution for sensing physical attributes of soil using IoT based WiFi sensing devices. By understanding variations in WiFi radio signals with channel state information (CSI) and machine learning models, we evaluate the proposed soil sensing system through experiments on physical soil traits such as soil moisture content, soil texture and position. Moreover, we also demonstrate how a mesh network of WiFi sensing devices allows us to predict the physical traits of the soil in the area between each pair of sensors, allowing for an increase in sensing area coverage as nodes are added.

Wi-CaL: WiFi Sensing and Machine Learning Based Device-Free Crowd Counting and Localization

“…They conducted a hallway experiment to investigate the capability of ESPbased device-free WiFi sensing for single-person detection and walking direction prediction, even if the Tx/Rx ESP nodes are lined up behind the same side of a wall. In addition, they also presented a method of soil sensing by using ESP nodes in [36], demonstrating that ESP-based WiFi sensing is effective not only for human sensing. By [35], [36], they showed the feasibility of this compact ESP32 becoming an alternative solution of WiFi sensing.…”

“…In addition, they also presented a method of soil sensing by using ESP nodes in [36], demonstrating that ESP-based WiFi sensing is effective not only for human sensing. By [35], [36], they showed the feasibility of this compact ESP32 becoming an alternative solution of WiFi sensing. In this paper, we also adopt the ESP32 CSI toolkit and ESP32 WiFi nodes, which are shown in Figure 1 node has a great advantage in terms of easy and flexible deployment.…”

“…Since the ESP32 nodes are powered, the AP continuously sends CSI requests to the STA, Then, the STA returns the observed CSI information to the AP so that we can get the channel state between AP and STA from the AP side. The ESP32 nodes are operated on 802.11n legacy mode WiFi, which uses 2.4 GHz band (bandwidth: 20 MHz) and consists of 52 non-null subcarriers [35], [36].…”

A Wireless Underground Sensor Network Field Pilot for Agriculture and Ecology: Soil Moisture Mapping Using Signal Attenuation

“…Studies have included examining power consumption [ 30 , 33 , 34 , 35 ], as well as the deployment of communication protocols such as Mica [ 14 ], Zigbee [ 36 ], Wi-Fi [ 37 , 38 ], RFID [ 39 ], cellular [ 37 ], Sigfox [ 10 ], and Lora [ 12 , 35 ] for WUSNs. While experimental WUSN evaluations have been carried out in laboratory testbeds [ 9 , 22 , 40 , 41 , 42 ] and in some outdoor environments [ 10 , 12 , 43 , 44 , 45 , 46 ] and agricultural farms [ 14 , 19 , 32 , 43 , 47 , 48 , 49 , 50 ], testing has been limited, often with one or a few sensor nodes. There are no studies of WUSNs deployed deep in the vadose zone and tested under “real-life” conditions, long time periods, including multiple seasons, and over large areas of active agricultural management.…”