An underground, wireless, open-source, low-cost system for monitoring oxygen, temperature, and soil moisture

Abstract

Abstract. The use of wireless sensor networks to measure soil parameters eliminates the need to remove sensors for field operations, such as tillage, thus allowing long-term measurements without multiple disturbances to soil structure. Wireless sensors also reduce above-ground cables and the risk of undesired equipment damage and potential data loss. However, implementing wireless sensor networks in field studies usually requires advanced and costly engineering knowledge. This study presents a new underground, wireless, open-source, low-cost system for monitoring soil oxygen, temperature, and soil moisture. The process of system design, assembly, programming, deployment, and power management is presented. The system can be left underground for several years without the need to change the battery. Emphasis was given on modularity so that it can be easily duplicated or changed if needed and deployed without previous engineering knowledge. Data from this type of system have a wide range of applications, including precision agriculture and high-resolution modelling.

Internet of Underground Things in Agriculture 4.0: Challenges, Applications and Perspectives

“…In recent years, WUSNs have started to be implemented in real field conditions, mainly on corn crops. We can cite, for example, [64,66,67,69], who respectively used buried sensor nodes to optimize the irrigation in corn and soybean crops (continental climate; Illinois, USA), corn crops (continental climate; Nebraska, USA), poplar orchards (Mediterranean climate; California, USA) and corn crops (continental climate, Germany). The adoption and deployment of such smart irrigation systems will become essential in the near future to face the global warming and the increasing water scarcity.…”

“…Research works in data collection.Experiment 23 nodes in an agricultural field and predict soil VWC[65] -Develop a UG2AG link to manage a pivot irrigation system[62] -Evaluate LoRa at 433 MHz in UG2UG and UG2AG[66] -Evaluate LoRa at 915 MHz in UG2AG[63] -Evaluate UG2AG in LoRa in UG2AG[12] -Evaluate UG2AG in LoRa at 433 and 868 MHz[67] -Develop a UG2AG link to manage a pivot irrigation system[61] -Experiment UG2AG in LoRa in different conditions UAV [68] -Analyze the RSSI signals received by an UAV (high altitude) [71] -Perform simulations with an UAV in hovering mode [69] -Analyze the RSSI signals received by an UAV (low altitude) [70] -Analyze the packet loss received by an UAV (low altitude)…”

Advancing “Autonomous” sensing and prediction of the subsurface environment: a review and exploration of the challenges for soil and groundwater contamination

“…Additionally, pattern recognition machine learning promises intelligent sensor/detector applications where complex chemical signals may be measured, as explored by Ballard et al ( 2021 ). Telemetering data directly back from subsurface sensors would seem improbable, but investigations are pursuing such an advancement especially related to agricultural practices (Huang et al 2020 ; Levintal et al 2022 ). As with any method, calibration of sensors and avoiding drift remains challenging if probes/sensors are to be deployed over long periods.…”

Harnessing the power of poplar tree natural genetic variation for the development of future sustainable biofuels and bioproducts: a droughted marginal-land experiment for multi-disciplinary investigations

“…The tumbling costs of DNA sequencing, improved technologies, and increased depth of genome coverage and future technological advances (Shendure et al, 2019), mean that plant traits can now more easily be resolved to the level of the gene. Alongside enhanced computational power, the potential of AI and the development of new innovative approaches in a number of contrasting technologies, from gene editing (Zhang et al, 2018) to cheap sensors in the environment (Levintal et al, 2022), improved satellite imagery, linked to plant function (Tattaris et al, 2016) and high throughput phenotyping (Tardieu et al, 2017), these new technologies are converging to drive a step change in the rate of novel discoveries on the foundational links between plant performance and genomic control. This is of critical importance to the emerging bioeconomy, and of particular interest is the scale-up and production of resilient biomass resources that can grow in resourcelimited environments with few water and nutrient inputs; land undesirable for food production, and delivering few ecosystem services (Khanna et al, 2021).…”