Abstract. Many applications for irrigation management and environment monitoring exploit buried sensors wired-connected to the soil surface for information retrieval. Wireless Underground Sensor Networks (WUSNs) is an emerging area of research that promises to provide communication capabilities to these sensors. To accomplish this, a reliable wireless underground communication channel is necessary, allowing the direct communication between the buried sensors without the help of an aboveground device. However, the significantly high attenuation caused by soil is the main challenge for the feasibility of WUSNs. Recent theoretical results highlight the potential of smaller attenuation rates with the use of smaller radio frequencies. In this work, experimental measurements are presented at the frequency of 433MHz, which show a good agreement with the theoretical studies. We observe that (a) a decrease of the frequency of the wireless signal implies a smaller soil attenuation rate, (b) the wireless underground communication channel presents a high level of temporal stability, and (c) the volumetric water content (VWC) of the soil is the most important factor to adversely affect the communication. The results show the potential feasibility of the WUSNs with the use of powerful RF transceivers at smaller frequencies (e.g., 300-500MHz band). We also propose a classification for wireless underground communication, defining and showing the differences between Subsoil and Topsoil WUSNs. To the best of our knowledge, this is the first work that reports experiment results for underground to underground communication using commodity sensor motes.
Despite the well-known advantages of communication solutions based on energy harvesting, there are scenarios where the absence of batteries (supercapacitor only) or the use of rechargeable batteries is not a realistic option. Therefore, the alternative is to extend as much as possible the lifetime of primary cells (nonrechargeable batteries). By assuming low duty-cycle applications, three power-management techniques are combined in a novel way to provide an efficient energy solution for wireless sensor networks nodes or similar communication devices powered by primary cells. Accordingly, a customized node is designed and long-term experiments in laboratory and outdoors are realized. Simulated and empirical results show that the battery lifetime can be drastically enhanced. However, two trade-offs are identified: a significant increase of both data latency and hardware/software complexity. Unattended nodes deployed in outdoors under extreme temperatures, buried sensors (underground communication), and nodes embedded in the structure of buildings, bridges, and roads are some of the target scenarios for this work. Part of the provided guidelines can be used to extend the battery lifetime of communication devices in general.
Geophysical products generated from remotely sensed data require validation to evaluate their accuracy. Typically in situ measurements are used for validation, as is the case for satellite-derived soil moisture products. However, a large disparity in scales often exists between in situ measurements (covering meters to 10s of meters) and satellite footprints (often hundreds of meters to several kilometers), making direct comparison difficult. Before using in situ measurements for validation, they must be 'upscaled' to provide the mean soil moisture within the satellite footprint. There are a number of existing upscaling methods previously applied to soil moisture measurements, but many place strict requirements on the number and spatial distribution of soil moisture sensors difficult to achieve with permanent/semi-permanent ground networks necessary for long-term validation efforts. A new method for upscaling is presented here, using Random Forests to fit a model between in situ measurements and a number of landscape parameters and variables impacting the spatial and temporal distributions of soil moisture. The method is specifically intended for validation of the NASA Soil Moisture Active Passive (SMAP) products at 36, 9 and 3 km scales. The method was applied to in situ data from the SoilSCAPE network in California, validated with data from the SMAPVEX12 campaign in Manitoba, Canada with additional verification from the TxSON network in Texas. For the SMAPVEX12 site the proposed method was compared to extensive field measurements and was able to predict mean soil moisture over a large area more accurately than other upscaling approaches.
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