Precision agriculture has become a promising paradigm to transform modern agriculture. The recent revolution in big data and Internet-of-Things (IoT) provides unprecedented benefits including optimizing yield, minimizing environmental impact, and reducing cost. However, the mass collection of farm data in IoT applications raises serious concerns about potential privacy leakage that may harm the farmers’ welfare. In this work, we propose a novel scalable and private geo-distance evaluation system, called SPRIDE, to allow application servers to provide geographic-based services by computing the distances among sensors and farms privately. The servers determine the distances without learning any additional information about their locations. The key idea of SPRIDE is to perform efficient distance measurement and distance comparison on encrypted locations over a sphere by leveraging a homomorphic cryptosystem. To serve a large user base, we further propose SPRIDE+ with novel and practical performance enhancements based on pre-computation of cryptographic elements. Through extensive experiments using real-world datasets, we show SPRIDE+ achieves private distance evaluation on a large network of farms, attaining 3+ times runtime performance improvement over existing techniques. We further show SPRIDE+ can run on resource-constrained mobile devices, which offers a practical solution for privacy-preserving precision agriculture IoT applications.

Wireless underground sensor networks (WUSNs) are becoming ubiquitous in many areas. The design of robust systems requires an extensive understanding of the underground (UG) channel characteristics. In this article, the UG channel impulse response is modeled and validated via extensive experiments in indoor and field testbed settings. Three distinct types of soils are selected with sand contents ranging from 13% to 86%, and clay contents ranging from 3% to 32%. The impacts of changes in soil texture and soil moisture are investigated with more than 1, 200 measurements in a novel UG testbed at the University of Nebraska-Lincoln that allows flexibility in soil moisture control. Moreover, the time-domain characteristics of the channel, such as the RMS delay spread, coherence bandwidth, and multipath power gain, are analyzed. The power delay profile analysis validates the three main components of the UG channel: direct, reflected, and lateral waves. Furthermore, it is shown that the RMS delay spread follows a log-normal distribution. The coherence bandwidth ranges between 650 kHz and 1.15 MHz for soil paths of up to 1 m and decreases to 418 kHz for distances above 10 m. Soil moisture is shown to affect the RMS delay spread non-linearly, which provides opportunities for soil moisture-based dynamic adaptation techniques. A statistical channel model for the wireless underground channel has been developed based on the measurements and analysis. The statistical model shows good agreement with the measurement data. The model and analysis pave the way for tailored solutions for data harvesting, UG sub-carrier communication, and UG beamforming.

Wireless underground sensor networks (WUSNs) are becoming ubiquitous in many areas and designing robust systems requires extensive understanding of the underground (UG) channel characteristics. In this paper, UG channel impulse response is modeled and validated via extensive experiments in indoor and field testbed settings. Three distinct types of soils are selected with sand and clay contents ranging from 13% to 86% and 3% to 32%, respectively. Impacts of changes in soil texture and soil moisture are investigated with more than 1,200 measurements in a novel UG testbed that allows flexibility in soil moisture control. Time domain characteristics of channel such as RMS delay spread, coherence bandwidth, and multipath power gain are analyzed. The analysis of the power delay profile validates the three main components of the UG channel: direct, reflected, and lateral waves. It is shown that RMS delay spread follows a log-normal distribution. The coherence bandwidth ranges between 650 kHz and 1.15MHz for soil paths of up to 1m and decreases to 418 kHz for distances above 10m. Soil moisture is shown to affect RMS delay spread non-linearly, which provides opportunities for soil moisture-based dynamic adaptation techniques. The model and analysis paves the way for tailored solutions for data harvesting, UG sub-carrier communication, and UG beamforming.

In this demo, a novel underground communication system and an online underground sensor network testbed is demonstrated. The underground communication system, developed in the Cyber-physical Networking (CPN) Laboratory at the University of Nebraska-Lincoln, includes an underground antenna that is tailored to mitigate the adverse effects of soil on underground communication. An online connection is established with the CPN underground sensor network testbed that is located at Clay Center, Nebraska. The underground sensor network testbed consists of a network of underground communication systems equipped with soil moisture sensors and a mobile data harvesting unit equipped with cellular communication capabilities. Real-time soil moisture data delivery from Nebraska to Korea is demonstrated.