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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. 

To facilitate research in dynamic spectrum access, 5G, vehicular networks, underground wireless communications, and radio frequency machine learning, a city-wide experimental testbed is developed to provide realistic radio environment, standardized experimental configurations, reusable datasets, and advanced computational resources. The testbed contains 5 cognitive radio sites, and covers 1.1 square miles across two campuses of the University of Nebraska-Lincoln and a public street in the city of Lincoln, Nebraska. Each site is equipped with a 4x4 MIMO software-defined radio transceiver with 20Gbps fronthaul connectivity. Additional cognitive radio transceivers with an underground 2x2 MIMO antenna are included in a site. High speed fronthaul network based on dedicated fiber connects the 5 sites to a cloud-based central unit for data processing and storage. The testbed provides researchers rich computational resources such as arrays of CPUs and GPUs at the cloud and FPGAs at both the edge and fronthaul network. Developed via the collaboration of the university, city, and industrial partners, this testbed will facilitate education and researches in academic and industrial communities.