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Millimeter-wave (mmWave) spectrum offers wide bandwidth resources that are promising to realize high- throughput wireless communications in agricultural fields. Due to the relatively small wavelength at this frequency band, mmWave signals tend to be scattered when the wireless link is established above the crop canopy. However, little is known about the scattering effect caused by crop canopy at mmWave. In this work, the scattering loss in the mmWave spectrum is quantified for different crop canopy states that are represented by the leaf area index. In particular, an approach based on a Rayleigh roughness criterion is utilized, coupled with canopy height statistics, to calculate the scattering loss. The results of the model agree well with empirical data collected from agricultural field experiments conducted in Summer 2021. The results demonstrate that as the leaf area index decreases with crop maturity, the scattering loss also decreases. This is the first work that illustrates the feasibility of using the mmWave communication links to perform sensing on the leaf area index, which is a critical metric in estimating crop conditions. 

Climate change resulting from releasing greenhouse gases into the atmosphere continues to affect the Earth’s ecosystem. This pressing issue is driving the development of novel technologies to sense and measure harmful gas emissions. In parallel, the evolution of wireless communication networks requires the wider deployment of mobile telecommunication infrastructure. The terahertz (THz) spectrum is currently under-utilized but is expected to feature in 6G. The use of this spectrum is explored simultaneously for ultra-broadband communication and atmospheric sensing. For atmospheric sensing, the absorption of THz signals by gas molecules is used to estimate atmospheric gas composition. Molecular absorption loss profiles for each gas isotopologue are taken from the HITRAN database and compared with data from transceivers in sensing mode. Preliminary results are presented, showing the effects of signal path loss and power spectral density. A 6G network architecture is proposed to indicate how 6G infrastructure can perform climate change sensing, in addition to its primary purpose of wireless communication. 

Reliable Terahertz (THz) links are necessary for outdoor point-to-point communication with the exponential growth of wireless data traffic. This study presents a modified Monte Carlo simulation procedure for estimating THz link attenuation due to multiple scattering by charged dust particles on the THz beam propagation path. Scattering models are developed for beams through dust, based on Mie and Rayleigh approximations for corresponding frequencies on Earth (0.24 THz) and Mars (0.24 & 1.64 THz). The simulation results are compared, considering parameters such as the number of Monte-Carlo photon (MCP) packets, visibility, dust particle placement density along the beam, frequency, and distance between the transmitter and the receiver. Moreover, a channel capacity model was proposed, considering THz link attenuation due to dust storms, spreading loss, and molecular absorption loss for Earth and Mars outdoor environments. Simulation results for Earth show that the link attenuation increases with dust particle placement density, distance, and frequency, and attenuation decreases with visibility and MCP packets. On Mars, similar results are obtained for both frequencies, except that the attenuation varies around a constant value with the frequency increase. Moreover, attenuation is slightly higher at 0.24 THz frequency compared to 1.64 THz when more dust particles are present on the beam propagation path. Channel capacity is estimated for Earth and Mars environments considering time and distance-dependent scenarios. Time windows that show a sudden drop of dust particles along the beam provide opportunities to communicate with high reliability. Moreover, increasing the distance between the transmitter and receiver severely reduces the channel capacity measurement in strong dust storm conditions in both environments. Our study has found that weak dust storms have relatively little effect on Mars but much more significant effects on Earth. 

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.