The integration of artificial intelligence (AI) into agriculture is revolutionizing farming practices, leveraging IoT-enabled sensors, automation, and advanced image-based diagnostics to realize smart agriculture. However, the need for high-bandwidth data transmission poses challenges, particularly in rural areas lacking robust communication infrastructure. AI-driven applications, like plant disease detection and many more, employ computationally intensive algorithms, such as convolutional neural networks (CNNs), which require remote processing of large volumes of high-definition images. Conventional sub-6GHz communication bands cannot efficiently support this data transfer due to limited bandwidth and spectrum scarcity. Millimeter-wave (mmWave) communications offer a solution, delivering multi-gigabit data rates through higher frequency signals. Yet, their limited transmission range demands frequent base stations, which are economically unfeasible for expansive farmland. We consider a model integrating mmWave technology with device-to-device (D2D) communication in the agricultural sector, allowing nearby idle devices to relay data in short hops. This approach enables efficient, high-speed data transmission over mmWave frequencies, ensuring timely and reliable data transfer for remote computation, while minimizing infrastructure costs in rural areas. Thereafter, we discuss some of the problems that come up while implementing this approach. We begin by considering the static scenario, wherein all the users and relays are static, and each user requires a high-speed path to an mmWave base station. We then begin introducing complexities like user mobility, and fairness criterion to describe how fast changing metrics are often conflicting. For example, when idle users are mobile, the dynamic nature of their positions can lead to time-varying link qualities, potentially affecting transmission stability. Taking corrective measures based on predicted link degradation is vital to maintain system throughput. Lastly, we provide a simple greedy algorithm based on hop-restricted breadth-first search (BFS) for multihop D2D path allocation over mmWaves. This algorithm prioritizes efficient, localized data transmission by selecting the shortest paths through nearby idle devices, thereby ensuring efficient relaying.