Smart agriculture systems have several applications and features that aim to provide an automated agriculture process with zero human intervention. Monitoring is one of the most demanding applications of the smart agriculture system. Image and video processing are very important features in the application of smart agriculture monitoring. However, the transmission of video and images requires a large bandwidth, stable connectivity, and noiseless transmission. Notably, high-quality images usually require more bandwidth. On the other hand, the smart agriculture system usually adopts wireless communication among its elements. However, the wireless communication channel generally has some noise which inversely affects the transmission system bandwidth. There are several research efforts found in the literature to address this issue. Some of the distinguished research efforts found address that by either compressing the image or correcting the image errors. However, the smart agriculture system elements are limited in the hardware capabilities. The limitation of the system’s hardware configuration is a permanent constraint for this type of solution. This paper proposes an optimization technique to mitigate the issues encountered within the wireless channel while considering the limitation of the hardware resources. The paper jointly optimizes the resources by compressing the image and encoding it using the reed Solomon encoding technique. The results provided a 98% efficiency against the traditional unlimited resources system, along with better BER.