LoRa has emerged as a cornerstone of low-power, long-range IoT communication. While highly effective for scalar sensing, its extension to multimedia remains constrained by limited bitrate, payload size, and duty-cycle regulations. This survey reviews research on multimedia transmission over LoRa, revealing that most current efforts are image-centric, with only a few preliminary studies addressing video or audio. We propose a structured taxonomy encompassing compression and fragmentation methods, cooperative and multi-hop architectures, MAC and cross-layer optimizations, and hybrid network designs. These strategies are analyzed in the context of IoT domains such as agriculture, surveillance, and environmental monitoring. Open challenges are highlighted in extending beyond static images, ensuring energy-efficient delivery, and developing spectrum- and ML-aware protocols. The survey provides IoT researchers with both a consolidated reference and a roadmap toward practical and scalable multimedia systems over LoRa.

Long-range (LoRa) communication has emerged as a preferred low-power protocol for Internet of Things (IoT) applications in remote or infrastructure-limited environments. However, its constrained data rate poses significant challenges for transmitting high-volume data, such as images. This article presents a novel interleaved frequency transmission (IFT) framework that employs a dual-receiver architecture to significantly reduce transmission time and energy consumption for LoRa-based image communication. By alternating packet transmissions between two frequencies (915 and 914.5 MHz), the system effectively bypasses receiver-side processing delays and enables pseudo-parallel data reception. Experimental results demonstrate that IFT achieves up to 50% reduction in image transmission time and up to 59% energy savings on the transmitter side compared to traditional single frequency transmission (SFT), without requiring changes to the physical layer. Field tests across diverse environments on a Norfolk State University campus further validate the robustness of IFT, showing consistent improvements in packet reception rate, signal-to-noise ratio, and received signal strength indicator, especially in semi-obstructed areas. The proposed IFT architecture is implemented using Raspberry Pi Zero W and SX1276 LoRa modules and is evaluated under real-world deployment conditions. The findings suggest that IFT is an energy-efficient solution for visual IoT applications in agriculture, environmental monitoring, and remote sensing. Future work will explore ultralow-power microcontroller integration to further enhance system viability for long-term deployments.

LoRa has emerged as a cornerstone of low-power, long-range IoT communication. While highly effective for scalar sensing, its extension to multimedia remains constrained by limited bitrate, payload size, and duty-cycle regulations. This survey reviews research on multimedia transmission over LoRa, revealing that most current efforts are image-centric, with only a few preliminary studies addressing video or audio. We propose a structured taxonomy encompassing compression and fragmentation methods, cooperative and multi-hop architectures, MAC and cross-layer optimizations, and hybrid network designs. These strategies are analyzed in the context of IoT domains such as agriculture, surveillance, and environmental monitoring. Open challenges are highlighted in extending beyond static images, ensuring energy-efficient delivery, and developing spectrum- and ML-aware protocols. The survey provides IoT researchers with both a consolidated reference and a roadmap toward practical and scalable multimedia systems over LoRa.