Next-Gen IoT Architecture: Long-Range, Low-Bandwidth Video Transmission Using GenAI
This paper introduces a groundbreaking IoT frame-work combining the Luckfox Pico Max RV1106 with LoRa (RYLR998) for low-bandwidth, long-range video transmission. The system integrates YOLOv5 Tiny for efficient edge processing, enabling real-time object detection and metadata generation directly on the Luckfox Pico Max RV1106. Detected metadata, including object, bounding box coordinates, confidence scores, is transmitted via LoRa to a central server. At the server, a large language model (LLM) processes the metadata to reconstruct a simulated visualization of the detected scene, offering a low-power alternative to full video transmission. The architecture demonstrates significant scalability, low energy consumption, and high reliability, making it ideal for remote surveillance, smart cities, and autonomous systems. By offloading computation to edge devices and utilizing LLM-based reconstruction, this approach showcases a transformative vision for future IoT networks emphasizing efficiency, scalability, and innovative data processing.
Authors
- Salim Bitam (ORCID: https://orcid.org/0000-0001-5618-4126)
- A Mellouk
- Abdelhak Heroucha
Institutions
- Université Paris-Est Créteil (FR)
- University of Biskra (DZ)
- Paris-Est Sup (FR)
Publication Details
- Published
- 2025-01-28
- DOI
- https://doi.org/10.1109/isnib64820.2025.10983192
- Primary Topic
- CCD and CMOS Imaging Sensors
- Type
- article
- Field-Weighted Citation Impact
- 0.00