The PriMO-5G firefighting use cases present scenarios that could benefit significantly (from an operational perspective) by leveraging 5G technologies and related enhancements including networking slicing and edge computing. However, these solutions need to optimized and adopted to meet technical and operational requirements of hostile and constrained firefighting environments. To that end, one of most promising tools is the use artificial intelligence (AI) algorithms to manage and optimize computing and networking resources in this context.
The PriMO-5G has released a deliverable D4.1 – Intermediate report on AI-assisted networking and edge computing, that presents potential solutions for AI-assisted networking and edge computing. In AI-assisted networking, the use of AI is proposed for optimizing spectrum sharing, distributed machine learning, communication scheduling, caching, and simulation for networked firefighting drones (see figure below). Whereas, for AI-assisted edge computing some of these aspects and others (e.g. drone battery constraints) are considered for edge processing of different applications (e.g. HD video processing) relevant for firefighting.