# The Cloud-to-Edge-to-IoT Continuum as an Enabler for Search and Rescue Operations
## 1 Introduction  
When a natural or human disaster occurs, the first 72 hours are particularly critical to locate and rescue victims [1]. Although advanced technological solutions are being investigated by researchers and industry for search and rescue (SAR) operations, rescue teams and first responders still suffer from limited situational awareness in an emergency. The main motivation for this is a generalized lack of modern and integrated digital communication and technologies. Relying only on direct visual or verbal communication is indeed the root cause of limited situational awareness. First responders have very limited, sparse, non-integrated ways of receiving information about the evolution of an emergency and its response (e.g., team members and threat locations). A real-time visual representation of the emergency response context would greatly improve their decision accuracy and confidence on the field. _\"The greatest need for cutting-edge technology, across disciplines, is for devices that provide information to the first responders in real-time\"_[2]. Mobile robot teams comprising possibly robots with heterogeneous sensory (cameras, infrared cameras, hyperspectral cameras, light detection and ranging--LiDARs, radio detection additionally, ranging--RADARs, etc.) and mobility (land, air) capabilities have the potential of scaling up first responders' situational awareness [3]. They are, therefore, an important asset in the response to catastrophic incidents, such as wildfires, urban fires, landslides, and earthquakes as they also offer the possibility to generate 3D maps of a disaster scene with the use of cameras and sensors. However, in many cases, robots usedby first responders are remotely teleoperated, or they can operate autonomously only in scenarios with good global positioning system (GPS) coverage. Furthermore, 3D maps cannot be provided in low-visibility scenarios, such as when smoke is present, in which remote operation is also very complicated. Operating robots in scenarios such as large indoor fires requires the robots to be able to navigate autonomously in environments with smoke and/or where GPS is not available. Other advanced technologies, such as artificial intelligence (AI) and computer vision are also gaining momentum in SAR operations to fully exploit the information available through cameras and sensors and by this enable smart decision-making and enhanced mission control. On the other hand, these technologies are often very resource-demanding in time and computation. Therefore, the computational power in the cloud and at the edge of the infrastructure has shown great potential to strongly support them. Edge computing is where devices with embedded computing and \"hyper-converged\" infrastructures integrate and virtualize key components of information technology (IT) infrastructure such as storage, networking and computing. It is also the first step towards a computing continuum that spans from network-connected devices to remote clouds. To leverage this continuum, the seamless integration of capabilities and services is required. Advanced connectivity techniques such as 5G (fifth generation) mobile networks and software-defined networking (SDN) offer unified access to the edge and cloud from anywhere. Workloads can potentially run wherever it makes the most sense for the application to run. At the same time, the different environments along the continuum will work together to provide the right resources for the task at hand. The range of applications and workloads with unique cost, connectivity, performance, and security requirements will demand a continuum of computing and analysis at every step of the topology, from the edge to the cloud, with new approaches to orchestration, management, and security being required. In this context, there are several open research and technological questions that need to be addressed.