Next-Generation Public Safety Systems Based on Autonomous Vehicles and Opportunistic Communications

An emergency scenario is characterized by the unpredictability of the environment conditions and by the scarcity of the available communication infrastructures. After a natural or human disaster, the main public and private infrastructures are partially damaged or totally destroyed. These infrastructures include roads, bridges, water supplies, electrical grids, telecommunications and so on. In these conditions, the first rescue operations executed by the public safety organizations can be very difficult, due to the unpredictability of the disaster area environment and the lack in the communications systems. The aim of this work is to introduce next-generation public safety systems where the main focus is the use of unmanned vehicles that are able to exploit the self-organizing characteristics of such autonomous systems. With the proposed public safety systems, a team of autonomous vehicles will be able to overcome the hazardous environments of a post disaster scenario by introducing a temporary dynamic network infrastructure which enables the first responders to cooperate and to communicate with the victims involved. Furthermore, given the pervasive penetration of smart end-user devices, the emergence of spontaneous networks could constitute promising solutions to implement emergency communication systems. With these systems the survivors will be able to self-organize in a communication network that allows them to send alerts and information messages towards the rescue teams, even in absence of communication infrastructures

Robust, Resilient Networked Communication in Challenged Environments

In challenged environments, digital communication infrastructure may be difficult or even impossible to access. This is especially true in rural and developing regions, as well as in any region during a time of political or environmental crisis. We advance the state of the art in wireless networking and security to design networks and applications that rapidly assess changing networking conditions to restore communication and provide local situational awareness. This dissertation examines new systems for responding to current and emerging needs for wireless networks. This work looks across the wireless ecosystem of widely deployed standards. We develop new tools to improve network assessment and to provide robust and reliable network communication. By incorporating new technological breakthroughs, such as the wide commercial success of Unmanned Aircraft Systems (UAS), we introduce novel methods and systems for existing wireless standards for these challenged networks. We assess how existing technologies and standards function in difficult environments: lacking end-end Internet connectivity, experiencing overload or other resource constraints, and operating in three dimensional space. Through this lens, we demonstrate how to optimize networks to serve marginalized communities outside of first world urban cities and make our networks resilient to natural and political crisis that threaten communication

Enhancing TV White-Spaces database with Unmanned Aerial Scanning Vehicles (UASVs)

After the digital TV switch-over, national spectrum regulators are considering opportunistic spectrum access techniques in the TV White Spaces (TVWS) frequency band. At present, the reference solution envisages the utilization of geolocation spectrum databases (GLDBs), in which spectrum availability is computed through complex propagation models. However, recent studies indicate that the used path loss model in GLDBs could be either inaccurate or too much conservative, possibly reducing the use of TVWS for opportunistic use by secondary networks. In this paper, we investigate the possibility to enhance the estimation accuracy of GLDBs with sensing reports produced by a swarm of Unmanned Aerial Scanning Vehicles (UASVs). These latter are able to explore the scenario in both space and frequencies, and to build a fine-grained shadowing map which can be used to tune the accuracy of propagation model used by GLDB. A novel distributed mobility algorithm is described for the sensing coverage of the scenario, and an aggregation mechanism for the map creation is illustrated. Simulation results confirm the effectiveness of our scheme in terms of TVWS detection accuracy and scenario coverage issues