Sherif Tolba

• PhD
• University of Connecticut

Identifying the location of a target in an unbounded underwater environment is a challenging task. Limited and intermittent communication only adds to the difficulty of the process. Many target search algorithms use communication as an essential structural component to coordinate Autonomous Underwater Vehicles’ (AUV) motion and share sensory inform...

Particle Swarm Optimization (PSO) can be used in swarm robotic search tasks to find extrema that represent targets. PSO assumes that particles can update their positions and velocities instantaneously in each iteration of the algorithm. For optimization purposes, this assumption is acceptable, however, it is not suitable when the algorithm is to be...

Large scale missions in unpredictable and unstable underwater environments are beyond the capabilities of a single intelligent and complex robot. Relying on one robot is far from optimal as loss of the unit means failure of the whole mission. On the contrary, robotic swarms depend on large numbers of simple, cheap, and error-prone robots that exhib...

A city-wide deployment of advanced sensing technology will, undoubtedly, transform the way we live and interact with the surroundings. A countless number of applications would be feasible if such deployment is available. Of immense importance is the protection of roads and other important infrastructure of a city. This is only one such applica...

Underwater Sensor Networks (UWSN) have several applications in aquatic environments ranging from target tracking to environmental monitoring. Harsh nature of underwater environments and different conditions and properties of the medium compared to on-ground environment pose some challenges when it comes to the design of a robust system. One of thes...

Modern ocean exploration and sensing approaches have been mainly based on Autonomous Underwater Vehicles (AUVs), Remotely Operated Vehicles (ROVs), and/or static Underwater Acoustic Sensor Networks (UASNs) deployments. Individual AUVs and ROVs represent a single point of failure in addition to being bulky and expensive as vehicles are usually full-...

Underwater sensor networks (UWSN) have two major challenges: limited bandwidth and high propagation delay. In-network processing can improve the performance of UWSN data flow in the network, leading to better channel utilization. In order to do this, processing nodes have to be deployed to perform local processing, such as compression, mining, and...

Underwater Sensor Networks are associated with a number of applications that require real-time delivery of large data. Examples include: still frame images or full-motion videos in seismic monitoring setups, oil pipe leak detection, and capturing sea activities. However, the transmission of large data relying only on acoustic communication is chall...

High-speed rail (HSR) holds promise as an investment to modernize our country's transportation infrastructure and serve as a driver for our national economy. The five-hundred billion dollar price tag necessitates thorough analysis and planning upfront to ensure long-term success, including a well formulated vulnerability analysis to identify an opt...

An important challenge for homeland security agencies is to properly understand the interaction between terrorists and the methods to protect and deter attacks on the transportation network. Examining the nature of these interactions can greatly assist the enhancement of existing technologies and guide the development of new ones. This interaction...

In transportation networks, the vulnerable links will be those which play a critical role and are therefore the most likely to be attacked. High-volume edges with few alternative paths represent obvious system vulnerabilities. Conflict between a terrorist organization and a transportation management agency can be characterized as two opponents who...