SECReT 2010 PhD projects
- Metal oxide semiconductor gas sensors as an electronic nose for the detection of microbial agents
- What are the factors that make communities vulnerable to, or resistant against, the emergence of radicalising settings?
- Covert taggant nanoparticle inks - discovery, process and product development, and analysis for sustainability and efficiency
- Diffusion processes of political violence: The role of information
- Engineering IT risk awareness, education and training
- Three-dimentional imaging of baggage for security applications.
- Understanding the traffic-driven epidemic spreading in scale-free networks
- Optimal search and detection of targets in an uncertain environment using unmanned aerial vehicle
- Explosive residue: Evaluation and optimisation of detection and sampling procedures
- Forecasting adversary’s scenarios: Systemic competitive red teaming
- Secure digital archive and web search using a Probably Approximately Correct architecture
- Mobilising community resilience through techno-social innovation
- Numerical modelling/empirical analysis of civil conflict
- Landmine, IED, UXO Detection using Ground Penetrating Radar from an Unmanned Aerial Vehicle
- Towards a usable and less disruptive security in the workplace
- Securing from exploits using information theoretical techniques
- Crime drop in Chile: Searching for causes and mechanisms
- Inferring user behaviour despite wireless network encryption
- The Chain of Evidence - a critical appraisal of the applicability and validity of forensic research and the usability of forensic evidence
Optimal search and detection of targets in an uncertain environment using unmanned aerial vehicle
7 March 2012
There is a growing interest in optimal search and detection of targets in an uncertain environment using modern electronic surveillance technologies such as network of RADAR’s and UAV’s. In specific, the UAV missions for a number of security applications increasingly require high level of information acquired from various sources and assets that are used for planning and decision aiding capabilities. Therefore, it is extremely important in the quality and timeliness of this information considering the limited time and energy of a UAV. As a result, there is a need to predict the consequences of the UAV actions in an uncertain environment.
The proposed research investigates the potential use of Bayesian based probability models that would determine the prior information with new information and update the probabilistic situational awareness; thereby optimising search techniques. Of particular interest is the optimal search and location of targets in an uncertain environment. In an uncertain situation, the target location is unknown; therefore it is imperative to make the best use of any prior information that is associated with targets existence. However, a number of issues need to be considered. These would include environmental, terrain, target characteristics, technical and human factors. The understanding of technological architectures and their operational use is also an important component of this research.