Events Calendar

Oral Defense Dissertation

Speaker: Nan Li, Ph.D. Candidate, Astani Departmentof Civil and Environmental Engineering, USC

Talk Title: A Radio Frequency Based Indoor Localization Framework For Supporting Building Emergency Response Operations

Abstract: Building emergencies especially structure fires are big threats to the safety of building occupants and first responders. When emergencies occur, unfamiliar environments are difficult and dangerous for first responders to search and rescue, sometimes leading to secondary casualties. One way to reduce such hazards is to provide first responders with timely access to accurate location information. Despite its importance, access to the location information at emergency scenes is far from being automated and efficient. This thesis assesses the value of location information through a card game, and identifies a set of important requirements for indoor localization through a survey. The most important five requirements are: accuracy, ease of on-scene deployment, resistance to damages, computational speed, and device size and weight. The thesis proposes a radio frequency based indoor localization framework. When there is usable existing sensing infrastructure in a building, an iterative maximum likelihood estimation localization algorithm is proposed for the framework. The algorithm integrates a maximum likelihood estimation technique for location computation. The algorithm also introduces an iterative process that mitigates impacts of radio signal’s multipath and fading effects on localization accuracy. When no existing sensing infrastructure is accessible and an ad-hoc sensor network needs to be established, an environment aware beacon deployment algorithm is proposed for supporting a sequence based localization schema. The algorithm is designed to achieve dual objectives of improving room-level localization accuracy and reducing the effort required to deploy the ad-hoc sensor network. Moreover, building information models are integrated to both algorithms. Building information plays an important role in mitigating multipath and fading effects in iterative location computation, enabling the metaheuristic based search for building-specific satisfactory beacon deployment plans, and providing a graphical interface for user interaction and result visualization. The framework was validated in both simulations and real-world experiments. The simulations involved two fire emergency scenarios in an office building, and reported room-level accuracies of above 87.0% and coordinate-level accuracies of above 1.78 m. The real-world experiments involved the same test bed and scenarios, and used a smartphone based prototype. The experiments reported room-level accuracies of above 82.8% and coordinate-level accuracies of above 2.29 m. The framework was also proven to be deployable in limited time and robust against partial loss of devices, and could promisingly satisfy other aforementioned important requirements for indoor localization at building emergency scenes.

Location: Kaprielian Hall (KAP) - 209 Conference Room

Audiences: Everyone Is Invited

Contact: Evangeline Reyes