Multimedia Analysis
& Retrieval (MARS)
The MARS project designed and developed an integrated
multimedia information retrieval and database management infrastructure,
entitled Multimedia Analysis and Retrieval System (MARS), that supported
multimedia information as first-class objects suited for storage and retrieval
based on their content. Specifically, research in the MARS project focused on
content representation, multimedia information retrieval, multimedia feature
indexing, and multimedia data management. MARS pioneered the usage of relevance
feedback mechanisms in multimedia retrieval. Furthermore, as part of MARS we
developed amongst the most scalable techniques for high dimensional data
indexing and retrieval.
MARS
was funded by NSF through the CAREER award for Prof. Mehrotra
Quality Aware Sensor
Infrastructure (QUASAR)
The
Quasar project investigated issues related to data management in sensor
enriched environments. Unlike
conventional distributed database systems, a sensor
data architecture must handle extremely high data generation rates from a large
number of small autonomous components. And, unlike the emerging paradigm of
data streams, it is infeasible to think that all this data can be streamed into
the query processing site, due to severe bandwidth and energy constraints of
battery-operated wireless sensors. Thus, sensing data architectures must become
quality-aware, regulating the quality of data at all levels of the
distributed system, and supporting user applications' quality requirements in
the most efficient manner possible.
QUASAR
Project was funded by NSF through a medium ITR grant.
Advances
in the networking technologies have triggered one of the key industry
responses, the "software as a service" initiative, also referred to
as the application service provider (ASP) model. To address the above-stated
problem, the DAS project pioneered the concept of "Database as a service" model that
inherits all the advantages of the ASP model, indeed even more, given that a
large number of organizations have their own DBMSs. The model allows
organizations to leverage hardware and software solutions provided by the
service providers, without having to develop them on their own, thereby freeing
them to concentrate on their core businesses. The DAS project explored the viability of
database-as-a-service (DAS) model. The project made pioneering contributions to
understanding and realizing challenge of data privacy in outsourcing.
The DAS project was funded by NSF through a small ITR grant.
RESCUE
Project
Responsphere Project
Funded
by NSF through the infrastructure grant, this project created a campus level
sensing testbed including cameras, acoustic sensors,
sensor motes, cell phones, motion sensors, RFID, etc. to create a deeply sensed
environment that supported research on various aspects of crisis response. It allowed
us to capture campus level emergency drills, capture, store and analyze data
from it. Various innovative solutions including a new architecture for sensor
data processing entitled SATWARE, a Fire Incident Command Board (FICB), a
Disaster Portal came out as a result of Responsphere.
Responsphere was also integral
to support variety of research in RESCUE.
SAFIRE Project
SATWARE Project