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
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.
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.