SBIR-STTR Award

This SBIR Phase I research project seeks to develop asset tracking methods for complex environments. Location-based data methods will be built as a middleware platform that leverages the strengths of traditional systems for managing simple alphanumeric data. Research will include the necessary steps to develop simple demonstration applications that can be used to show scalable querying, updating, and location based trigger evaluation features. The expected outcome is a system that augments existing data management applications with powerful location-based data management capabilities that informs critical business decisions. The proposed methods could lead to improved efficiencies in applications where asset tracking represents a significant resource drain. For example, commercial deployment of these methods could prevent a nurse from spending hours searching for lost diagnostic equipment, leading to improved efficiencies and eventually eliminating what is now an issue costing individual care units hundreds of thousands of dollars a year

This Small Business Innovation Research Phase II project aims to design, implement, and test scalable methods for providing location-based services, with a special emphasis on mobile cell phone applications. Examples of such applications include continuous monitoring of static and dynamic geo-fences, building dynamic mobile social networks, and mobile e-commerce. The Phase II effort will develop methods to push the efficiency of the location-based computation techniques, and develop methods for more sophisticated features such as privacy management and mobile power management, which will be crucial for the wider adoption of location-based applications. Location data is currently generated by continually moving physical objects equipped with location-based sensors, such as GPS and Wi-Fi based tags. Data management methods for these datasets require dealing with high update rates, large volumes of historical location data, and location-based triggers that raise an alert when the location of a moving object meets certain criteria (for example, if an object is beyond a well-defined boundary). Existing methods for supporting applications that have these requirements are not scalable. The broader merits of this project include the development of a technology that has a potentially large commercial value and addresses an emerging market need. For example, for the cell phone market, these location-based services are projected to grow from $464M in 2007 to over $11B by 2011. If successful, the potential impact in both consumer and enterprise markets for location-based services could be substantial.