SBIR Phase I: Optimized Signal Processing Solutions for Wireless Sensor Networks

Period of Performance: 01/01/2013 - 12/31/2013


Phase 1 SBIR

Recipient Firm

Streamlined Embedded Technologies
4325 Broadgate Circle
Ellicott City, MD 21043
Principal Investigator, Firm POC


This Small Business Innovation Research Program (SBIR) Phase I project seeks to develop innovations that enable efficient design, optimization, and integration of digital systems and embedded software for signal processing in wireless sensor networks (WSNs). WSNs are used in an increasing variety of important applications, including applications in building energy management, environmental monitoring, and surveillance. However, deploying sensor nodes is challenging because such devices must be developed and operated under stringent constraints on energy consumption, cost, and reliability. The advanced signal processing solutions developed in this project will enable deployment of WSNs with significantly lower cost and energy consumption for a given set of features, and will help to maximize the performance of new WSN application features under given cost and energy constraints. This project will build on a body of extensive research on dataflow-based design and implementation of signal processing systems. The project seeks to bridge the gap between results from this basic research on dataflow-based signal processing, and important technology requirements and market needs in the digital mobile radio domain, which is targeted as an initial application area within the WSN market. The broader impact/commercial potential of this project is to enable deployment of novel applications in the rapidly growing wireless sensor network (WSN) market. The WSN market serves application areas of great interest and societal importance, including building energy management, digital mobile radio, defense, environmental monitoring, and surveillance. The utility of WSNs often depends on the level of functionality that can be embedded in the network nodes under severe cost and energy constraints. This project will help to enable more powerful WSN deployments through its objectives in providing energy-efficient use of more complex processing hardware, more sophisticated software, and more advanced sensors. These optimized sensing and signal processing capabilities can be leveraged to significantly enhance important design objectives, including reliability and security, in addition to providing more functionality to end users. Also, the innovation pursued in this project will enhance scientific and technological understanding by enabling the efficient integration of more sophisticated and heterogeneous combinations of hardware and software subsystems in WSNs. This understanding will help WSN system developers to envision new applications for their technologies, thereby helping to catalyze further innovations and economic benefits.