TY - GEN
T1 - A systems engineering approach to wireless integration, design, modeling, and analysis of nanosensors, networks, and systems
AU - Mohan, Seshadri
AU - Al-Rizzo, Hussain M.
AU - Babiceanu, Radu
AU - Elwi, Taha
AU - Ghimire, Rabindra
AU - Huang, Guoliang
AU - Khalil, Haider
AU - Rucker, Daniel
AU - Singh, Chitranjan
AU - Varadan, Vijay
AU - Yoshigoe, Kenji
AU - Zhu, Rui
PY - 2010
Y1 - 2010
N2 - Wireless nano sensors networks are being increasingly applied in many real-world applications, such as structural health monitoring, medical applications, smart clothes, battlefield communications, and intelligent highway systems. A systems approach to such applications require end-to-end infrastructure that includes sensors and sensor networking, wireless communication, reliable backbone networking,, computing infrastructure and other supporting systems. In fact, it fairly clear that sensor systems, communications systems, and computing systems need to interwork together to form a system of systems. The design and implementation of such complex systems need to take into consideration their intended functionality, operational requirements, and expected lifetime. Systems engineering provides the design and implementation framework to successfully bring large complex systems into operation by integrating multiple engineering disciplines into a structured development process, starting with identification of the need, and defining the initial concept, to formulating the requirements to detailed design, development and then, implementation. This paper brings together aspects of research that is being conducted as part of the Arkansas ASSET initiative, which is a multi-campus project supported by NSF Section 2 provides a systems engineering life-cycle modeling approach. Section 3 develops modeling and analysis of nanowires for a biological application. Section 4 provides insights into the design of wireless interfaces to provide wireless capability to wearable sensors for medical applications. Section 5 discusses the application of multiple input multiple output (MIMO) to improve reliability in wireless Section 6 proposes a data-driven adaptive transmission mechanism to improve both data quality and energy efficiency. Section 7 provides insights into the development of protocols for reliable transport of data over a wavelength division multiplexed optical transport network. Section 8 summarizes our findings.
AB - Wireless nano sensors networks are being increasingly applied in many real-world applications, such as structural health monitoring, medical applications, smart clothes, battlefield communications, and intelligent highway systems. A systems approach to such applications require end-to-end infrastructure that includes sensors and sensor networking, wireless communication, reliable backbone networking,, computing infrastructure and other supporting systems. In fact, it fairly clear that sensor systems, communications systems, and computing systems need to interwork together to form a system of systems. The design and implementation of such complex systems need to take into consideration their intended functionality, operational requirements, and expected lifetime. Systems engineering provides the design and implementation framework to successfully bring large complex systems into operation by integrating multiple engineering disciplines into a structured development process, starting with identification of the need, and defining the initial concept, to formulating the requirements to detailed design, development and then, implementation. This paper brings together aspects of research that is being conducted as part of the Arkansas ASSET initiative, which is a multi-campus project supported by NSF Section 2 provides a systems engineering life-cycle modeling approach. Section 3 develops modeling and analysis of nanowires for a biological application. Section 4 provides insights into the design of wireless interfaces to provide wireless capability to wearable sensors for medical applications. Section 5 discusses the application of multiple input multiple output (MIMO) to improve reliability in wireless Section 6 proposes a data-driven adaptive transmission mechanism to improve both data quality and energy efficiency. Section 7 provides insights into the development of protocols for reliable transport of data over a wavelength division multiplexed optical transport network. Section 8 summarizes our findings.
UR - http://www.scopus.com/inward/record.url?scp=77953409998&partnerID=8YFLogxK
U2 - 10.1117/12.849763
DO - 10.1117/12.849763
M3 - Conference contribution
AN - SCOPUS:77953409998
SN - 9780819480613
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Nanosensors, Biosensors, and Info-Tech Sensors and Systems 2010
T2 - Nanosensors, Biosensors, and Info-Tech Sensors and Systems 2010
Y2 - 8 March 2010 through 11 March 2010
ER -
