TinyOS-based real-time wireless data acquisition framework for structural health monitoring and control

Wireless smart sensor networks have become an attractive alternative to traditional wired sensor systems to reduce implementation costs of structural health monitoring systems. The onboard sensing, computation, and communication capabilities of smart wireless sensors have been successfully leveraged in numerous monitoring applications. However, the current data acquisition schemes, which completely acquire data remotely prior to processing, limit the applications of wireless smart sensors (e.g., for real-time visualization of the structural response). Although real-time data acquisition strategies have been explored, challenges of implementing high-Throughput real-time data acquisition over larger network sizes still remain because of operating system limitations, tight timing requirements, sharing of transmission bandwidth, and unreliable wireless radio communication. This paper presents the implementation of real-time wireless data acquisition on the Imote2 platform. The challenges presented by hardware and software limitations are addressed in the application design. The framework is then expanded for high-Throughput applications that necessitate larger networks sizes with higher sampling rates. Two approaches are implemented and evaluated on the basis of network size, associated sampling rate, and data delivery reliability. Ultimately, the communication and processing protocol allows for near-real-time sensing of 108 channels across 27 nodes with minimal data loss.