Sensing technology is a cornerstone for many industrial applications. Manufacturing plants and engineering facilities, such as shipboard engine rooms, require sensors to ensure product quality and efficient and safe operation. We focus on one representative application, preventative equipment maintenance, in which vibration signatures are gathered to predict equipment failure. Based on application requirements and site surveys, we develop a general architecture for this class of industrial applications. This architecture meets the application's data fidelity needs through careful state preservation and over-sampling. We describe the impact of implementing the architecture on two sensing platforms with differing processor and communication capabilities. We present a systematic performance comparison between these platforms in the context of the application. We also describe our experience and lessons learned in two settings: in a semiconductor fabrication plant and onboard an oil tanker in the North Sea. Finally, we establish design guidelines for an ideal platform and architecture for industrial applications. This paper includes several unique contributions: a study of the impact of platform on architecture, a comparison of two deployments in the same application class, and a demonstration of application return on investment.

There is a growing need to support reliable data communications in sensor networks that are capable of supporting new applications, such as, assured delivery of high-priority events to sinks, reliable control and management of sensor networks, and remotely programming/retasking sensor nodes over-the-air. We present the design, implementation, and evaluation of pump slowly, fetch quickly (PSFQ), a simple, scalable, and robust transport protocol that is customizable to meet the needs of emerging reliable data applications in sensor networks. PSFQ represents a simple approach because it makes minimum assumptions about the underlying routing infrastructure, it is scalable and energy- efficient because it supports minimum signaling, thereby reducing the communication cost for data reliability, and importantly, it is robust because it is responsive to a wide range of operational error conditions found in sensor network, allowing for the successful operation of the protocol even under highly error-prone conditions. The key idea that underpins the design of PSFQ is to distribute data from a source node by pacing data at a relatively slow speed ("pump slowly"), but allowing nodes that experience data loss to fetch (i.e., recover) any missing segments from their local immediate neighbors aggressively ("fetch quickly"). We present the design and implementation of PSFQ, and evaluate the protocol using the ns-2 simulator and an experimental wireless sensor testbed based on Berkeley motes and the TinyOS operating system. We show that PSFQ can outperform existing related techniques and is highly responsive to the various error conditions experienced in sensor networks. The source code for PSFQ is freely available for experimentation.