IoT Applications Computing

The evolution of emerging and innovative technologies based on Industry 4.0 concepts are transforming society and industry into a fully digitized and networked globe. Sensing, communications, and computing embedded with ambient intelligence are at the heart of the Internet of Things (IoT), the Industrial Internet of Things (IIoT), and Industry 4.0 technologies with expanding applications in manufacturing, transportation, health, building automation, agriculture, and the environment. It is expected that the emerging technology clusters of ambient intelligence computing will not only transform modern industry but also advance societal health and wellness, as well as and make the environment more sustainable. This book uses an interdisciplinary approach to explain the complex issue of scientific and technological innovations largely based on intelligent computing

A drift detecting anti-divergent EKF for online biodynamic model identification

This paper describes a novel online biodynamic model parameter estimation algorithm applied to data acquired from a small Inertial Measurement Unit network. The predicted biodynamic model represents the response motion of a human seated in a vehicle subjected to mechanical vibrations. The motivations for identifying the body model parameters are, to aid vibration isolation technologies and to continuously monitor the transmission of vibrations through the seated occupant. The algorithm consists of a bank of parallel Extended Kalman Filters for estimating each biodynamic parameter. During the posterior state prediction update step of the Extended Kalman Filter, an Adaptive Sliding Window concept drift detection algorithm maintains a variable window of past priori estimation errors. The model process error statistics are then updated based upon the statistics of the priori state errors in the window. The algorithm updates the estimator parameters incrementally and is suitable for streaming data. The estimator is applicable for cases where the distribution of the biodynamic model process noise is unknown or is abruptly varying, and when the model parameters are unknown. This estimator was evaluated experimentally with data sourced from a network of wearable wireless Inertial Measurement Units affixed to the test subject. The test subjects were then exposed to an external vibrating excitation source. The results validate that this algorithm provides accurate online estimates of the human biodynamic model parameters for a second order transmissibility model. The algorithm presented mitigates problems associated with the estimation of biodynamic parameters such as biomechanical nonlinearities, process noise drift and divergence

Aeronautical engineering: A continuing bibliography with indexes (supplement 233)

This bibliography lists 637 reports, articles, and other documents introduced into the NASA scientific and technical information system in November, 1988. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics