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Preface
is book is a product of collaboration between the Sensor, Signal & Information Processing
(SenSIP) center at Arizona State University and NXP Semiconductor’s sensor division. SenSIP
is one of the sites of the Industry/University Cooperative Research Center (I/UCRC) for Net-
Centric Software and Systems, partially sponsored by the National Science Foundation and
industrial members. Freescale Semiconductor (now a part of NXP) joined SenSIP in 2014, and
the two organizations began a joint project to explore the use of sensors and machine learning
techniques in the context of machine condition monitoring.
Student investigators Jongmin Lee (now Dr. Lee, and an NXP engineer) and Uday
Shankar Shanthamallu worked under the supervision of SenSIP director Dr. Andreas Spanias
and Michael Stanley at NXP to evaluate the application of standard machine learning techniques
to the embedded design space. We were specifically interested in bringing machine learning
techniques to the IoT “leaf node”.
Prior to joining SenSIP, Stanley, Mark Pedley, and Dr. Zbigniew Baranski of NXP spent
significant efforts developing and documenting what is now the open-sourced NXP Sensor Fu-
sion Library. Stanley also wrote a series of blogs on sensor and sensor fusion topics.
As we gained additional insights during the SenSIP project, we began to consider pulling
materials from that project, as well as our existing blogs and sensor fusion documentation for
an overview book on topics of sensors for IoT and machine learning. is book is a result of
that effort. It is intended to provide a sampling of sensor and sensor data analysis topics, with
sufficient references to allow the interested user to follow up on specific areas of interest.
Michael Stanley and Jongmin Lee
December 2017
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