Preface
The Internet of Things (IoT) is a hot concept and developed rapidly in recent years. It
is an important component of the future generation of information systems. The emergence of IoT is another information technology revolution after computer, internet,
and mobile communication. As one of the core technologies in the field of IoT perception, Radio Frequency Identification (RFID) is a non-contact automatic identification
technology that developed rapidly in the 1990s. It is a non-contact two-way communication of inductive or electromagnetic radiation, using radio waves and microwaves,
to achieve purposes of automatic identification of target objects, access to relevant
data, and data exchange.
The concept of “physical anti-collision” proposed in this book is relative to the
software anti-collision. It is found that the reasons for multi-tag collisions that occur
in the frequency bands above Ultra High Frequency (UHF) have both the inherent
design of algorithm flaws and physical interferences such as some tags that cannot
be identified due to various external physical interferences. Physical anti-collision
mainly solves the problem of the low batch recognition success rate caused by
the latter. Therefore, physical collision avoidance is defined as the use of physical means to solve the problem of the multi-tag collision caused by non-software
factors. The front-end of the physical anti-collision system uses physical means to
collect data, for example, image sensors are used to collect the geometric characteristics of multi-label distribution, and the back-end uses neural network algorithms to
learn, train, and predict the physical optimal distribution structure, and then adjust
the label arrangement through physical means, angle, to achieve the overall optimal
recognition performance of the tag group.
This book is based on the basic principles of physics (including electromagnetics,
optics, thermodynamics, etc.), with engineering mathematical methods as the core of
detection and control algorithm design. Furthermore, this book innovatively applies
semi-physical verification and detection technology to the dynamic performance
testing of Radio-Frequency Identification (RFID) systems. This book proposes a
series of new theories and methods for physical collision prevention, as well as related
test verification methods for building semi-physical hardware platforms based on
photoelectric sensing technology, which will provide important theories and technical
v
The Internet of Things (IoT) is a hot concept and developed rapidly in recent years. It
is an important component of the future generation of information systems. The emergence of IoT is another information technology revolution after computer, internet,
and mobile communication. As one of the core technologies in the field of IoT perception, Radio Frequency Identification (RFID) is a non-contact automatic identification
technology that developed rapidly in the 1990s. It is a non-contact two-way communication of inductive or electromagnetic radiation, using radio waves and microwaves,
to achieve purposes of automatic identification of target objects, access to relevant
data, and data exchange.
The concept of “physical anti-collision” proposed in this book is relative to the
software anti-collision. It is found that the reasons for multi-tag collisions that occur
in the frequency bands above Ultra High Frequency (UHF) have both the inherent
design of algorithm flaws and physical interferences such as some tags that cannot
be identified due to various external physical interferences. Physical anti-collision
mainly solves the problem of the low batch recognition success rate caused by
the latter. Therefore, physical collision avoidance is defined as the use of physical means to solve the problem of the multi-tag collision caused by non-software
factors. The front-end of the physical anti-collision system uses physical means to
collect data, for example, image sensors are used to collect the geometric characteristics of multi-label distribution, and the back-end uses neural network algorithms to
learn, train, and predict the physical optimal distribution structure, and then adjust
the label arrangement through physical means, angle, to achieve the overall optimal
recognition performance of the tag group.
This book is based on the basic principles of physics (including electromagnetics,
optics, thermodynamics, etc.), with engineering mathematical methods as the core of
detection and control algorithm design. Furthermore, this book innovatively applies
semi-physical verification and detection technology to the dynamic performance
testing of Radio-Frequency Identification (RFID) systems. This book proposes a
series of new theories and methods for physical collision prevention, as well as related
test verification methods for building semi-physical hardware platforms based on
photoelectric sensing technology, which will provide important theories and technical
v