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The Internet of Things (IoT) refers to the interconnection of various objects in our
daily life, including cars, refrigerators, cell phones, smart doors, patient monitoring devices,
and any other monitoring equipment. These devices are equipped with a smart
sensor, an actuator, and internet connectivity, allowing them to exchange, gather, and
send data to a remote server. IoT is a hybrid of various core forms of technology with
varying levels of communication. Many existing IoT systems rely on a number of protocols
and technologies. This causes complications with IoT connectivity and networking.
Our thesis focuses on LoRaWAN networks because of their flexibility, as well as the fact
that wireless communication takes advantage of the LoRa physical layer’s long-range
properties.
The different levels’ requirements necessitate varying levels of security. Researchers
strongly recommend deploying biometric security devices at levels where direct human
access is essential. Biometric security offer a scalable solution for IoT that combats unauthorized
access and credential swapping. Indeed, the biometric traits of human organs
serve as a unique identity for each individual since they are universal, permanent, distinct,
and work perfectly. This identification will be regarded as critical data to be transmitted
in the IoT network; as a result, packet loss should be minimal and packet delivery ratio
high. This data will be shared over the same medium, posing a significant collision risk
that must be addressed and avoided.
Collisions occur in wireless communication due to the large number of nodes sharing
the same channel. As a result, substantial amounts of data are lost. To avoid this
issue, Networks Communications employs the CSMA method for detecting channel occupancy
by measuring the carrier’s Received Signal Strength Indication (RSSI). However,
the known CSMA is inefficient in LoRa-based networks, such as LoRaWAN, which employs
the ALOHA protocol. Because the receiver can demodulate signals even below the
noise floors, LoRa wireless communication uses the Channel Activity Detection (CAD)
approach to avoid collisions.
This study makes a contribution by integrating a new LoRaWAN module into the NS3
simulator and introducing a novel CSMA method called FT-CSMA, which is based on the
well-known CSMA used in WIFI IEEE 802.11 and WSN IEEE 802.15.4.
In this work, we describe some interesting areas of IoT use while highlighting their
faults and limits. We then provide our proposal to alleviate one of these restrictions.
Finally, we present the IoT applications with biometric security methods that have been
developed the most by scientists. |
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