81
The students were advised to stop and restart manually the application in the device
programming tab, as shown in the below figure, every time the Cisco Packet Tracer was
launched the first time.
Figure 62 - Example of custom Phyton program running
on RFID reader device
Another limitation observed during the course, not related to Cisco Packet Tracer but
more on the structure of the classes, was related the limited amount time reserved for
the IoT practical part in the study course.
Being the first time this course had been taught, and the fact that the structure of the
classes had been decided before a deeper analysis of Cisco Packet Tracer complexity
was completed, it resulted in underestimating the time necessary to be reserved for the
practical classes.
82
Other smaller limitations came from the fact that all students should have created their
own Cisco NetAcad account beforehand and also have the Cisco Packet Tracer installed
in their own laptop.
As mentioned earlier, despite the limitations caused by the tool or the time, the simula-
tions had been built beforehand allowing students, with different skillset, to adapt their
own IoT business case
or even further expand them, both on network and IoT level.
As previously listed in the chapter 4.3 future expansion of the simulations are possible.
Regarding the network area students could, in the two Smart-home cases, upgrade the
VPN connectivity in order to be able to remotely access the home LAN when connecting
from an external network. Another example is to add a firewall in order to limit the access
to the IoT network from the remote office LAN in the Smart-industrial case. In Smart-
Campus the IoT network could be re-organized by using a cellular infrastructure.
IoT smart-devices expansion should be also very simple for the student, purpose would
be to add more devices within the IoT network and create more intelligent rules via the
IoT backend server. In some of the case this would require also that IoT network would
be expanded in order to be capable in running more devices.
Last and more technical expansion could be the usage of microcontroller.
Multi-Chip
Units (MCU) or Single-Board Computer (SBC) can be widely used in the simulations in
order to fully control the IoT device functions. IoT server backend intelligence, program-
able via browser, it is only possible for smart-devices and only allows simple IF-THEN-
ELSE rules. Programming of microcontroller instead offers full visibility on sensor param-
eters, actuator functions, data logging and also allows to use a wider range of IoT de-
vices.
Microcontrollers should also be connected to the local IoT network.
Students with stronger programming skills, were encouraged
not only to program
MCU/SBC board but also modify or create the pre-set program of the sensor and actua-
tors, giving full freedom and control of the IoT device.
