expensive (in relation to the market price of the Physical Entity) to
measure the temperature of each orchid. Instead sensor(s) measuring
the air temperature are situated inside the cargo area. It is then assumed
that the air temperature equals that of the orchids. In other words, the
Physical Entity model also needs to include a sensing and/or an
actuating model; Information view: What physical quantities are monitored by the
sensors; how are the quantities related to each other, etc.? In the
recurring example the quantity that is handled by the system is the air
temperature in the cargo area of the truck.Second, in some use cases, the devices might be incorporated inside the
Physical Entity, which can have a range of implications for the IoT system. For
instance, if sensors are deployed inside a human body and the wireless sensor
signal is to be relayed to an outside reader, one needs to understand the in-
body propagation characteristics of said signal. Maybe the strong attenuation
caused by the body tissue calls for a scenario in which signal repeaters are
deployed. This has implications for the communication aspect of the
architecture ( functional view).
Third, the type of the Physical Entity – in combination with the application
scenario - can have implications for the Trust, Security, and Privacy Perspective
(see Section 4.3.3). Let us look again at the recurring example. Since orchids
can be very expensive, and since this can increase the likelihood of the truck
being raided while, for instance, parked during a coffee break or over night, it is
paramount that the wireless signal emanated by the orchid-monitoring system
cannot be identified as such nor be deciphered. The latter could, for instance,
inform the burglar about how many orchids are in the shipment.
Although the Physical Entity View is obviously very central to the IoT ARM, it is
not covered in the IoT Reference Architecture. This seeming contradiction is
attributed to the overwhelming range of Physical Entities in the IoT. They can
range from the nano- and micrometre scale (for instance, sugar molecules
detected by a diabetes sensor), to truly macroscopic dimensions (glacier
monitoring, etc. They can be gaseous or liquid. They can be animate or
inanimate or a mixture of both. They can be stationary or mobile. The latter can
include walking, running, moving on wheels, flying, coasting under water, flying
through interplanetary space, and so on. Also, there is nothing like ―the‖
physical quantity to be monitored. In one use case it can be the temperature of
orchids, in the other the occupancy of a room (automated light switch), in
another case blood-sugar levels. This overwhelming range of Physical Entities
does not provide for the generation of generic but yet comprehensive
viewpoints and thus models for the Physical-Entity View. This lack of ―least-
common-denominator‖ is the reason for why no Physical Entity models on the
reference-architecture level could be devised and thus integrated into the IoT
ARM.