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Dynamic are all the SCs that embed various rules allowing them to perform different actions according to these rules. Examples of such SCs are functions that monitor certain conditions and trigger according actions. This can happen i.e. when a SC is utilized to monitor the electricity consumption and temperature logged on the BC of an energy smart building. The SC includes thresholds for different heating and consumption measurements in order to adjust the temperature in an eco-friendly way, avoiding excessive electricity consumption and costs. The following pseudocode can be part of the smart contract’s definition showing the logic behind monitoring and execution
if room_temperature < 18 Celcius {
if electricity_consumption < 25 Watt
then turn_on air_condition
else send_message: "The dailydaily electricity consumption threshold has been reached. Would you like to turn on the A/C?"
if user_answer == ‘YES’ then
turn_on air_condition
else do_nothing
}
if room_temperature > 25 Celcius {
if electricity_consumption < 25 Watt
then turn_on heating_unit
else send_message: "The daily electricity
consumption threshold has been reached. Would you like to turn on the heating_unit?"
if user_answer == ‘YES’ then
turn_on heating_unit
else do_nothing
}
This SC although deterministic, follows a non-static conditioned flow, which shows how a dynamic SC might be formed and how it can act. The aforementioned code is very simplistic but computer functions can be long and very complex. Additionally it involves human interaction, which in certain occasions could hinder or cancel the dynamic action feature of SCs. In our perspective the human input is considered dynamic to the terms of non-standard, condition driven final action. There are also other occasions where the dynamic nature of SCs is controlled by machine-to-machine M2M actions. This M2M interactions can have unpredictable outcomes when the developer’s design and implementation of the SC is erroneous, incomplete, or non-deterministic.
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