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Shazmin Aniza Abdul Shukor
A study of embedded fuzzy logic to determine artificial stingless bee hive condition and honey volume
2024
,
Bukhari Ilias
,
Norasmadi Abdul Rahim
,
Shazmin Aniza Abdul Shukor
,
Abdul Hamid Adom
,
Muhammad Ammar Asyraf Che Ali
,
Mohd Al-Haffiz Saad
,
Mohd Fauzi Abu Hassan
Stingless Bee is particularly nutrient-dense in his honey. Therefore, numerous beekeepers for
the Stingless Bee have begun this agricultural enterprise, particularly in Malaysia. However,
beekeepers encounter challenges when caring for an excessively large stingless bee colony.
Due to the risk of causing colony disruption, the beekeeper cannot always access the hives
to monitor honey volume and hive condition. Consequently, the purpose of this paper is to
aid beekeepers and prevent disruption to bee colonies by determining the condition of the
hive and the quantity of honey using an embedded fuzzy logic system. Artificial hives have
been created in order to easily measure the weight of a hive of stingless bees and to divide
the honey compartment from the brood compartment in order to calculate the honey
volume. Since the stingless bee designs its colony with honey on top and larvae on the bottom,
honey volume can be determined by weighing the honey compartment using load cell and
internal humidity using dht22. DHT22 is used for measuring the internal temperature and
humidity, as previous papers have stated that the hive condition can be determined using
the internal temperature and humidity. Morever, FLDa (Fuzzy Logic Designer app) by
MATLAB was subsequently utilised to construct membership function, rules, fuzzification,
and defuzzification. Then, the same input, membership function, and rules that used in FLDa
will be implemented on the Nodemcu ESP8266 using eFLL (Embedded Fuzzy Logic Library).
A comparison between the crisp output from FLDa and the crisp output from eFLL was
conducted to determine whether eFLL is suitable for use in the NodeMCU ESP8266. As a
consequence, the standard deviationand averaged percentage error of differences for hive
condition, which is 0.22 and 0.17%, isless than the honey volume, which is 0.49 and 0.66%,
because hive condition has a strict correlation with temperature. The hive condition will be
rated bad (0% when the temperature is cold or hot state), but it will be rated good (100%
when the temperature is normal state). As for honey volume, the majority of results
correspond to the percentage of honey compartment weight, unless the humidity is dry state,
which will cause the value to be cut in half. Finally, the fuzzy logic system is effectively
implemented into an embedded system, making it easier for the beekeeper to monitor the
hive condition and honey volume without interfering with the activity of stingless bees.