A Study of Embedded Fuzzy Logic to Determine Artificial Stingless Bee Hive Condition and Honey Volume

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 deviation and averaged percentage error of differences for hive condition, which is 0.22 and 0.17%, is less 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.