Implementation of Fuzzy Logic Control in Predictive Analysis and Real Time Monitoring of Optimum Crop Cultivation : Fuzzy Logic Control In Optimum Crop Cultivation

Roy, Shrestha; Dey, Debolina; Saha, Medha; Chatterjee, Kalyan; Banerjee, Sayanti

doi:10.1109/confluence47617.2020.9057927

Cited by 1 publication

(1 citation statement)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This study uses the Mamdani fuzzy method, and the following steps are carried out for research: a) Carry out secondary data collection activities needed in calculations and analysis. b) Determine the range and membership function of each attribute c) Determination of the consequent function for each implication rule d) Forming fuzzy implication rules by combining each linguistic attribute on each input variable e) Perform defuzzification by calculating the weighted average of all fuzzy implication rules [18,19,38,40] f) Affirmation (defuzzy) is the process of confirmation (defuzzification) using the help of software Matlab R2017a using the facilities provided in the fuzzy toolbox.…”

Section: Methodsmentioning

confidence: 99%

Prototype of Water Turbidity Measurement With Fuzzy Method using Microcontroller

Siregar¹,

Sinaga²,

Hanafiah³

2022

IOTA

View full text Add to dashboard Cite

Water is a source of much-needed living things such as daily needs and transportation routes, and also as a source of energy. Water is also essential as a water quality factor. Good water for treating cold-water ornamental fish with temperatures below 20o Celcius has a maximum water turbidity value of 10 NTU (Nephelometric Turbidity Unit); if the turbidity level is above 10 NTU, the water will be declared cloudy and affect fish health. The object of this research is ornamental aquarium fish with the type of goldfish. The research method used is qualitative. The research flow begins with observing the problem, then designing and simulating the Arduino Uno as a place to process the measuring data. The prototype of this tool aims to show changes in the level of turbidity of water from the value of water turbidity. This prototype uses the fuzzy method to assist the testing process. This study's results for five days showed that 1 out of 5 tests indicated that the aquarium water was cloudy, namely on the fifth day. The results of this study are expected to be implemented in a prototype for measuring water turbidity using the fuzzy method using a microcontroller. The design of this water turbidity measuring instrument is expected to estimate the turbidity of water or liquid correctly, precisely, accurately, with a small error rate, and notify warnings for replacing ornamental fish aquarium water.

show abstract

Section: Methodsmentioning

confidence: 99%