Industrial Quality Prediction System through Data Mining Algorithm
Volume-3 | Issue-2
Comparative Analysis an Early Fault Diagnosis Approaches in Rotating Machinery by Convolution Neural Network
Volume-3 | Issue-2
Nakagami-m Fading Detection with Eigen Value Spectrum Algorithms
Volume-3 | Issue-2
Abstractive Summarization System
Volume-3 | Issue-4
Design of Adaptive Estimator for Nonlinear control system in Noisy Domain
Volume-3 | Issue-3
Automated Nanopackaging using Cellulose Fibers Composition with Feasibility in SEM Environment
Volume-3 | Issue-2
Comparative Analysis of Temperature Measurement Methods based on Degree of Agreement
Volume-3 | Issue-3
Transistor Sizing using Hybrid Reinforcement Learning and Graph Convolution Neural Network Algorithm
Volume-3 | Issue-3
A Review on Meshing Techniques in Biomedicine
Volume-3 | Issue-4
EL DAPP - An Electricity Meter Tracking Decentralized Application
Volume-2 | Issue-1
SMART STREET SYSTEM WITH IOT BASED STREET LIGHT OPERATION AND PARKING APPLICATION
Volume-1 | Issue-1
ENERGY AND POWER EFFICIENT SYSTEM ON CHIP WITH NANOSHEET FET
Volume-1 | Issue-1
Abstractive Summarization System
Volume-3 | Issue-4
A Review on Meshing Techniques in Biomedicine
Volume-3 | Issue-4
MIMO BASED HIGH SPEED OPTICAL FIBER COMMUNICATION SYSTEM
Volume-1 | Issue-2
Industrial Quality Prediction System through Data Mining Algorithm
Volume-3 | Issue-2
Comparative Analysis of Temperature Measurement Methods based on Degree of Agreement
Volume-3 | Issue-3
Transistor Sizing using Hybrid Reinforcement Learning and Graph Convolution Neural Network Algorithm
Volume-3 | Issue-3
VIRTUAL REALITY SIMULATION AS THERAPY FOR POSTTRAUMATIC STRESS DISORDER (PTSD)
Volume-1 | Issue-1
Comparative Analysis an Early Fault Diagnosis Approaches in Rotating Machinery by Convolution Neural Network
Volume-3 | Issue-2
Volume - 2 | Issue - 1 | march 2020
Published
07 April, 2020
The waste water which are the outcomes of processing liquids cannot be used further without proper treatment so the water has to be treated and handled in order to elude the contamination that deteriorates the quality of the atmosphere. Although the biological methods can be utilized for treating the wastes in the water by decomposing the bacteria, it is biased by various causes such as the impurity level, the oxygen available, the dirt type etc. But the standard methodology like aeration utilizes the biological and the chemical oxygen demand reduction termed BO and CO respectively to treat the waste water, the conventional aeration process is performed manually causing enormous usage of electrical energy. So the paper elaborates the scheme of a fuzzy logic based aerator control system (FLACS) for the waste water. The essential equipment of the proposed system are the sensors providing the particulars of the chemical and the biological oxygen demand as input, the microcontroller (Arduino UNO) and other electrical and electronic equipment's that controls the working of the aerator. The analysis performed on the proffered model indicates the performance improvement of the FLACS in terms of the electrical energy utilization and duration of working hours.
KeywordsFLACS Arduino UNO Fuzzy Logic Aerator Control System Demand in Biological Oxygen and Chemical Oxygen
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