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A smart greenhouse is a scheme with the aim of allowing the plant growth optimally due to the control in temperature, soil moisture, and humidity. It is necessary to go for best possible smart greenhouse controlling system to maneuver the parameters in accordance with the climatic and seasonal changes plant. In this proposed work, the appropriate setting, monitoring of the model parameters like optimal temperature, humidity, and soil moisture in the greenhouse farm available at Modakkurichi near Erode is carried out using fuzzy logic and multiclass Support Vector Machine (SVM) techniques. It is efficiently implemented as the fuzzy trapezoidal membership function for each sample within the hyper-sphere as a linear function of the selected sample’s distance in the non-linear SVM hyperplane. Based on the simulation and experimental results, the fuzzy logic with Multi-class Support Vector Machine method is effective in selection of the rules to make decision. Simulation of the work was carried out in Python using the open source tool COLAB. Statistical parameters are evaluated for the proposed Fuzzy based SVM method. Root Mean Square Error of the proposed controller has the minimum value as 0.962E-02 when compared to other controllers which vary from 1.04 E-02 to 8.27 E-02.

Convolutional codes are comprehensively used as Forward Error Correction (FEC) codes in digital communication systems. For decoding of convolutional codes at the receiver end, Viterbi decoder is often used to have high priority. This decoder meets the demand of high speed and low power. At present, the design of a competent system in Very Large Scale Integration (VLSI) technology requires these VLSI parameters to be finely defined. The proposed asynchronous method focuses on reducing the power consumption of Viterbi decoder for various constraint lengths using asynchronous modules. The asynchronous designs are based on commonly used Quasi Delay Insensitive (QDI) templates, namely, Precharge Half Buffer (PCHB) and Weak Conditioned Half Buffer (WCHB). The functionality of the proposed asynchronous design is simulated and verified using Tanner Spice (TSPICE) in 0.25 µm, 65 nm, and 180 nm technologies of Taiwan Semiconductor Manufacture Company (TSMC). The simulation result illustrates that the asynchronous design techniques have 25.21% of power reduction compared to synchronous design and work at a speed of 475 MHz.