Guhan
@kce.ac.in
Associate Professor., Department of Information Technology
karpagam College of Engineering
EDUCATION
M.E.,Ph.D
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Engineering, Computer Science Applications, Artificial Intelligence, Computer Graphics and Computer-Aided Design
Scopus Publications
Scopus Publications
S. Vidya, Veeraraghavan Jagannathan, T. Guhan, and Jogendra Kumar
IOS Press
Rainfall forecasting is essential because heavy and irregular rainfall creates many impacts like destruction of crops and farms. Here, the occurrence of rainfall is highly related to atmospheric parameters. Thus, a better forecasting model is essential for an early warning that can minimize risks and manage the agricultural farms in a better way. In this manuscript, Deep Neural Network (DNN) optimized with Flamingo Search Optimization Algorithm (FSOA) is proposed for Long-term and Short-term Rainfall forecasting. Here, the rainfall data is obtained from the standard dataset as Sudheerachary India Rainfall Analysis (IRA). Moreover, the Morphological filtering and Extended Empirical wavelet transformation (MFEEWT) approach is utilized for pre-processing process. Also, the deep neural network is utilized for performing rainfall prediction and classification. Additionally, the parameters of the DNN model is optimizing by Flamingo Search Optimization Algorithm. Finally, the proposed MFEEWT-DNN- FSOA approach has effectively predict the rainfall in different locations around India. The proposed model is implemented in Python tool and the performance metrics are calculated. The proposed MFEEWT-DNN- FSOA approach has achieved 25%, 26%, 25.5% high accuracy and 35.8%, 24.7%, 15.9% lower error rate for forecasting rainfall in Cannur at Kerala than the existing Map-Reduce based Exponential Smoothing Technology for rainfall prediction (MR-EST-RP), modular artificial neural networks with support vector regression for rainfall prediction (MANN-SVR-RP), and biogeography-based extreme learning machine (BBO-ELM) (BBO-ELM-RP) methods respectively.
B. Uma Maheswari, T. Guhan, Christopher Francis Britto, Adlin Sheeba, M. P. Rajakumar, and Kumar Pratyush
AIP Publishing
N. Senthilkumar, N. Revathy, and T. Guhan
IEEE
Many paths between the source and sink nodes may be detected using multi-path routing in WSNs. The reliability, energy efficiency, and other benefits of data transmission may be increased by using many channels. The topic of multi-path routing has been the subject of several academic studies. These multi-path routing protocols, however, are ineffective because of the time and energy needed to build several channels. The elimination of bottlenecks and delays in data transmission is made possible by multipath routing in WSNs. Network QoS (Quality of Service), load balancing, and communication dependability may all benefit from multipath routing systems. To identify multipath routing in WSN, we suggested the Enhanced Geographic multipath (EGMPIP) architecture. The proposed framework first constructs the base station routing algorithm by computing the Neighbor node discovery (NND) function in the network using the G-ND. Each node in the network may make use of multipath routing thanks to the network-wide routing mechanism. In the end, simulation data are shown to validate the suggested technique, and the findings demonstrate that the routing strategy described in this work is superior to past methods.
N. Revathy, T. Guhan, S. Nandhini, S. Ramadevi, and R. Dhipthi
IEEE
In India, agriculture is that the first offer of income. It’ an enormous impact on the country’ economy. However, agriculture is being hampered latterly as a results of parents migrating from rural to urban areas. Looking environmental factors isn't a full strategy for increasing agricultural productivity. There are sort of parts that have a major impact on productivity. Hence to handle these issues, agriculture ought to utilize automation. A farmer can save time, money, and energy by victimization an autonomous watering system. Ancient farmland irrigation ways necessitate human intervention. Human intervention is reduced with irrigation instrumentality that's automated. Continuous sensing and looking of crops through the convergence of sensors and thus the web of Things (IoT), allowing farmers to recollect of crop growth and harvest on a daily basis, resulting in high agricultural yield and correct product delivery to end users.
A. Uma Maheswari, N. Revathy, T. Guhan, B. Praveen, and R. Magesh Kumar
IEEE
Concept drift is a problem where context behind the word changes in different times as different. This happens ahead of the minimum stability period. Many applications are there in which the problem of the concept drift needs to be addressed, including online shopping preferences and review of the consumer, spam detection, climate change predictions and social stream data. In E-Commerce applications the concept drift plays a vital role in deciding the review and sentiment analysis. This research focus on the concept drift which impacts the sentiment mining. This research will provide a novel algorithm based on the deep learning recurrent neural network variant.
K. Anuradha, R. Prema, N. Revathy, T. Guhan, and K. P. Uma
IEEE
From the last decade, robot development has become a major ingredient for scientists and researchers. Due to the latest advancements in the computing and nanotechnologies field, robotics has gained popularity all over the world. To secure living beings and to minimize the hard work taken by the fireman, we proposed a robot model. The aim of the robot model is to automate the fire rescue operations. This model can be used to save the life of humans, minimize damages in household, laboratories and small scale industries. The robot is constructed to follow a predefined path to perform various tasks. With the developmental improvement in the robotic field, intervention of humans has turn into less and they are widely used for secure purpose. In our day by day life, accidents caused by fire have become common and may rather cause life challenging situations which make it tough for the firemen to guard individual life. In such cases, a robot is employed to guard living beings, property and environment from the fire incidents. The sensors are used in Robot for sensing the fire and the information about fire is sent to the microcontroller. Then the microcontroller pass the signal to the control circuitry for moving the robot in that particular fire zone for extinguishing the fire by using water pump or extinguisher. This technology is more secure because it reduces the human efforts and risks.
T. Guhan, N. Revathy, K. Anuradha, and B. Sathyabama
Springer Singapore