Smart Agriculture: Deep Learning-Powered Disease Recognition in Mango and Banana Leaves Surekha Bijapur, Janapati Venkata Krishna, Sheela N S, DR. Meghana G R, Dr. Chetan H R International Journal of Drug Delivery Technology, 2026 Mango and banana are major commercial crops with worldwide importance, providing nutritional and economic sustainability. But leaf diseases pose a threat to their growth and productivity. Effective disease management is necessary to avoid losses. In this research, we present an automated system for identifying and classifying banana and mango leaves infected by diseases using a Deep Learning (DL) approach. The proposed method utilizes a CNN that has been trained on a large and diverse dataset of leaf images representing different stages of various diseases at different resolutions. The proposed method is expected to provide accurate identification between different common diseases such as Bacterial Canker, Powdery Mildew, Anthracnose, Gall Midge, and Sooty Mould. By leveraging learned visual features, the proposed system provides a valuable tool for early detection and effective pest control measures in commercial farming. Beside proposing apesticideto control the diseases observed in both bananas and mangoes, the proposed work utilizes a hybrid feature extraction technique, image segmentation, and classification algorithms to improve the efficiency of the disease identification process. With an accuracy of 95.5% for banana and 96.0% for mango leaf disease identification, the proposed hybrid model proved its applicability for real-time agricultural applications.
Optimized Load Sharing in Residential Energy Systems Using Simulated Annealing: A Comparative Study Nandish B M, Santhosha B M, Geetha V, Nagaraja Bodravara, Chandan K R, Chetan H R International Conference on Electrical Energy Systems Icees, 2025 This study presents an optimization-based approach for efficient electrical load sharing among three houses, with one house utilizing a 10-kW solar power system. The optimization framework considers time-of-use pricing, solar generation variations, and grid constraints, ensuring cost-effective energy utilization. Various performance metrics, such as cost of operation over a month, solar power utilization, convergence trends, computational time, and peak-to-average ratio (PAR), are analyzed. The proposed model optimizes power consumption using Simulated Annealing (SA) and compares its performance with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC). The optimization framework considers time-of-use (TOU) pricing, solar generation variations, and grid constraints, ensuring cost-effective energy utilization. The results demonstrate that SA achieves a 22-30% reduction in operational costs compared to non-optimized consumption, with GA, PSO, and ABC achieving 18%, 20%, and 24% reductions, respectively. SA also maximizes solar power utilization by 85%, compared to 78% for GA, 80% for PSO, and 83% for ABC. The peak-to-average ratio (PAR) is reduced significantly with SA, enhancing grid stability, and reducing peak-hour dependency. Overall, the findings demonstrate that Simulated Annealing is a superior optimization technique for energy-efficient load sharing. It effectively reduces costs, improves solar energy utilization, minimizes peak demand, and enhances grid stability. The proposed approach can be further extended for larger energy distribution networks, smart grids, and renewable-integrated power systems.
Design and Implementation of IoT Based Smart Energy Meter for Energy Management of Residential loads Nagaraja Bodravara, Chandan K R, Vidyashankar M, Chetan H R, Guruprashanth N, Nandish B M International Conference on Electrical Energy Systems Icees, 2025 An energy meter is utilized to quantify the energy consumption of residential, commercial, and industrial users. The smart energy meter facilitates the energy management system as the population of energy consumers continues to grow. The study illustrates a proposed method aimed at mitigating human intervention in energy management for both residential and industrial settings. The monitoring of data is conducted exclusively through a web-based portal that is equipped with a dedicated internet connection. The system must be designed to ensure accurate analysis of power use. At present, the technology employed necessitates human intervention, resulting in time consumption. It has long been a requirement for a designated individual or representative from the energy department to personally visit the consumer’s residence and record the readings, so introducing the potential for inaccuracies. In order to mitigate stress, the implementation of a smart energy meter is proposed. This study employs a microcontroller equipped with an integrated WIFI capability due to its energy efficiency, resulting in reduced power consumption.
Smart Electricity Monitoring, Management and Control for Household Appliances Using Real-Time IoT Sensors B M Nandish, Nagaraja Bodravara, H R Chetan, N Guruprashanth, D Suhas, B M Santosha Cosmic 2024 IEEE International Conference on Computing Semiconductor Mechatronics Intelligent Systems and Communications Proceedings, 2024 The Internet of Things (IoTs) refers to the interconnection of commonplace objects such as smartphones, Internet TVs, sensors, and actuators with the Internet. This interconnection facilitates intelligent communication between objects and individuals, as well as among objects themselves. This project entails the design and implementation of an intelligent monitoring and control system for residential electrical appliances, operating in real-time. The primary function of the system is to monitor the electrical parameters of household appliances, specifically voltage and current, and later do calculations to determine the power consumption. The uniqueness of this system lies in its application of several methods for controlling appliances. The system that has been designed has characteristics of being cost-effective and adaptable, thereby enabling users to reduce their electricity expenses. Our objective is to identify the specific time periods when power usage reaches its highest levels and propose a solution to reduce consumption and optimize the utilization of limited resources during these peak hours.
Plant leaf disease detection using hybrid feature extraction techniques H. R. Chetan, G. S. Rajanna, G. Nandini, K. C. Santosh, B. H. Puneeth, K. S. Gururaj, B. R. Sreenivasa, M. S. Abdul Razak Archives of Phytopathology and Plant Protection, 2024 Excessive yield losses are due to delayed identification of leaf diseases, resulting in lower farmer revenue. To address this, early and precise detection methods are crucial. Sunflower, a vital commercial crop in India for edible oil production, faces issues like leaf blight, downy mildew, powdery mildew, and leaf spot. Our research aims to create an algorithm that effectively identifies these diseases using hybrid feature extraction techniques. We compiled sunflower leaf images from village databases and farm visits. Initially, color images were converted to grayscale, and the noise was reduced using Gaussian filtering during image pre-processing. Disease-affected areas were segmented using edge-based approaches. Hybrid feature extraction was then employed to encompass color and texture-related attributes. The K-Nearest Neighbors (KNN) algorithm facilitated disease classification. The proposed algorithm’s performance was benchmarked against SVM, RF and DT classifiers. Remarkably, our algorithm achieved exceptional accuracy: 98% for leaf blight, 97.3% for downy mildew, 95% for powdery mildew, and 96.5% for leaf spot detection. These results underscore the algorithm’s effectiveness in combating plant diseases and enhancing agricultural productivity.
MORDEX: A Real Time Responsive Humanoid T Rashmi, Anushka Jemima, C Raghavendran, H Chetan 2022 2nd International Conference on Computer Science Engineering and Applications Iccsea 2022, 2022 Speech is an easy-to-understand communication medium that also acts as an interface for processes in artificial intelligence. In this paper, we provide a brief introduction to the humanoid that we have developed. Our humanoid is based on voice recognition principles. Voice commands are given to the humanoid as a set of instructions. The Raspberry Pi 4 microcontroller plays a significant role in collecting samples as Pulse width modulation (PWM). The signals are then transferred to the raspberry pi via a USB module. Raspberry pi-4 functions as the brain of the robot and converts the signals into a set of commands that the robot will then execute. A Servo Motor (MG90) is used to control the humanoid’s movement. We measure the success of the robot based on the accuracy of speech recognition using Google speech API and have provided the results through this paper.
An Efficient 32-bit Ladner Fischer Adder derived using Han-Carlson Kavitha A, Chetan H Gowda 2021 IEEE International Conference on Mobile Networks and Wireless Communications Icmnwc 2021, 2021 Parallel-prefix adders propose an extremely efficient solution to the binary addition problem. Adders are building block in digital circuit that performs addition of two numbers. In VLSI design, a parallel- prefix adder is a kind of adder that performs efficient addition by using the prefix operation. In this Research, a 32 bit Ladner-Fischer parallel prefix adder, a category of a parallel prefix adder that executes addition operations in parallel. Nevertheless, through the use of a black cell, the performance of the Ladner Fischer adder took a large amount of space. As a result, the gray cell has been used instead of the black cell, resulting in the Ladner-Fischer Adder Efficiency. Earlier Ripple carry adder waited for previous bit for every bit addition which was overcome by Ladner Fischer adder. The proposed system introduced D register stage which increases the performance with reduce in delay to 7.165ns and LUT count is 82.
Mitigating HTTP GET FLOOD DDoS attack using an SDN controller R Sanjeetha, K.N Ajay Shastry, H.R Chetan, Anita Kanavalli Proceedings 5th IEEE International Conference on Recent Trends in Electronics Information and Communication Technology Rteict 2020, 2020
Arduino based smart and intelligent helmet system for two-wheelers Mahesh S Gour, Druva Kumar S, Pradeep Kumara, Manjunatha S, Sunil Kumar K, Chetan H 2020 IEEE International Conference on Distributed Computing VLSI Electrical Circuits and Robotics Discover 2020 Proceedings, 2020
SOFT ROBOTICS: A Bio-Inspired Revolution Anushka Jemima, C Raghavendran, Chetan H Proceedings of B Htc 2020 1st IEEE Bangalore Humanitarian Technology Conference, 2020
Design and modeling of a nanomechanical pressure sensor using silicon photonic crystal Journal of Advanced Research in Dynamical and Control Systems, 2019
Detection of harmful bacteria in water using phc sensors and analysis of the quality factor Journal of Advanced Research in Dynamical and Control Systems, 2019
Low Power Architecture for 17X17 Parallel Multiplier using Reversible Logic Gates in 65nm Technology 11th Indiacom 4th International Conference on Computing for Sustainable Global Development Indiacom 2017, 2017
Low power VLSI implementation of data compression for multimedia devices using CDF m/n DWT on to resource constrained dynamically reconfigurable memories Proceedings of the 10th Indiacom 2016 3rd International Conference on Computing for Sustainable Global Development Indiacom 2016, 2016
RECENT SCHOLAR PUBLICATIONS
MORDEX: A Real Time Responsive Humanoid T Rashmi, A Jemima, C Raghavendran, H Chetan 2022 Second International Conference on Computer Science, Engineering and … , 2022 2022
A survey paper on evolution of VANET towards IOV R Bindu, M Preethi Sejal, H Chetan International Conference on Optical and Wireless Technologies, 99-113 , 2021 2021 Citations: 6
Relative study between technology to perceive hand gestures H Chetan, S Praveen, S Shreyas, S Singh, R Urvi ICT Analysis and Applications: Proceedings of ICT4SD 2020, Volume 2, 621-628 , 2020 2020 Citations: 1
Advanced Signal Processing for Ground-Penetrating Radar M Nagesha, H Chetan, P Borannavar ICT Analysis and Applications: Proceedings of ICT4SD 2020, Volume 2, 535-546 , 2020 2020
Performance dependency of facial emotion recognition system on dropout and learning rate H Chetan 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS … , 2020 2020 Citations: 3
Arduino based smart and intelligent helmet system for two-wheelers MS Gour, P Kumara, S Kumar 2020 IEEE International Conference on Distributed Computing, VLSI … , 2020 2020 Citations: 21
Soft robotics: A bio-inspired revolution A Jemima, C Raghavendran 2020 IEEE Bangalore Humanitarian Technology Conference (B-HTC), 1-6 , 2020 2020 Citations: 9
Diagnostic Study of Lung Cancer using Photonics T Rashmi, S Geethanjali, H Chetan 2020 IEEE Bangalore Humanitarian Technology Conference (B-HTC), 1-6 , 2020 2020
A novel image compression approach using DTCWT and RNN encoder SK KH, H Chetan, G Indumathi 2020 IEEE Bangalore Humanitarian Technology Conference (B-HTC), 1-4 , 2020 2020 Citations: 1
Detection of melanoma cancer cell by designing a SPR based biosensor N Chandra Shekar, BS Rakshitha, N Mamatha, H Chetan, MR Jyoti, ... Journal of Physics: Conference Series 1362 (1), 012011 , 2019 2019 Citations: 7
Design and Performance Analysis of Differential Amplifier for Various Applications MR Jyoti, H Chetan Journal of Computational and Theoretical Nanoscience 15 (11-12), 3501-3508 , 2018 2018 Citations: 1
Performance Analysis of Modified Architecture of DA-DWT and Lifting based Scheme DWT for Image Compression. H Chetan, G Indumathi International Journal of Multimedia and Ubiquitous Engineering 12 (7), 31-42 , 2017 2017
Notice of Violation of IEEE Publication Principles: Low power VLSI implementation of data compression for multimedia devices using CDF m/n DWT on to resource constrained … H Chetan, G Indumathi 2016 3rd International Conference on Computing for Sustainable Global … , 2016 2016
Low Power VLSI Implementation of Data Compression for Multimedia Devices using CDF m/n DWT on to Resource Constrained Dynamically Reconfigurable Memories DIG CHETAN H INDIACom-2016; IEEE Conference 10 (3rd International Conference), 3752-3757 , 2016 2016
Low Power Implementation of Wireless Telecommand and Telemetry System based on IEEE 802.15 H Naveen, H Chetan International Journal of Advances in Applied Science and Engineering (IJAEAS … , 2014 2014 Citations: 1
MOST CITED SCHOLAR PUBLICATIONS
Arduino based smart and intelligent helmet system for two-wheelers MS Gour, P Kumara, S Kumar 2020 IEEE International Conference on Distributed Computing, VLSI … , 2020 2020 Citations: 21
Soft robotics: A bio-inspired revolution A Jemima, C Raghavendran 2020 IEEE Bangalore Humanitarian Technology Conference (B-HTC), 1-6 , 2020 2020 Citations: 9
Detection of melanoma cancer cell by designing a SPR based biosensor N Chandra Shekar, BS Rakshitha, N Mamatha, H Chetan, MR Jyoti, ... Journal of Physics: Conference Series 1362 (1), 012011 , 2019 2019 Citations: 7
A survey paper on evolution of VANET towards IOV R Bindu, M Preethi Sejal, H Chetan International Conference on Optical and Wireless Technologies, 99-113 , 2021 2021 Citations: 6
Performance dependency of facial emotion recognition system on dropout and learning rate H Chetan 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS … , 2020 2020 Citations: 3
Relative study between technology to perceive hand gestures H Chetan, S Praveen, S Shreyas, S Singh, R Urvi ICT Analysis and Applications: Proceedings of ICT4SD 2020, Volume 2, 621-628 , 2020 2020 Citations: 1
A novel image compression approach using DTCWT and RNN encoder SK KH, H Chetan, G Indumathi 2020 IEEE Bangalore Humanitarian Technology Conference (B-HTC), 1-4 , 2020 2020 Citations: 1
Design and Performance Analysis of Differential Amplifier for Various Applications MR Jyoti, H Chetan Journal of Computational and Theoretical Nanoscience 15 (11-12), 3501-3508 , 2018 2018 Citations: 1
Low Power Implementation of Wireless Telecommand and Telemetry System based on IEEE 802.15 H Naveen, H Chetan International Journal of Advances in Applied Science and Engineering (IJAEAS … , 2014 2014 Citations: 1
MORDEX: A Real Time Responsive Humanoid T Rashmi, A Jemima, C Raghavendran, H Chetan 2022 Second International Conference on Computer Science, Engineering and … , 2022 2022
Advanced Signal Processing for Ground-Penetrating Radar M Nagesha, H Chetan, P Borannavar ICT Analysis and Applications: Proceedings of ICT4SD 2020, Volume 2, 535-546 , 2020 2020
Diagnostic Study of Lung Cancer using Photonics T Rashmi, S Geethanjali, H Chetan 2020 IEEE Bangalore Humanitarian Technology Conference (B-HTC), 1-6 , 2020 2020
Performance Analysis of Modified Architecture of DA-DWT and Lifting based Scheme DWT for Image Compression. H Chetan, G Indumathi International Journal of Multimedia and Ubiquitous Engineering 12 (7), 31-42 , 2017 2017
Notice of Violation of IEEE Publication Principles: Low power VLSI implementation of data compression for multimedia devices using CDF m/n DWT on to resource constrained … H Chetan, G Indumathi 2016 3rd International Conference on Computing for Sustainable Global … , 2016 2016
Low Power VLSI Implementation of Data Compression for Multimedia Devices using CDF m/n DWT on to Resource Constrained Dynamically Reconfigurable Memories DIG CHETAN H INDIACom-2016; IEEE Conference 10 (3rd International Conference), 3752-3757 , 2016 2016
