A5107972209- COVID-19 diagnosis using AI
- Artificial Intelligence in Healthcare
- Digital Imaging for Blood Diseases
- AI in cancer detection
- Anomaly Detection Techniques and Applications
- Advanced Neural Network Applications
- Smart Agriculture and AI
- Energy Load and Power Forecasting
- IoT and Edge/Fog Computing
- Blockchain Technology Applications and Security
- Optical Network Technologies
- Advanced Photonic Communication Systems
- Sentiment Analysis and Opinion Mining
- PAPR reduction in OFDM
- Vehicular Ad Hoc Networks (VANETs)
- Stock Market Forecasting Methods
- Brain Tumor Detection and Classification
- IPv6, Mobility, Handover, Networks, Security
- Machine Learning in Healthcare
- Neural Networks and Applications
- Energy Efficient Wireless Sensor Networks
- Imbalanced Data Classification Techniques
- Advanced Image and Video Retrieval Techniques
- Optical Wireless Communication Technologies
- Smart Grid Energy Management
SRM Institute of Science and Technology
2023-2025
Sri Eshwar College of Engineering
2024
Intel (India)
2022-2024
Hankuk University of Foreign Studies
2023
Nanjing University of Information Science and Technology
2023
Edinburgh Napier University
2023
Veer Surendra Sai University of Technology
2022
Maharaja Sriram Chandra Bhanja Deo University
2022
University of Teramo
2022
Jeppiaar Engineering College
2021
Abstract Healthcare practices include collecting all kinds of patient data which would help the doctor correctly diagnose health condition patient. These could be simple symptoms observed by subject, initial diagnosis a physician or detailed test result from laboratory. Thus, these are only utilized for analysis who then ascertains disease using his/her personal medical expertise. The artificial intelligence has been used with Naive Bayes classification and random forest algorithm to...
Banana cultivation is one of the main agricultural elements in India, while common problem that crop has been influenced by several diseases, pest indications have needed for discovering infections initially avoiding financial loss to farmers. This will affect entire banana productivity and directly affects economy country. A hybrid convolution neural network (CNN) enabled disease detection, classification proposed overcome these issues guide farmers through enabling fertilizers be utilized...
To improve text input for motor-disabled people, this research uses the Internet of Things (IoT) and machine learning. Swipe-to-Type, a popular touch-based technique, is study's focus. User swipe motions contextual data are collected in real-time using IoT devices. A learning framework trains algorithm to adapt disabled users' motor skills preferences. Addressing impairment problems, suggested method improves efficiency personalization. The Swipe-to-Type constantly adjusted based on learned...
With the prevalence of Aerospace Technologies, regulations cybersecurity are becoming smarter, assured, and long-lasting. Modern communication network technologies have enormous growth in cyber threats masquerading attacks to steal data. Hence concepts mechanisms built made into for a safer environment. Unmanned aerial vehicles (UAVs), often known as drones, increasingly common, posing new problems areas such monitoring, agriculture, weather prediction, surveillance other fields. This...
In this paper, an advanced and optimized Light Gradient Boosting Machine (LGBM) technique is proposed to identify the intrusive activities in Internet of Things (IoT) network. The followings are major contributions: i) An LGBM model has been developed for identification malicious IoT network; ii) efficient evolutionary optimization approach adopted finding optimal set hyper-parameters projected problem. Here, a Genetic Algorithm (GA) with k-way tournament selection uniform crossover...
This research study proposes an innovative method for enabling real-time monitoring of soil health and nutrient status in agricultural areas by integrating Internet Things (loT) Geographic Information Systems (GIS) technologies. The conventional approach to is more difficult challenging; it provides the most current data required making smart decisions. proposed makes use loT devices configured with a wide range sensors continuously monitor essential qualities including moisture, pH,...
Satellite images have a very high resolution, which make their automatic processing computationally costly, and they suffer from artifacts making difficult. This paper describes method for the effective semantic segmentation of satellite images, compares different object classifiers in terms accuracy execution time. In paper, image spectrum is used to reduce computational cost during classification steps. Firstly, are corrected facilitating feature extraction process. After this,...
The evolution of Internet-of-Vehicles (IoV) from IoT has revolutionized Smart cities, enabling vehicle communication for safety and traffic information dissemination. However, fulfilling time-sensitive applications like alerts via Cellular Vehicle-to-Everything (C-V2X) faces resource constraints. This study presents a Non-Orthogonal Multiple Access (NOMA) based allocation C-V2X in Ultra-dense networks (UDN). paper also discussed the role TinyML unmanned aerial (UAV) it is demonstrated with...
Abstract This article outlines an integrated strategy that combines fuzzy multi‐objective programming and a multi‐criteria decision‐making framework to achieve number of transportation system management‐related objectives. To rank fleet cars using various criteria enhancement, the Fuzzy technique for order preference by resemblance optimum solution are initially integrated. We then offer novel Multi‐Objective Possibilistic Linear Programming (MOPLP) model, based on rankings vehicles,...