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Journal of Recent Innovations in Computer Science and Technology

JRICST ISSN: 3050-7030 India

Published by Academics Achievers Education And Research Foundation

Journal Profile

Journal Information

Bibliographic and publication information recorded by BIBNEX.

Print ISSN
3050-7022
Online ISSN
3050-7030
Publisher
Academics Achievers Education And Research Foundation
Publication Frequency
Quarterly
Subject / Stream
artificial intelligence, machine learning, data science, big data analytics, cybersecurity, blockchain, Internet of Things (IoT)
Country
India
Language
English
DOI Prefix
10.70454
Open Access
No
BIBNEX Status
Active
43 Articles
43 Indexed Records
0 DOI Records
Active Indexing Status

Articles Indexed from This Journal

Browse scholarly records indexed in BIBNEX from Journal of Recent Innovations in Computer Science and Technology.

43 Articles
Info:eu Repo/semantics/article

IoT Based Weather Monitoring System for Tourists

0 citations
DOI 10.70454/jricst.2025.20106

The rapid expansion of tourism has necessitated the provision of weather information to guarantee the safety, convenience, and improved travel experiences of travelers. An innovative solution is provided by an IoT-based weather monitoring system, which provides precise, current meteorological data that is specifically designed for visitors. The IoT has greatly impacted and improved many aspects of our daily lives and...

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Info:eu Repo/semantics/article

Potato Leaf Disease Detection Method is based on a CNN model with a Genetic Algorithm

0 citations
DOI 10.70454/jricst.2025.20107

This paper puts forward an approach that combines Convolutional Neural Networks (CNNs) and Genetic Algorithm (GA) to detect accurately and quickly the diseases that affect potato leaves swiftly and accurately. The model of the CNN is employed for automated feature extraction from the images of leaves which are pivotal in differentiating between the healthy and the infected leaves. Optimization of CNN hyper parameters...

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Info:eu Repo/semantics/article

Attack and Anomaly Detection in IoT Sensors Using Machine Learning Approaches

0 citations
DOI 10.70454/jricst.2025.20108

The extensive usage of IoT sensors significantly improved the collection and monitoring of data within various application domains, such as smart agriculture and industrial automation. On the other hand, the great dependence on IoT sensors makes systems vulnerable to hacks and anomalies. In this paper, we explore machine learning approaches that can be used to protect Internet of Things sensor networks against attack...

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