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Indigenous IoT and Software Framework for Implementing Digital Twin Over Indian Region Towards Sustainable Development 1

Indigenous IoT and Software Framework for Implementing Digit...

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1st international conference on computing, Sciences and Communications, ICCSC 2024

作者： Agarwal, Nikunj Singla, JaiG. Dhaka, Vijaypal Singh School of Computing and Intelligent Systems Manipal University Jaipur Rajasthan Jaipur India Space Applications Centre ISRO Signal and Image Processing Area Gujarat Ahmedabad India

ISBN: (纸本)9798350353648

Digital Twin is a digital replication of physical things. This technology has been in works for over a decade, and has been implemented in various regions. This study shows the integration of internet of Things(IoT) with the Digital Twin technology seamlessly within the Indian ecosystem to lead towards sustainable development. The Digital Twin model utilizes the data collected through an indigenous IoT solution equipped with LoRa technology and Node MCU. However, with the diverse geographic properties of the Indian subcontinent, it poses a significant challenge to collect comprehensive data of the entirety of the region. This paper presents an approach to develop an indigenous and integrated solution to simplify the complexities of integrating data from the sensors spread across the region into one simple framework. This paper further present show this Digital Twin model can play a huge role in showcasing data received from indigenous IoT devices to nroduce more accurate and actionable insishts. © 2024 IEEE.

关键词： Sustainable city

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Leveraging internet of Things (IoT) Sensors and Deep Learning Techniques for Precision Agriculture 1

Leveraging Internet of Things (IoT) Sensors and Deep Learnin...

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1st international conference on Innovative Engineering Sciences and Technological Research, ICIEstR 2024

作者： Wilfred Blessing, N.R. Pyingkodi, M. Wasim Haidar, S.K. Palarimath, Suresh Paravathavarthini, S. Balakumar, C. Sheeja Kumari, V. Sutherlin Subitha, G. Seldev Christopher, S. University of Technology and Applied Sciences-Ibri College of Computing and Information Sciences Ibri Oman Kongu Engineering College Department of Computer Applications Erode India University of Technology and Applied Sciences-Salalah College of Computing and Information Sciences Salalah Oman Kongu Engineering College Department of Computer Technology Erode India Karpagam Academy of Higher Education Department of Computer Science Coimbatore India Saveetha Institute of Medical and Technical Sciences Department of Computational Intelligence Chennai India Stella Mary's College of Engineering Department of Computer Science and Engineering Aruthenganvilai India St. Xavier's Catholic College of Engineering Department of Computer Science and Engineering Nagercoil India

ISBN: (纸本)9798350348637

Precision agriculture, driven by advancements in technology, aims to optimize farming practices by utilizing data and technology to enhance efficiency, productivity, and sustainability This research introduces an innovative pilot investigation centered on the convergence of two revolutionary technologies are the internet of Things (IoT) and Deep Learning. With a specific focus on advancing precision agriculture, the primary objective of this study is to evaluate the combined effects of data collection facilitated by IoT and analytical capabilities of deep learning in enhancing and optimizing various agricultural processes. The integration of IoT in agriculture has revolutionized data acquisition, employing an array of sensors to monitor critical parameters such as soil moisture, temperature, and crop health. Concurrently, Deep Learning, a subset of artificial intelligence, exhibits the potential to glean actionable insights from voluminous datasets, offering advanced analytics and predictive capabilities. This study investigates the practical implementation and efficacy of this integration in a controlled agricultural setting. Sensors strategically positioned in the pilot study capture real-time data, while deep learning algorithms process and analyze this information. The primary objectives include evaluating the effectiveness of this combined technology in optimizing irrigation schedules, predicting crop yields, and identifying anomalies in crop health. Preliminary findings underscore the transformative potential of IoT and Deep Learning, empowering farmers with real-time data for informed decision-making. Key considerations encompassed in the study include IoT Sensors, Deep learning algorithms, and user adoption. The research not only sheds light on the technical intricacies of the integration but also delves into the challenges and opportunities inherent in merging these technologies within the agricultural landscape. As agriculture transitions towards the next

关键词： Smart agriculture

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Enhanced Cybersecurity: Development and Evaluation of a Secure Data Sharing Paradigm Based on Blockchain technology 1

Enhanced Cybersecurity: Development and Evaluation of a Secu...

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1st international conference on Electronics, Communication and Signal Processing, ICECSP 2024

作者： Geetha, R. Vijayanandh, T. Ananthi, S.N. Mercilin Raajini, X. Divya Sundar, V.S. Kumari Deepika, P. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of EEE Tamil Nadu Chennai India School of Computing Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Department of CSE Tamil Nadu Chennai India S.A Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India St. Joseph's College of Engineering Department of Artificial Intelligence and Data Science Tamil Nadu Chennai India

ISBN: (纸本)9798350364590

As time goes on and technology gets better, various data-sharing technologies are becoming more and more integrated into many different businesses. Therefore, data exchange and security are crucial for the data's value to be realized. Nevertheless, it is challenging to verify the authenticity of a basic data sharing method in order to detect electronic data usage traces. An further difficulty is the reluctance of data suppliers to provide their data. Employing Blockchain's distributed ledger, smart contract, data trust, and traceability features. For the purpose of facilitating secure access to data, this study introduces a blockchain-based data-sharing architecture that optimizes to circumvent the security and control issues associated with traditional centralized data sharing and administration. In addition, the research evaluates the practicality and safety of the prototype. Furthermore, this paper proposes a Secured Data Management Scheme (SDMS) that utilizes blockchain technology to optimize data sharing efficiency. To assess the efficacy of this model, it is cross-validated with the conventional Data Privacy Handler (DPH) method. While present centralized security solutions fail to meet security requirements in an IoT setting, blockchain technology provides a decentralized solution. Through the use of a blockchain and a WiFi-enabled network model, this article seeks to offer a secure communication framework for internet of Things (IoT) devices. According to the results, attitudes and character quirks have a role in how the intelligence community plans to use a blockchain-based data-sharing model for integrating systems. This research demonstrated the viability of using blockchain technology in an intelligence community-centric data-sharing strategy. © 2024 IEEE.

关键词： Data consistency

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distributed Authentication using Self Sovereign Identities 1

Distributed Authentication using Self Sovereign Identities

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1st international conference on Emerging Technologies for Dependable internet of Things, ICETI 2024

作者： Annadurai, Charan Sikora, Axel Welte, Dominik Offenburg University of Applied Sciences Badstrasse 24 Offenburg77652 Germany

ISBN: (纸本)9798331533557

Traditional authentication involves sharing a considerable amount of personal and identifying information. Usually, a single central authority controls the data of all their users. This creates a single point of failure and users typically have to relinquish control over their data. Therefore it is important to explore alternate authentication mechanisms to uphold data sovereignty. Data sovereignty describes forms of independence, control, and autonomy over digital data. Enforcing data sovereignty also requires independence from central authorities. This paper explores alternate decentralized authentication methods. It leverages Verifiable Credentials (VCs) which allow verification without needing to contact the issuer and self-sovereign identities in the form of Decentralized IDentifiers (DIDs). This paper aims to leverage the decentralized authentication supported by VCs and DIDs and provide two use cases that might explain how they could be used. © 2024 IEEE.

关键词： Authentication Protocol

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NLP-Based Sentiment Analysis using Deep Learning Methods 1

NLP-Based Sentiment Analysis using Deep Learning Methods

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1st IEEE international conference on Advances in computing, Communication and Networking, ICAC2N 2024

作者： Kumar, Dheeraj Bhatia, Sandeep Singh Dhillon, Hardeep Goel, Amit Kumar Galgotias University School of Computing Science and Engineering Greater Noida India Department of Applied Sciences Panjab Mohali140307 India Apeejay Stya University Sohna Gurugram School of Engineering and Technology India

ISBN: (纸本)9798350356816

Opinion mining systems rely heavily on sentiment analysis because to the vast amount of data and opinions that are generated, exchanged, and sent on a regular basis through the internet and other media. This study presents a deep learning network-based sentiment analysis categorization that was created and compares the results across multiple deep learning networks. Using the Multilayer Perceptron, a benchmark for other networks' performance was established (MLP). Built and implemented on the 50K movie review file IMDB dataset were a hybrid model of long short-term memory (LstM) and convolutional neural network (CNN), as well as an LstM recurrent neural network. Reviews for the dataset were 50% positive and 50% negative. After Word2Vec performed its initial pre-processing on the data, word embedding was applied. The hybrid CNN_LstM model outperformed the MLP and the separate CNN and LstM networks, as seen by the findings. While CNN reported an accuracy of 88.9%, MLP and LstM reported accuracy of 87.78% and 87.68, respectively. 89.4% accuracy was reported by CNN_LstM. Results further show that the proposed deep learning models have performed better than SVM, Naïve Bayes, and RNTN models based on English datasets presented in previous works. © 2024 IEEE.

关键词： Contrastive Learning

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A Brief Review on Security in IoT Environments Based on Fog computing Architecture 2

A Brief Review on Security in IoT Environments Based on Fog ...

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2nd international conference on Electrical Engineering and Automatic Control (ICEEAC)

作者： Damerdji, Djennet Oudjedi Lehsaini, Mohamed Benmahdi, Meryem Bochra Tlemcen Univ STIC Lab Tilimsen Algeria

ISBN: (纸本)9798350349740;9798350349757

The internet of Things (IoT) is an innovative technology that encompasses the connectivity of physical, intelligent objects to the internet, enabling the collection, sharing and analysis of data. Currently regarded as one of the revolutionary technologies of the 21st century, the significant increase of IoT devices and the huge amount of data they produce at the network's edge has led to the Cloud computing (CC) paradigm being over-loaded. Consequently, new computing paradigms are emerging, such as Edge computing and Fog computing (FC). Although these paradigms offer different functionalities and improve Quality of Service (QoS), they also introduce huge risks in terms of data security and privacy. This paper presents a brief review on security in IoT environments based on Fog computing (FC) architecture, with particular attention to security measures such as authentication, confidentiality and data integrity. Furthermore, it addresses attacks targeting these measures, in order to avoid or reduce security issues in Fog computing-IoT environments.

关键词： Fog computing IoT Cloud computing Security Authenticity Confidentiality Integrity

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A Comprehensive Survey on the Efficacy of Machine Learning Algorithms for Detecting DDoS Attacks 1

A Comprehensive Survey on the Efficacy of Machine Learning A...

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1st international conference on Data, Computation and Communication, ICDCC 2024

作者： Eswari, Dutta Sai Lakshmi, P.V. GITAM University Department of Computer Science and Engineering Visakhapatnam India

ISBN: (纸本)9798331532956

Denial-of-service (DoS) and distributed denial-of-service (DDoS) attacks are blatant attempts to prevent legitimate users from reaching a service or from using the service they already are using. DDoS attacks are possible due to the internet's current design, and an attacker gain control over many machines by exploiting their weak factors and setting up different targeted networks, also known as 'Botnets'. Once an attacker is ready with the targeted network, they can launch a massive, coordinated attack against a target or targets. As new attacks are constantly being created, and the number of hosts that may be attacked online continues to grow, several various DDoS attack detection and prevention methods have been developed to combat this growing threat. In this paper, we discuss a wide range of DDoS attacks and methods, as well as countermeasures. This review is useful because it addresses many different approaches to stopping DDoS attacks, such as detecting them, defending against them, minimizing their impacts, tracing their origins, answering unresolved problems, and overcoming research difficulties. © 2024 IEEE.

关键词： Botnet distributed denial of service attack Fuzzy logic Machine learning Naïve bayes

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Autonomous Hydroponic Farming using internet of Things 1

Autonomous Hydroponic Farming using Internet of Things

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1st international conference on Cognitive, Green and Ubiquitous computing, IC-CGU 2024

作者： Lal, Ratan Northwest Missouri State University MaryvilleMO United States

ISBN: (纸本)9798350361780

Natural sunlight is widely recognized as the best source for plant growth and development. However, during the winter months, some plants may not receive adequate light and may die due to neglect. To promote faster or balanced growth, we plan to develop a prototype for hydroponic systems. This system will enable us to provide the necessary nutrients, water, and light to plants whenever needed. The prototype comprises multiple sensors, including a pH sensor to monitor the pH level inside the water, a DHT11 sensor to detect the temperature and humidity of the environment, and a DS18B20 sensor to detect the water temperature. Additionally, it includes a relay used for controlling a water pump to maintain the water level inside the tank and an HCSR04 sensor to detect the water level. Moreover, the prototype features an ESP32 micro-controller that performs all the necessary computations, such as reading sensor values, turning on/off the water pump, and facilitating data transmission to farmers using the Blynk IoT application. This application is connected to the micro-controller through the internet. Finally, we deployed a pepper plant in the prototype, validated its functionality, and observed the data associated with the plant. © 2024 IEEE.

关键词： Hydroponics

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Rise of Diversity of internet of Things (IoT): A Review

Rise of Diversity of Internet of Things (IoT): A Review

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2025 international conference on Intelligent Control, computing and Communications, IC3 2025

作者： Sobana, P. Yaiaman, Gummagatta Vybhavi Kumar, A. Pradeep Karthi, S. Almusawi, Muntather Rani, Hema Sethu Institute of Technology Department of Computer Science Engineering Pulloor Tamil Nadu Kariapatti626115 India Gokaraju Rangaraju Institute of Engineering and Technology Department of Cse Telangana Hyderabad India Cmr College of Engineering & Technology Department of Ece Telanagana Hyderabad India Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil nadu Chennai India College of technical engineering The Islamic University Department of computers Techniques engineering Najaf Iraq Centre for Managament studies Gitarattan International Business School Delhi India

ISBN: (纸本)9798331527495

It has been established for a long time and has evolved correspondingly that actuators and sensor systems may be connected to the internet for the purpose of continuously monitoring and controlling biological phenomena. The term 'internet of Things (IoT)' was first used to combine these methods into a coherent framework a little more than a decade earlier. The IoT based idea has evolved along with science, adopting new vocabulary that is suited for technical advancements and many applications sectors. The IoT has undergone modifications since its inception, and this study examines studies on how technical advancements have transformed it as well and encouraged the emergence of modified terms appropriate for certain fields. A three separate study of the literature was done using games companies and classification data warehouses. First step involved looking for proposed changes on the Iot devices principle & evaluating them to compute the similarity, disparities, and functionality that enable us to generate a number of links its progression. The 1st step involved identifying and briefly assessing the much more common names handed to it IoT for multiple areas. As underpinning innovation continues to advance and software update areas are put out, the research supports the assertion that a consensus on the IoT concept is still not established. With information and information solutions playing an important role in the panorama, recent developments have been somewhat restrained and its variants on possible applications are distinct. © 2025 IEEE.

关键词： Labeled data

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Voice Automation Mail System for Visually Impaired 1

Voice Automation Mail System for Visually Impaired

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1st IEEE international conference on Networking and Communications, ICNWC 2023

作者： Malathi, D. Gopika, S. Awasthi, Dev Jayaseeli, Dorathi SRM Institute of Science and Technology Department of Computing Technologies Kattankulathur603203 India Kristu Jayanti College Department of Computer Science Bangalore Karnataka560077 India

ISBN: (纸本)9798350336009

The internet has emerged as one of the most crucial elements of modern life. Every single person uses the internet to access knowledge, information, and all communication tools available to them. However, many who are visually impaired find it difficult to use those features and need outside aid to complete their tasks. People with visual impairments all around the world now have a wide range of new opportunities because of the invention of computers. Screen readers, audio-based environments, and other assistive features have made it easier for blind persons to utilize the workspace. Today, email is required to send confidential information. Email is a type of technology that facilitates business correspondence and lets users transmit messages to other people. The main objective of this work is to develop a voice-based email system that will enable people who are blind or visually impaired to send and receive emails using computers. It will make advantage of modern features to create a working environment that enables persons with visual impairments to do their jobs independently. © 2023 IEEE.

关键词： Character recognition

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