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Effective utilization of embedded system and sensors with Wireless data monitoring for investigation of irrigation scheduling for Sugarcane crop 1

Effective utilization of embedded system and sensors with Wi...

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

作者： Karunendra, Kumar Kumbhar, Vidya Dhumal, Rajesh Kanse, Sohan Maharashtra Pune India Maharashtra Pune India

ISBN: (纸本)9798350361780

In this advanced technological era, farming methods and techniques also get upgraded to improve their yield so that farmers' profits improve. Precision farming uses drip irrigation techniques to optimize its resource utilization. Different technologies like the Internet of Things (IoT), artificial intelligence (AI), Sensors, and drones bring precise data that helps farmers better schedule and manage. This research paper aims to implement a sensor-based system that optimizes the irrigation schedule for Sugarcane crops in Satara, Maharashtra. In this research, two stages of sugarcane cultivation, i.e., Grand growth and maturation phases, are being monitored. Using a moisture sensor, real-time data is stored through a Wifi module, which determines the theoretical irrigation requirement using the Crop Water Requirement model. The theoretical irrigation requirement is compared with the current irrigation schedule. The study gives insights related to water requirements in different growth stages. During research, the Grand growth phase has a deficit of water as per their requirement. So, the irrigation schedule needs to be closely monitored with exact requirements that optimize the water resource. Conversely, the Maturation phase demonstrated a harmonious alignment between the irrigation schedule and crop water requirements. The research underscores the significance of precision irrigation with drip strategies attuned to specific growth stages for enhancing sugarcane yields. This study showcases the potential of sensor-driven monitoring and data-driven decisions to elevate agricultural practices, ensuring optimal water supply during pivotal growth periods and enhancing overall productivity and resource efficiency. The findings have implications for sustainable agricultural practices and contribute to advancing precision farming techniques. © 2024 ieee.

关键词： Soil moisture

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Evaluation Methods of Machine Translation Based on Big data Algorithms 3

Evaluation Methods of Machine Translation Based on Big Data ...

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3rd ieee international conference on Distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Zhang, Bing School Of Foreign Languages Guangdong University Of Science And Technology Dongguan China

ISBN: (纸本)9798350318609

In order to solve the challenges of machine translation evaluation methods, this study proposes an innovative machine translation evaluation method based on big data algorithms in view of the shortcomings of existing dynamic programming algorithms. This new scheme uses the principle of overlapping sub-problem theory to accurately identify and locate the key influencing factors, and accordingly carries out a wise classification of indicators to reduce possible interference. At the same time, by using the unique mechanism of big data algorithms, this scheme cleverly constructs the design strategy of translation evaluation methods. The empirical results show that the proposed scheme shows a significant improvement over the traditional dynamic programming algorithm in terms of the accuracy of the machine translation evaluation method and the processing efficiency of key factors, showing its obvious strong advantages. Machine translation evaluation methods play a crucial role in translation systems, which can accurately predict and optimize the growth trend and output results of machine translation evaluation methods. However, in the face of complex simulation tasks, traditional dynamic programming algorithms show some inherent shortcomings, especially when dealing with multi-level challenges, their performance is often unsatisfactory. To overcome this, this study introduces a new idea of machine translation evaluation method optimized by big data algorithms, and accurately controls the influencing parameters through the overlapping sub-problem theory, and uses this as a road map for index allocation, and then uses big data algorithms to innovate and construct a system scheme. © 2024 ieee.

关键词： Big data

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An Efficient Dimensionality ReductionTechniques to data data Visualization 3

An Efficient Dimensionality ReductionTechniques to Data Data...

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international conference on Advances in computing, Communication and Applied Informatics (ACCAI)

作者： Sasikala, R. Sakthi, P. Agalya, K. Vidhya, U. Karthik, M. Nareshkumar, R. CARE Coll Engn Dept Artificial Intelligence & Data Sci Trichy India SRM Valliammai Engn Coll Dept Informat Technol Chennai Tamil Nadu India Sri Eshwar Coll Engn Coimbatore Dept Comp Sci & Engn Coimbatore Tamil Nadu India Indra Ganesan Coll Engn Dept Informat Technol Tiruchirappalli India K Ramakrishnan Coll Technol Dept Comp Sci & Engn Trichy Tamil Nadu India SRM Inst Sci & Technol Coll Engn & Technol Sch Comp Dept Networking & Commun Kattankulathur Tamil Nadu India

ISBN: (纸本)9798350389432;9798350389449;9798350389456

The aim of this paper, is to gain insights in to dynamics of Kabaddi. This sport has become increasingly popular, by analyzing teams' performance in national leagues. To do so, the results of each round of matches the participating teams play are used to create a dissimilarity matrix. This matrix is then processed through two algorithms, A visualization of the outcomes of each team was achieved by the utilization of novel dimensionality techniques. This novel approach for dimensionality reduction enables the teams' performance to be represented in a lower-dimensional manner, facilitating the visualization of complex data connections. The t-SNE algorithm, on the other hand, captures the non-linear relationships in the teams' performance. This study attempts to discover crucial characteristics that impact team performance and give a greater knowledge of the dynamics of the sport by comparing the findings acquired using a novel dimensionality reduction technique. The data for this study comes from the Kabaddi season that took place during 2017-2018.

关键词： data Visualization Feature Projection Sports analysis Statistical analysis

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A Novel Multi-Objective Model for Feature Selection in Cancer data 1

A Novel Multi-Objective Model for Feature Selection in Cance...

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

作者： Panigrahi, Himanshu Sekhar Mishra, Itishree Mishra, Pritish Piri, Jayashree Silicon University Data Science Bhubaneswar India Silicon University Dept. of CSE Bhubaneswar India

ISBN: (纸本)9798350361780

Cancer is a vital disease taking several lives every year. Early detection can prevent lots of terrible cases. Traditional methods frequently don't achieve the best possible accuracy of diagnosis in the detection of cancer. This paper presents a complete framework to improve the feature selection process for cancer detection by integrating a multi-objective optimization approach. Developing a strong multi-objective feature selection method that optimizes computing efficiency, sensitivity, and specificity is one of the main goals. The proposed methodology leverages multi-objective feature selection and the Crayfish Optimization Algorithm (COA), using clues from crayfish behavior to improve exploration and exploitation at different phases. Thorough research and analysis have shown that the hybrid technique works well for optimizing feature subsets. When multi-objective optimization and COA are used, interpretability is enhanced as well as the precision of classification. The study's findings indicate positive advancements in the field of cancer, and the suggested design holds great potential for streamlining feature selection procedures and lowering the complexity of cancer data. MO-COA excels over MOGA and MOPSO, achieving 96.7% average accuracy in breast cancer with 3 average features, surpassing MOGA's 95.3% (2 features) and MOPSO's 95.7% (4 features). In lung and cervical cancer, MO-COA achieves 60.5% (10 features) and 95.5% (5 features) accuracies respectively, outperforming MOGA (52.2% lung, 95.2% cervical) and MOPSO (52.4% lung, 94.2% cervical). The average is taken for total non-dominated solutions for each algorithm over different datasets. These findings underscore MO-COA's efficiency over other algorithms in enhancing cancer diagnosis accuracy with minimal features, benefiting both research and clinical practice. © 2024 ieee.

关键词： Feature Selection

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A Well-Structured data Sharing System Implementation using EC Technology and Higher end Communication Network 4

A Well-Structured Data Sharing System Implementation using E...

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4th ieee international conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Kumar, Ashok Jasim, Laith Pramanik, Atreyi Maheswari, G. Sangeetha, S. Angadi, Sanjeevkumar Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India The Islamic University Najaf Iraq Uttaranchal University School of Applied and Life Sciences Division of Research and Innovation Uttarakhand Dehradun India Hindustan Institute of Technology and Science Department of Information Technology Chennai603103 India Cmr College of Engineering & Technology Department of Eee India Nutan College of Engineering and Research Computer Science and Engineering Pune Maharashtra Talegaon Dabhade India

ISBN: (纸本)9798350360165

Vehicular traffic networks (VANETs) are an important part of modern transportation systems, focusing on critical applications such as collision avoidance, lane change assistance, and traffic recognition. However, data distribution in VANETs is very challenging, especially due to the unique characteristics of wireless communications and the dynamic traffic environment. In this context, packet delivery control is very important for proper communication. In this paper, research proposes a new Computer defined Vehicle Network (SDVN) Controlled Routing and Scheduling (CDRS) method to solve the complex data distribution problem of VANET unlike existing approaches, CDRS uses SDVN management functions to integrate a routing strategy and a scheduling strategy that optimizes multihop data transmission. Priorities in CDRS are based on routing and scheduling constraints. Current protocols focus on finding the shortest path connecting source and destination pairs, ignoring factors such as packet proximity and link length, but performance is limited in dynamic VANET environments. Similarly, current scheduling approaches focus on single-hop data distribution and ignore the © 2024 ieee.

关键词： Vehicular ad hoc networks

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Big data Analytics for Smart Cities 1

Big Data Analytics for Smart Cities

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

作者： Singh Rathore, Saurabh Pratap Vishnubhai Dalabhai, Chaudhary Babubhai Patel, Chintan Kumar Sharma, Rajeev Mathur, Aditya Yadav, Arti ICAPSR Dept. of Management New Delhi India Madhav University Dept. Physical Education Pindwara India Mangalayatan University Dept. of Buss. Management and Commerce Aligarh India Lingayas Vidyapeeth Dept. of Pharmacy Faridabad India J.S. University Dept. of Computer Science Shikohabad India

ISBN: (纸本)9798350356816

The concept of smart cities represents a pivotal shift in urban development, leveraging advanced technologies to improve efficiency, sustainability, and quality of life. At the heart of this transformation lies big data analytics, enabling cities to harness vast volumes of data for informed decision-making and strategic planning. This paper examines the pivotal role of big data analytics in the context of smart cities, focusing on its applications across key domains such as urban planning, transportation management, energy optimization, public safety, and citizen engagement. By integrating data from sensors, IoT devices, and digital platforms, cities can optimize resource allocation, predict urban trends, and enhance service delivery. However, this transformative potential is accompanied by challenges related to data privacy, security, and governance, necessitating robust frameworks and *** on current research and technological advancements, this paper provides a comprehensive overview of how big data analytics can empower smart cities to address complex urban challenges effectively. It explores case studies and initiatives from around the globe to illustrate best practices and innovative approaches. Ultimately, the integration of big data analytics not only enhances operational efficiencies but also fosters more sustainable and resilient urban environments. This paper concludes by outlining future directions for research and implementation, emphasizing the need for interdisciplinary collaboration and stakeholder engagement in shaping the cities of tomorrow. © 2024 ieee.

关键词： Sustainable city

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Navigating the Generative AI Project Ecosystem with a Focus on Addressing data Architecture complexities and Strategic Model Selection for Optimal Outcomes

Navigating the Generative AI Project Ecosystem with a Focus ...

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2024 OPJU international Technology conference on Smart computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Gupta, Priyanka Kumari, I. Vasantha Rajalakshmi, B. Nijhawan, Ginni Praveen Mazaal, Zahraa Sahib Institute of Aeronautical Engineering Hyderabad Dundigal India Siddhartha Institute of Technology and Sciences Medchal Malkajgiri District Hyderabad Telangana India New Horizon College of Engineering Department of Computer Science Bangalore India Lovely Professional University Phagwara India Lloyd Institute of Engineering & Technology Knowledge Park II Uttar Pradesh Greater Noida201306 India National University of Science and Technology Collage of Dentist Dhi Qar64001 Iraq

ISBN: (纸本)9798350373783

This article discusses the Generative Artificial Intelligence (AI) project's complex ecology and how to pick the optimal models and data design. Creative AI in many commercial and academic fields presents new issues and opportunities. Knowing your way around generative AI projects is crucial. Choose models carefully since data design is hard to grasp. This research provides comprehensive guidance on how to address these areas and ensure project success. data architecture study is the first step towards generative artificial intelligence since it identifies common issues and viable solutions. Next, to determine which generative models - in terms of complexity, scalability, and ethics - are best suited for a range of tasks, we must evaluate and compare many of them. Researchers were able to validate these findings using case studies and expert interviews. The results suggest that an ordered data infrastructure is required for creative AI. This study indicated the need to boost generational artificial intelligence programs by making practitioners and researchers more aware of the challenges. The study argues that further research and development are necessary to keep up with the fast progress of creative artificial intelligence. © 2024 ieee.

关键词： Generative adversarial networks

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Real-Time Stress Monitoring using IoT and Machine Learning for cognitive Wellness 5

Real-Time Stress Monitoring using IoT and Machine Learning f...

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5th international conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Thangam, S. Karthik, Garikipati Muppala, Tejaswi Vinitha Chowdary, A. Kumari, J. Jesy Janet Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350379945

Stress monitoring and management became some of the most vital requirements for maintaining overall well-being in high-stress environments. This work deals with the challenging issue of real-time stress detection using a fusion of the Internet of Things and machine learning technology implemented on a Raspberry Pi. Using the proposed model, the following physiological signals are collected using a Pulse Sensor for heart rate, a DS18B20 sensor for temperature, a DHT22 sensor for humidity, and a Grove GSR sensor for galvanic skin response (GSR). Based on the collected data, a hybrid model of Support Vector Machines and Random forests was trained, which would ultimately classify stress into different levels. A Snake game dynamics were controlled through a joystick. Using the predicted stress levels, the game difficulty is automatically adjusted, to provide real-time biofeedback for the user's cognitive wellness and stress management. This ensures that the user is calm and focused. The system effectively adapted to the gaming environment based on the stress levels of the player and it will serve as a promising tool to enhance cognitive wellness through game interaction. © 2024 ieee.

关键词： Biofeedback

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Fusion data on Fuzzy Modality: From Algebraic Interpretations to Quantum Simulations via Qiskit Platform

Fusion Data on Fuzzy Modality: From Algebraic Interpretation...

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2024 ieee international conference on Systems, Man, and Cybernetics, SMC 2024

作者： Buss, Juliano Novack, Bruna Botelho, Cecilia Santos, Helida Lucca, Giancarlo Cruz, Anderson Yamin, Adenauer Reiser, Renata Universidade Federal de Pelotas CDTec RS Pelotas96010-610 Brazil Universidade Federal Do Rio Grande C3 RS Rio Grande96203-900 Brazil Universidade Católica de Pelotas Ppgc RS Pelotas96010-000 Brazil Universidade Federal Do Rio Grande Do Norte Imd Natal-RN59078-900 Brazil Universidade Federal de Pelotas Ppgc RS Pelotas96010-610 Brazil

ISBN: (纸本)9781665410205

This study is given at the intersection of three important areas: Modal Logic (ML), Fuzzy Logic (FL), and Quantum computing (QC), leveraging from their main features. On the one hand, we have the QC ability to handle complex data more efficiently, taking advantage of the quantum mechanics concepts. On the other hand, ML and FL allow us to express uncertainties by mathematically modeling the imprecision of the natural language. Therefore, we first provide an algebraic model to interpret modal operators on fuzzy logic, and then we represent them in a quantum computing environment. Besides, we present some case studies simulating the fuzzy modal connectives in the Qiskit platform, aiming to better understand the evolution of quantum circuits. © 2024 ieee.

关键词： Fuzzy logic

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Envisaging the patterns in Blockchain 7

Envisaging the patterns in Blockchain

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7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Nagarajan, G. Atmakuri, Sukeerth Nalamati, Sri Satyendra Minu, R.I. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India SRM Institute of Science and Technology Department of Computing Technologies Kattankulathur India

ISBN: (纸本)9798350372816

Cryptocurrency is becoming more mainstream, and experts predict that its market size will reach dollar 2.2 trillion by 2026. However, it's also an intangible and highly volatile asset that poses significant challenges for governments, anti-money laundering analysts, and financial crime investigators. Compliance with strict regulations is also a challenge facing virtual asset service providers. The price of Bitcoin hit an all-time high in January 2021, making headlines worldwide. As the popularity of cryptocurrency continues to grow, AML analysts and financial crime investigators face tougher challenges. VASPs are under pressure to comply with tighter regulations, and both parties need to take a proactive approach. Bitcoin visualization is a solution that involves visualizing a Bitcoin block, enabling analysts to clarify complex and dense blocks of transaction data quickly to identify high-risk activity. Instead of looking at historic Bitcoin transactions, analysts can now examine Bitcoin activity in real-time using a powerful Bitcoin network visualization chart showing key connections, combined with a dedicated Bitcoin timeline view featuring precise transaction details as they occur. We conducted a thorough and quantitative assessment of 76 analytics tools, including those proposed in academic research and those endorsed by professionals and blockchain enthusiasts online, to provide a comprehensive analysis of the facets of blockchain data that have been thoroughly investigated. We also identified areas that warrant further exploration in future research. © 2024 ieee.

关键词： Blockchain Blockchain tools data parsing data Visualization Graph Modelling Graph-based analysis

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