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Intelligent deep-well rescue system using ultrasound sensors /
"Patent Number: 201941048191, Applicant: Debabrata Samanta.
The present invention is related to an intelligent deep-well rescue system using ultrasonic sensors. The system for rescue a human in a narrow diameter deep-well (bore-well) comprises an ultrasonic sensor module, a grappling module, a central computing unit. The objective of the present invention is to solve the problems of the prior arts in solving issues of rescue of human being from the deep-well or bore well." -
Intelligent deep-well rescue system using ultrasonic sensors /
Patent Number: 201941048191, Applicant: Dr. Debabrata Samanta.
The present invention is related to an intelligent deep-well rescue system using ultrasonic sensors. The system for rescue a human in a narrow diameter deep-well (bore-well) comprises an ultrasonic sensor module, a grappling module, a central computing unit. The objective of the present invention is to solve the problems of the prior arts in solving issues of rescue of human being from the deep-well or bore well. -
Intelligent Course Recommendation for Higher Education based on Learner Proficiency
A course recommendation provides valuable guidance and support to learners navigating their educational and career journeys. Artificial Intelligence paves the way for recommending higher education courses. In this article, a framework is proposed that uses different features like learners' interest, their past performance and mainly their family talent history. This framework emphasizes the Intelligence Robotic Course Recommendation System. The system is very helpful for the learner who don't have that much of an explorer of the current trends happening in the world. When the learners similarity knowledge interest is known with respect to real-world needs, the perfect higher education is suggested for them. This paper shows that the framework gives better results when using with artificial intelligence algorithms. 2023 IEEE. -
Intelligent Approaches of Clinical and Nonclinical Type-1 Diabetes Data Clustering and Analysis
Every year in India, there are nearly 15,600 fresh cases being reported among these age groups. In 2011, in the United States, 18,000 children under 15 were newly reported for T1DM. Over 13years, the Karnataka state government has a list of records showing that out of 100,000, 37% of boys and 40% of girls are affected by T1DM Disease. This paper investigates two methodologies to identify significant details about Type-1 diabetes. The first methodology is applicable to clinical data. The second methodology is demonstrated for the NDA T1D dataset. The dataset is utilized further to apply machine learning techniques to group similar patient traits. Exploratory data analysis on the dataset has revealed significant information answering a few research questions. This analysis can be useful for India, China, and other countries with high populations. In this paper, a unique methodology based on Artificial Intelligence Technique is proposed for both clinical and non-clinical data. The Autoimmune Disease, Diabetes Type 1-T1D, is focused. Non Clinical data based on 2021 reports are collected to identify patterns. Substantial unique issues are addressed in this work which were never reported before. The knowledge generated can be helpful for creating new clinical datasets, methodology and new insights related to Type-1 diabetes. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Intelligent approach to automate a system for simulation of nanomaterials
Nanomaterial composites are generally found to have great thermal properties and hence have witnessed an increasing demand in the recent years for manufacturing of efficient miniature electronic devices. The process of finding the right composites that exhibit the desired properties is a rather tedious task involving a lot of trial and error in the current scenario. This paper proposes a methodology to digitize and automate this entire process by administering certain efficient practices of assessing the properties of nanomaterial like Coarse Grained Molecular Dynamics thus resulting in faster simulations. 2023 Author(s). -
Intelligent agriculture - Smart IOT system to assist farmers in effective decision making using data science /
Patent Number: 202141046585, Applicant: Dr.S.Balamurugan.
Research studies shows that the current world population of 7.3 billion is expected to increase to 9.3 billion by the ear 2050. In order to feed the increasing population, Food and Agricultural Organization (FAO), plans to increase the crop cultivation by 70%. Recent days have seen a steep rise in the adoption of IoT to various factors affecting agriculture like climate change monitoring, greenhouse automation, crop cultivation and management, cattle monitoring and management, precision farming, agricultural drones, predictive analysis for smart farming and many more. This invention discloses a Data-driven smart IoT system to help farmers for effective decision making on the choice of the crop to be cultivated in the given time. IoT sensors are capable to predict the humidity in the soil, nature of chemical resources that are apt for cultivation and weather forecasting. -
Intelligent Agents System for Vegetable Plant Disease Detection Using MDTW-LSTM Model
When it comes to agricultural output, nation, India, ranks first in the world, and agriculture is unparalleled. The need to categorize and trade agricultural goods is paramount. Manual organization, which is tedious and laborious, is not a choice. When agricultural products are graded automatically, a lot of time is saved. The application of image processing techniques facilitates the examination and evaluation of the products. A technique for identifying diseased vegetables is the focus of this effort. Feature extraction, preprocessing, segmentation, and training the model are all heavily dependent on sequence. Among the preprocessing technologies at disposal are image segmentation and filtering. Using Kapur's thresholding based segmentation method, the image's sick areas can be located during the segmentation process. Use k-means clustering for feature extraction to identify vegetable plant diseases. The training of an MDTW-LSTM model relies heavily on feature selection. In terms of performance, the proposed method surpasses two cutting-edge algorithms: LSTM and DTW. The results showed an accuracy of 97.35 percent, indicating a remarkable improvement. 2024 IEEE. -
Intelligence-Software Cost Estimation Model for Optimizing Project Management
With the evolution of pervasive and ubiquitous application, the rise of web-based application as well as its components is quite rising as such applications are used both for development and analysis of the web component by developers. The estimation of software cost is controlled by multiple factors right from human-driven to process driven. Most importantly, some of the factors are never even can be guessed. At present, there are no records of literature to offer a robust cost estimation model to address this problem. Therefore, the proposed system introduces an intellectual model of software cost model that is mainly targets to perform optimization of entire cost estimation modeling by incorporating predictive approach. Powered by deep learning approach, the outcome of the proposed model is found to be cost effective in comparison to existing cost estimation modeling. 2019, Springer Nature Switzerland AG. -
Intelligence in Children Whose Either Parent Is Treated For Schizophrenia.
G.J.B.A.H.S.,Vol.2(4):119-123- October- December ISSN: 2319-5584 -
Intellectual property rights vis-a-vis food security: A critical analysis
The Right to Food is undoubtedly a human right since it is one of the basic necessities without which it is impossible to sustain life. Food Security refers to the availability as well as accessibility to sufficient and quality food by all individuals. However, there persists a problem of food insecurity which is a major problem especially in the underdeveloped and, to a considerable extent, the developing countries. At an individual level, food security is limited to one's access to food but on a broader sense food security cannot be isolated from agricultural policies, crop technologies, economic and trade conditions. The intersection of crop technologies with economic factors is what links food security with Intellectual Property Rights (IPR). Over the recent past, IPR has gained immense importance in a number of fields including agriculture. It provides the incentive for the private sector development in advancement of plant science and crop technologies which helps in ensuring food security in the long term. This study aims at discussing the issues of food security with a specific focus on the developing nations, IPR regime, and its introduction into the agriculture sector. It intends to explore the connections and linkages between IPR and food security, especially how intellectual property can act as a medium to cover the path toward achieving global food security. The author aims to put forth the ability of IPR as a means to achieve food security by incentivising human creativity through a detailed study from an international as well as region-specific perspective. 2023 Apple Academic Press, Inc. All rights reserved. -
Intellectual Property Right - Copyright
The power of cognition of human beings is beyond the imagination of any cognitive person. As gifted and nurtured property, the intellect of human beings has the potential to be original, creative, and innovative. Has the human being got absolute control over her/his intellect? Can human beings possess absolute rights over any product of her/his intellect? How far is a human being indebted to society? If human beings are not given due credit to the product of her/his intellect, the enthusiasm to be more creative and productive may take a coarser path. Human beings have the fundamental right to use her/his intellect to live a life of their choice enjoying economic and non-economic benefits. The right to intellectual property is fundamental to human beings. Hence, any infringement of intellectual property has to be dealt with appropriately. At the same time, human beings should be indebted to society for nurturing their intellect. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Integrity assured multi-functional multi-application secure data aggregation in wireless sensor networks (IAMFMA-SDA)
Industrial revolutions and demand of novel applications drive the development of sensors which offer continuous monitoring of remote hostile areas by collecting accurate measurement of physical phenomena. Data aggregation is considered as one of the significant energy-saving mechanism of resource constraint Wireless Sensor Networks (WSNs) which reduces bandwidth consumption by eliminating redundant data. Novel applications demand WSN to provide information about the monitoring region in multiple aspects in large scale. To meet this requirement, different kinds of sensors of different parameters are deployed in the same region which in turn demands the aggregator node to integrate diverse data in a smooth and secure manner. Novelty in applications also requires Base station (BS) to apply multiple statistical functions. Hence, we propose to develop a novel secure cost-efficient data aggregation scheme based on asymmetric privacy homomorphism to aggregate data of multiple parameters and facilitate the BS to compute multiple functions in one round of data collection by providing elaborated view of monitoring region. To meet the claim of large scale WSN which requires dynamic change in size, vector-based data collection method is adopted in our proposed scheme. The security aspect is strengthened by allowing BS to verify the authenticity of source node and validity of data received. The performance of the system is analyzed in terms of computation and communication overhead using the mathematical model and simulation results. 2023 - IOS Press. All rights reserved. -
Integration of technology initiatives with educational neuroscience and its impact on technology readiness to technology adoption by HSS Teachers, Kerala
The technology-enabled education process remoulded the modern education systems. The facelift of education 4.0 process harmonized the education systems with industrial demands and technology advancements. The education reforms of the State of Kerala with the tools of technology and neuroscience could achieve remarkable milestones in the education sector. This case study analyses the digital initiatives of KITE and its role on providing uninterrupted-effective education during the Covid-19 pandemic in Kerala. This study is affirmed with quantitative study on how these integrated technology initiatives impact on Technology Adoption of the HSS teachers with respect to their Technology Readiness. Responses of 857 teachers from six education districts of Kerala were used for this study. This study is relevant as it could connect the pre-Covid digital initiatives which could successfully empower the teachers to face the Covid-19 pandemic situation without interrupting the education process amidst the Covid-19 restrictions in Kerala. The study identified that the technology learning initiatives with tools of educational neurosciences have partially mediated teachers' Technology Readiness to Technology Adoption. The multiple learning initiatives integrated with the tools of technology and educational neuroscience could fully support the virtual learning throughout the State of Kerala during the Covid-19 pandemic situations. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved. -
Integration of sustainability in business through finance
[No abstract available] -
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Integration of Mobile Edge Computing in Wireless Technology
This chapter delves into the potential for Mobile Edge Computing (MEC) to revolutionize wireless networks through its incorporation in wireless technologies. The authors give a thorough introduction to MEC, including its components, design, and the reasoning behind combining it with wireless networks. This chapter provides a foundational understanding of technologies for wireless communication, focusing on the establishment and improvement of 4G, 5G, and Wi-Fi networks. Different deployment strategies and supporting technologies for MEC integration with mobile networks are explored to demonstrate the adaptability and scalability of this approach. Improved connection, lower latency, and higher bandwidth utilization are just some of the benefits and obstacles of MEC integration that are demonstrated using practical scenarios and applications. This chapter also discusses techniques for optimizing performance and managing resources, as well as security and privacy concerns unique to wireless networks that make use of MEC. In this article, we explore the continuing standardization efforts and industry activities that are pushing MEC usage in wireless networks. Finally, the authors describe the unanswered questions and potential future developments in MEC-enabled wireless networks. This chapter presents a thorough analysis of MEC's incorporation into wireless technology, revealing how this development has the potential to revolutionize mobile communications and open up fresh avenues for developing useful services and applications. 2024 CRC Press. -
Integration of Intelligent System and Big Data Environment to Find the Energy Utilization in Smart Public Buildings
Buildings are the leading consumer of energy in the setting of smart cities, and public structures such as hospitals, schools, government offices, and additional institutions have high energy needs owing to their frequent use. However, there needs to be adequate use of the latest innovations in machine learning inside the big data context in this field. Controlling the energy efficiency of public subdivisions is a crucial aspect of the smart city concept. This chapter aims to address the challenge of integrating big data platforms and machine learning algorithms into an intelligent system for this purpose to forecast how much energy various Croatian government buildings will consume, prediction models were constructed using deep learning neural networks, Rpart regression tree models, and random forests using variable reduction techniques. The evaluation of all three techniques considered critical aspects, and the random forest methodology yielded the most precise model. The MERIDA intelligent system aims to enhance energy efficiency in public buildings by integrating big data and predictive algorithms. This research examines the technological requirements for a platform that facilitates public administration in planning public building reconstruction, reducing energy consumption and expenses, and connecting intelligent public buildings in smart cities. Digitizing energy management may improve public administration efficiency, service quality, and environmental health. 2025 Scrivener Publishing LLC. All rights reserved. -
Integration of Hyperspectral Imaging and Deep Learning for Sustainable Mangrove Management and Sustainable Development Goals Assessment
Mangrove forests support biodiversity and provide valuable ecosystem services. Their conservation is important for maintaining these benefits. In addition to this, understanding and preserving these forests is important for the assessment of Sustainable Development Goals (SDGs) such as SDG 1,2,3,6,8,11,12,13,14 and15. This review paper explores how the integration of Hyperspectral Image (HSI) technology and Deep Learning (DL) algorithms is helpful in mangrove conservation and SDGs assessment. HSI in mangrove research allows detailed analysis of tree health, species types and environmental stress factors (includes salinity levels, waterlogging, soil erosion, pollution, habitat fragmentation, disturbances from human activities etc.) with enhanced spectral and spatial resolution. Combining DL algorithms like Convolutional Neural Network (CNN) with HSI data automates mangrove mapping, detects change in mangrove health, estimates carbon sequestration and manages ecological zone. Rich spectral information from HSI empowers DL algorithms to identify patterns and features for accurate and efficient classification tasks in both supervised and unsupervised methods. This review aims to comprehensively summarize the research efforts reported in monitoring mangrove ecosystems through varied remote sensing approaches, algorithms and their support towards SDGs assessment. HSI and DL together offer a powerful approach for researchers, environmentalists and climate activists working towards sustainable development objectives. This paper not only focuses on mangrove conservation but also addresses challenges associated with integrating technologies such as data processing complexities and the need for specialized expertise. This study outlines advancements in HSI technology, DL applications and future directions to drive sustainable management strategies for mangrove ecosystems. The Author(s), under exclusive licence to Society of Wetland Scientists 2025. -
Integration of enterprise resource planning system as an effective technology for increasing business productivity
Enterprise Resource Planning (ERP) refers to a potential software, which organisations utilise for managing daily basis activities such as proper accounting, project management, compliance as well as procurement actions within organisational standards for achieving better business performance. This research focuses on understanding ways of ERP usage of businesses for enhancing potential procurement as well as accounting for assuring best performance achievement. Literature from different company reports and other sources has been implemented that brings out an understanding of productivity optimisation of organisations using ERP. It also focuses on illustrating different types of ERP along with assuring better data visibility aspects of the ERP usage for allowing consumers to view real time data while progressing with business relationships and enabling higher procurement standards. The research aims to investigate ways in which different types of ERP are used by organisations for assuring better accounting performance and procurement standards in their marketing environment. Hypothesis is a positive association between ERP utilisation and implementation in organisation and its accounting and procurement standards, achieving high performance in the competitive market. Methodology used in this research involves Exploratory research design with a probability sampling for bringing out best possible outcomes of the research. Sample sizes include secondary sources such as articles, journals and relevant company reports and databases for understanding ways in which ERP helps in attaining suitable accounting and procurement practices of businesses within organisational standards. Results as well as implications indicate an optimal relation of proper risk management through enhancing ERP and usage of most suitable ERP that assures best possible procurement and accounting practices for businesses to get competitive advantage in the market. 2024 Author(s). -
Integration of blockchain to IoT: Possibilities and pitfalls
[No abstract available]