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Internet of Things-Based Smart Agriculture Advisory System
The Internet era provides a lot of automation tools for data analysis, and it is the need of the hour to develop new analytical tools to manage the big data. For task automation, machine learning and expert systems are of primary importance to study the behavior of computer thinking to involve computers in sensible work, known as computational intelligence. The data involves varied formats such as structured, unstructured, as well as semi-structured, and it is an automation tool that uses computational intelligence to extract valid and potential information from the sources. The specific purpose of this proposed work is to meet out computing demands which highly rely on computational intelligence. Computational intelligenceinvolves the design and deployment of an analytical tool for multidimensional data analytics. The proposed integrated framework focuses on multidimensional data analytics, for crop and plant data, especially plants that contain medicinal values and components. This research works main aim is to create a secured data tool for agriculture crop data management through big data (crops and plants) analytics. The data security is enhanced through applied cryptography, and the final phase prediction on crops is done by various machine and deep learning algorithms. The specific objective of this research work is to help farmers in making informed decisions for the enhancement of cultivation and information. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Internet of Things Security and Privacy Issues in Healthcare Industry
The Internet of Things (IoT) is an imagines unavoidable, associated, and hubs connecting independently while offering a wide range of administrations. Wide conveyance, receptiveness and moderately high handling intensity of IoT objects made them a perfect focus for digital assaults. Additionally, the same number of IoT center points is assembling and taking care of private data, they are changing into a goldmine of information for malignant on-screen characters. Subsequently, security and particularly the capacity to recognize traded off hubs, together with gathering and safeguarding confirmations of an assault or malignant exercises develop as a need in effective arrangement of IoT systems. This paper is deal with some major security problems and challenging factors of IoT. This IoT security issues on really challenging factor in current world. 2019, Springer Nature Switzerland AG. -
Internet of Things in Bioelectronics: Emerging Technologies and Applications
This book provides a comprehensive exploration of the exciting intersection between technology and biology and delves into the principles, applications, and future directions of IoT in the realm of bioelectronics; it serves as both an introduction for those new to the field and as a detailed reference for experienced professionals seeking to deepen their knowledge. The rapid convergence of technology and biology heralds a new era of evolution in the Internet of Things (IoT), a transformative force enabling interconnected devices to communicate and operate with unparalleled synergy. This is particularly true in the groundbreaking field of bioelectronics, where the fusion of biological systems with electronic devices and IoT is reshaping the landscape of bioelectronics, promising to open up new frontiers in healthcare, diagnostics, and personalized medicine. This timely book explores the numerous ways in which IoT-enabled bioelectronic devices are used to monitor and enhance human health, from wearable sensors that track vital signs to implantable devices that can communicate with healthcare providers in real time. One central theme of this book is the transformative impact of IoT on healthcare. By enabling continuous, remote monitoring of patients, IoT technologies are not only improving the accuracy of diagnostics but also making healthcare more accessible and personalized. The book also addresses the critical issues of securing health records on the internet, which are of paramount importance as we increasingly rely on interconnected devices to collect and transmit sensitive health information. Additional attention is paid to the future directions of IoT in bioelectronics and the integration of innovative areas, such as artificial intelligence, machine learning, and big data analytics, in driving the development of ever more sophisticated and capable bioelectronic systems. Audience The target audience includes professionals, researchers, academics, and students involved in various fields related to bioelectronics, IoT, healthcare, biotechnology, engineering, and related disciplines. 2024 Scrivener Publishing LLC. -
Internet of things for building a smart and sustainable environment: A survey
In the previous decade, internet of things (IoT) has emerged as a transformative force in the quest to create smarter and more sustainable environments. By interconnecting a large array of sensors, devices, and infrastructure, IoT technology enables the real-time collection, analysis, and utilization of data to optimize resource management, improve decision-making, and reduce environmental impact. In smart cities, homes, industries, and agricultural settings, IoT plays a pivotal role in achieving resource efficiency, environmental preservation, and economic growth. However, its widespread adoption also poses several challenges related to privacy, security, and interoperability. As IoT continues to evolve, it promises to shape a future where sustainability and technological innovation go hand in hand, making a path toward more resilient, efficient, and livable environments. 2024, IGI Global. All rights reserved. -
Internet of Things Enhancing Sustainability of Business
When one assumes that the current era is the era for digital revolution then the Internet of Things (IoT) is supposed to be one of the most significant among all. It is the IoT which is assisting the bussinesses. Current IoT applications, on the other hand, are still in their early stages, and the true capacity of viable business opportunities has yet to be realised. However, IoT adoption may need considerable integration and experienced personnel. It also frequently generates new requirements in terms of security and interoperability, or the ability for different computer hardware systems as well as software applications to "speak"to one another. 2022 IEEE. -
Internet of Things Enabled Device Fault Prediction System Using Machine Learning
Internet of Things (IOT) started as a niche market for hobbyists and has evolved into a huge industry. This IoT is convergence of manifold technologies, real-time analytics, machine learning and Artificial Intelligence. It has given birth to many consumer needs like home automation, prior device fault detection, health appliances and remote monitoring applications. Programmed recognition and determination of different kinds of machine disappointment is a fascinating process in modern applications. Different sorts of sensors are utilized to screen flaws that is discovers vibration sensors, sound sensors, warm sensors, infrared cameras, light cameras, and other multispectral sensors. The modern devices are becoming ubiquitous and pervasive in day to day life. This device is need for reliable and predicate algorithms. This article is primarily emphases on the prediction of faults in real life appliances making our day to day life easier. Here, the database of the device includes previous faults which are restored in online by using cloud computing technology. This will help in the prediction of the faults in the devices that are to be ameliorated. It additionally utilizes Nae Bayes calculation for shortcoming location in the gadgets. The proposed model of this article is involves the monitoring of each and every home appliance through internet and thereby detect faults without much of human intervention. Springer Nature Switzerland AG 2020. -
Internet of things based metaheuristic reliability centered maintenance of distribution transformers
The transformer is a vital component of the power system. Continuous stress on the transformer due to overload, transient and faults will lead to physical damages. The isolation of the transformer causes significant revenue loss and inconvenience to the consumers at the distribution level. This invites the need to achieve a reliable power supply to the consumers and to perform maintenance activity appropriately. Optimized and predictive maintenance strategies are evolved to improve power availability for consumers. The model considers dispersive generation at the customer end, namely solar photovoltaics standalone system, diesel generation, and vehicle to load capabilities. Incipient or critical status of transformers' functional parameters are observed through the transformer terminal unit and sent to the internet of things platform. The remote processing unit acquires the information from all the distribution transformer and generates the optimized and reliability-centered maintenance schedule. In the proposed work, new reliability indices concerning the consumer dispersive generation are defined. The maximization of the reliability problem is solved using the coconut tree optimization technique. The highest reliability of power supply to the consumer and maintenance schedule are obtained. Economic facet of the estimated maintenance schedule exhibit benefit for both utility and consumer as it encapsulate time of use tariff. The heuristic dataset is used to synthesize the trained model by the machine learning algorithm and future maintenance schedule is predicted. The comparative study is made for the outcome of time-based optimized and predicted maintenance schedules against reliability. 2020 Institute of Physics Publishing. All rights reserved. -
Internet of things based financial data managing device in bank /
Patent Number: 359269-001, Applicant: Sapna Bisht. -
Internet of Things Based Autonomous Borewell Management System
Water is a basic need for all living beings. At present, due to a large population, water level is getting depleted at an alarming rate particularly in urban region. During summer season, there is no continuous flow of water or availability of water. In electrical contingency situations, bore-wells are prone to damages. The utilization of power at dry run condition affects the economy of the consumers. Despite having no water in the bore-well, if the motor runs, the motor windings may burdened and gives rise to unnecessary power loss. In the present scenario, conservation of energy is a major concern. The conservation of energy as a whole will take place when an individual take an active part by using autonomous and effective methodologies or controllers. The issue is solved by managing the borewell using Internet of Things (IoT) as a platform to automate and manage. The IoT based borewell management system is designed to provision scheduling, manual operation, avoidance of borewell motor running at dry run condition and also nullifies energy loss. The automated borewell operations can be executed from a remote control and measurement unit by the measurement of electrical parameters and analytics. The proposed system minimizes man power, saves time and conserve energy loss. The paper presents operating the conventional borewell by deployment of smart controller which handles the information and communication technology at client and base units. Springer Nature Switzerland AG 2020. -
Internet of Things and Machine Learning based Intelligent Irrigation System for Agriculture
Irrigated agriculture methods need a significant volume of water, and causes water waste. It is critically necessary to install an efficient watering system and lessen the volume of water wasted on this tiresome chore. It is a huge benefit of the computer vision (ML) - the Internet of Everything (Ot) era to construct expert machines that carry out this work successfully with little human endeavour. This work suggests an Embedded device Fluid ounces suggestion method for efficient water use with little farm involvement. In the agricultural field, IoT sensors are set up to capture important atmospheric and surface data. The obtained information is sent to and stored on a cloud-based server, where machine learning techniques are used to evaluate the information and recommend treatment to the farmers. This recommender system has an internal development process that makes the solution resilient and flexible. The test demonstrates that the suggested method operates admirably on the agricultural dataset from the National Institutes of Technology (Kit) Bhubaneswar as well as the information that we obtained. 2022 IEEE. -
Internet of Things and Cloud Computing Involvement Microsoft Azure Platform
The rapid advancement of cloud technology has resulted in the emergence of many cloud service providers. Microsoft Azure is one among them to provide a flexible cloud computing platform that can scale business to exceptional heights. It offers extensive cloud services and is compatible with a wide range of developer tools, databases, and operating systems. In this paper, a detailed analysis of Microsoft Azure in the cloud computing era is performed. For this reason, the three significant Azure services, namely, the Azure AI (Artificial Intelligence) and Machine Learning (ML) Service, Azure Analytics Service and Internet of Things (Io T) are investigated. The paper briefs on the Azure Cognitive Search and Face Service under AI and ML service and explores this service's architecture and security measures. The proposed study also surveys the Data Lake and Data factory Services under Azure Analytics Service. Subsequently, an overview of Azure Io Tservice, mainly Io THub and Io TCentral, is discussed. Along with Microsoft Azure, other providers in the market are Google Compute Engine and Amazon Web Service. The paper compares and contrasts each cloud service provider based on their computing capability. 2022 IEEE. -
Internet of Things and Blockchain in Healthcare: Challenges and Solutions
The Internet of Things (IoT) enables Internet-connected devices to transmit data to private blockchain networks, allowing for the creation of tamper-resistant documents with shareable exchanges. IoT blockchain technology enables you to communicate and connect IoT data with key stakeholders, while avoiding the need for extensive management and control. Each transfer can be checked to ensure there are no disagreements and to build trust in the network. Blockchain technology protects data from being changed, restricts access to Internet-connected devices, and allows vulnerable IoT devices to be shut down. Blockchain encryption eliminates the possibility of someone overwriting existing data records. In addition, storing IoT data on the blockchain adds an extra layer of security, preventing malicious attackers from accessing the system. The many blockchain IoT firms provide significant value in revolutionizing company operations and daily routines. IoT blockchain firms demonstrate the possibility of blockchain and IoT integration. For instance, Helium is a successful blockchain IoT company specializing in securing Internet connections. This chapter presents the vital role of the Internet of Things and blockchain in the healthcare domain. The integration of blockchain technology in the healthcare industry has given us a chance to solve some problems with IoT networks. In recent years, the need for blockchain-enabled IoT transactions has become an essential technology that will change how users share data. A scenario has been developed to enhance this study to analyse the integration, need, and obstacles associated with blockchain-enabled IoT transactions in the healthcare area. As a result, there is also an IoT model designed using devices for hospitals that take into account all of these people and their needs and the office space where they work. The Author(s), under exclusive license to Springer Nature Switzerland AG. 2024. -
Internet of Things (IOT) based information collection system for efficient production in large scale industries /
Patent Number: 202141046347, Applicant: Arumugam Ranjith.
A system for automatically collecting data on the traceability of duck products was developed in response to the difficulties inherent in the processing of duck products, including complicated technology, difficult data collection and linking, and a scarcity of specialized data collection equipment. This system was created in response to the difficulties encountered during the duck product processing process. Among the difficulties were complicated technology, difficult data collection and linking, and a lack of specialized data collection equipment. -
Internet of Things (IoT) as a Game Changer to the Education Sector
This study examines the use of internet of things (IoT) technology in the field of education, concentrating on its uses, advantages, and difficulties. The current educational system frequently fails to provide individualized learning opportunities since it is characterized by traditional classroom settings and teacher-centered learning. But the emergence of IoT and its companion technologies, including big data, artificial intelligence, and network communication, offers fresh chances to transform education. The IoT architecture in the education sector is covered in the opening section of the paper, with an emphasis on the function of IoT devices in building a networked environment. These tools, such as smart HVAC (heating, ventilation, and air conditioning) systems, make it easier to gather and analyze enormous volumes of data. Institutions of higher learning can get important insights and create individualized learning strategies, thanks to the integration of big data and artificial intelligence. The report also examines a variety of IoT uses in education. It emphasizes the importance of IoT in remote learning, which has become more popular recently. It also demonstrates how the internet of things has influenced the development of smart campuses with interactive whiteboards and other IoT gadgets. The importance of personalized learning in contemporary education is also discussed, with IoT acting as a catalyst for experiences that are specifically suited for students. The study also looks at how IoT might benefit students with disabilities and improve staff and student health monitoring. The use of augmented reality and virtual reality tools in teaching is also investigated. The study explores Edutech-based IoT solutions, concentrating on their function in the processes of teaching, learning, and evaluation. It examines management and government initiatives on both a national and international scale, including those from Ireland's Future Schools, Jharkhand's DigiSAT, and Assam's online job advisory portal. The Kajeet Smart Bus, C-Pen, and Ipevo VZ-X Wireless Document Camera are just a few examples of IoT deployments in education that are highlighted in the study. These instances highlight the concrete contribution of IoT to improving educational practices. IoT tools are also examined in relation to several educational contexts, such as primary, secondary, and higher secondary education. The study also examines the distinct needs of special schools and universities and emphasizes the importance of IoT in STEAM teaching at the university level. The chapter discusses the advantages, disadvantages, possibilities, and difficulties that players in the education sector would have when implementing IoT. It highlights how crucial it is to take advantage of the capabilities of big data, artificial intelligence, and network communication to enhance teaching and learning results. The article also highlights problems with the research and suggests potential fixes, noting areas that could use more investigation. This chapter's conclusion highlights the IoT's disruptive potential in the field of education. Education can be revolutionized by integrating IoT devices, utilizing big data and artificial intelligence, and utilizing network communication. It makes it possible to create individualized, engaging, and data-driven learning experiences that get students ready for the digital era. 2024 selection and editorial matter, Alex Khang, Vugar Abdullayev, Vladimir Hahanov and Vrushank Shah; individual chapters, the contributors. -
Internet of Senses: immersive eating and traversing into the metaverse
[No abstract available] -
Internet of healthcare things: Machine learning for security and privacy
The book addresses privacy and security issues providing solutions through authentication and authorization mechanisms, blockchain, fog computing, machine learning algorithms, so that machine learning-enabled IoT devices can deliver information concealed in data for fast, computerized responses and enhanced decision-making. The main objective of this book is to motivate healthcare providers to use telemedicine facilities for monitoring patients in urban and rural areas and gather clinical data for further research. To this end, it provides an overview of the Internet of Healthcare Things (IoHT) and discusses one of the major threats posed by it, which is the data security and data privacy of health records. Another major threat is the combination of numerous devices and protocols, precision time, data overloading, etc. In the IoHT, multiple devices are connected and communicate through certain protocols. Therefore, the application of emerging technologies to mitigate these threats and provide secure data communication over the network is discussed. This book also discusses the integration of machine learning with the IoHT for analyzing huge amounts of data for predicting diseases more accurately. Case studies are also given to verify the concepts presented in the book. 2022 John Wiley & Sons Ltd. All rights reserved. -
Internet chat based intervention as a mode for therapy and counselling
Increasing mental health issues in India demands for a strong intervention to curb the rise. According to the World Health Organization, roughly around 21 Indians out of 100,000 die by suicide every year. The burden on mental health domain increases due to the existing system as most of the existing services follow a traditional approach and are most sought after but lack reachability and ease of access. This study recognises the need for programmes that help in reachability and ease of access while simultaneously maintaining anonymity, therefore, analyses the impact of chat-based therapy provided online through the platform. The paper analyses the difference in subjective unit of well-being (SUW) pre and post chat-based sessions among 2624 college students and 805 corporate employees. The Wilcoxon signed rank test between pre and post intervention indicates significant results with the p < 0.001 (Z = -44.100a) suggesting and increase in SUW scores post intervention. Further, the Kruskal-Wallis test revealed that the gender of the clients has an association with the SUW scores (p < 0.05). It was also found that the duration of the sessions had a positive relation with the impact scores (p < 0.001). The Author(s), 2025. -
International multi conference on computing, communication, electrial & nanotechnology /
Materials Today Proceedings, Vol.11, Issue 3, pp.889-115, ISSN No:2214-7853. -
International Journal of Operational Research: a retrospective overview between 2005 and 2020
The study presents a retrospective analysis of the International Journal of Operational Research (IJOR) across its 16 years of publication, 2005 to 2020. IJOR is a journal of international repute that publishes original and peer-reviewed research in the management sciences, decision sciences, and operation research domain. The journal reached its 17th year of publishing in 2021. This study provides a comprehensive overview of 1,023 publications using the bibliometric data analysis technique. The study focuses on the contribution of IJOR to the knowledge domain through publishing trends, authorship patterns, dominant authors, prominent articles, nature of studies, and thematic analysis. Co-occurrence analysis of all keywords, co-authorship, citation and co-citation analysis of authors, countries, and institutions is performed through VOSviewer software. The findings of the study emphasise the relationship of IJOR to different fields. 2024 Inderscience Enterprises Ltd. -
International Journal of Logistics Systems and Management (20042020): an analytical retrospective
International Journal of Logistics Systems and Management (IJLSM) is a journal of international repute that publishes original and peer-reviewed research in the business, management, accounting, and decision sciences domain. The journal reached its 18th year of publishing in 2021. This study provides a comprehensive overview of 962 publications using the bibliometric data analysis technique. The study focuses on the contribution of IJLSM to the knowledge domain through publishing trends, authorship patterns, dominant authors, prominent articles, nature of studies, and thematic analysis. Cooccurrence of all keywords, co-authorship, citation and co-citation analysis of authors, countries, and institutions is performed through VOS viewer software. The findings of the study emphasise the relationship of IJLSM to different fields. The analysis also provides key insights into the evolution of the domain over time. 2024 Inderscience Enterprises Ltd.