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Assessment of Enablers for Adoption of Blockchain Technology in the Indian Hospitality Industry
Purpose The chapter attempts to analyse various enablers for implementing blockchain technology in the Indian hospitality sector and examine the appropriate set of facilitators through the causal interactions among the enablers. Design/methodology/approach To analyse the enablers for the adoption of blockchain, the tool used is the decision-making trial and evaluation laboratory (DEMATEL), which captures the judgements provided by the experts in the field for the cause-and-effect enablers and the interaction effect among these enablers. Findings The literature suggests fifteen enablers classified into cause-and-effect enabler groups and interactions (i.e., enabling and enabled) among each blockchain adoption practice. The study reveals a reduction in cost and transparency as the most significant cause enablers and the effect variables as trust and database security. Research limitations/implications The results generate various enablers that can be focused upon for bringing out various significant interventions in the field. The study, however, provides an understanding of the enablers for this specific industry in the Indian context. Practical implications The results may be useful for devising policies and managerial implications related to adopting blockchain technology in the hospitality sector. Originality/value Very few researchers have integrated the role of grey DEMATEL techniques in the hospitality industry. 2024 selection and editorial matter, Park Thaichon, Pushan Kumar Dutta, Pethuru Raj Chelliah and Sachin Gupta; individual chapters, the contributors. -
Demand Forecasting Methods: Using Machine Learning to Predict Future Sales
To thrive in the market today, businesses must increase the effectiveness, dependability, and accessibility of their services. Sales estimation and operative demand scheduling definitely impact the end result of the organizations, influencing their procurement process, production, delivery, supply chain, marketing communications, etc. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
A Multilayered Feed-Forward Neural Network Architecture for Rainfall Forecasting
The amount of rain received in a particular demographic region in a given time interval is called the rainfall. Rainfall is a natural and complex process and has significance in different domains including agriculture, transport, disaster management, and natural calamities resilience [1]. Abnormal rainfall affects every facet of humans and all other living beings of the world and also has a great impact in wellbeing and financial disruptions of a country. Accurate rainfall predictions at regular time intervals are always important to issue warnings about likelihood of any disaster about to happen. This also provides people a time for strategic planning in their work and precautions at time of adversity [2]. It is worth noting that rainfall forecasting does not only have an impact in day-to-day life, but more importantly for tropical countries like India where the chief occupation being agriculture and also for various other industries. It largely helps in disaster management and recovery process as well. The rainfall being a variable over time, geography and atmospheric conditions makes the forecasting considerably difficult [3]. Rainfall forecasting keeps a person informed about the likelihood of rainfall the forthcoming day, week, or month which enable long-time planning and on the other way; hourly prediction helps for shortterm planning such as enforcing traffic measures. Literature has seen various studies in this domain using predictive machine learning (ML) algorithms such as neural networks (NNs), Genetic algorithms, and Fuzzy-based systems [4]. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
Genetic Algorithms for Wireless Network Security
[No abstract available] -
Analysis and Prediction of Suitable Model for Coconut Production Estimates in South Indian States
The study attempts to forecast coconut production in major coconut-producing states in India. The future projections on coconut production have been calculated based on yearly data for 73 years (194950 to 202122) accessed from the database of Indiastat (2022). We have used prominent forecasting techniques for the purpose and a suitable model has been chosen based on the lowest results of MAPE. The damped linear trend has been chosen for forecasting coconut production in Karnataka whereas Differenced first-order Auto Regressive model with drift has been adopted for Kerala and Karnataka. This study has considered a large dataset compared to other existing works and has chosen states that produce coconut on a large scale in India. Along with this, this study also attempts to find which state will produce more nuts for the Indian coconut industry, which can help the concerned stakeholders to take necessary decisions. Future projections depict that Kerala will continue to be the largest producer of coconut and Karnataka will show remarkable performance in coconut production during the upcoming four years post-study period. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Augmented Reality-Enabled IoT Devices for Wireless Communication
[No abstract available] -
Agricultural Internet of Things (AIoT) Architecture, Applications, and Challenges
The internet of things (IoT) is a system that involves adding sensors, software, and network connectivity to physical devices, enabling them to collect and exchange data. This technology has the potential to bring significant advancements to various sectors, including agriculture. In farming, the agricultural internet of things (AIoT) utilizes IoT to improve efficiency, sustainability, and productivity. Through the real-time collection and analysis of data, AIoT can optimize growing conditions, prevent diseases and pests, and ultimately increase crop yields. By monitoring factors such as soil moisture, temperature, and nutrient levels, AIoT technology can effectively track crop health and detect potential issues in advance. In this way, AIoT technology is helping farmers to make more informed decisions and take more effective actions to improve crop yields, reduce waste, and lower costs. AIoT in agriculture finds practical applications in smart irrigation systems, precision agriculture, livestock monitoring systems, and climate control systems. Smart irrigation systems utilize weather data and soil moisture sensors to efficiently manage water consumption. Precision agriculture employs sensors and data analysis techniques to optimize planting, fertilization, and pest control practices. Livestock monitoring systems aid in monitoring and managing the well-being of farm animals. Climate control systems utilize AIoT to regulate and optimize environmental conditions for crops and livestock. Livestock monitoring systems use sensors to track the health and well-being of animals. Climate control systems for greenhouses and barns use AIoT devices to monitor temperature, humidity, and other environmental factors to optimize growing conditions. Sensors can be used to monitor various environmental factors in a farm, by connecting the sensors to a cloud-based platform for storing and analyzing data. The wireless sensor networks can be used to calculate the dew point on leaves and adjust the greenhouse environment to prevent and control plant diseases. Drones equipped with sensors, cameras, and other imaging technology can also be used to monitor crop conditions, as this allows farmers to take proactive measures to address these issues, preventing crop loss and reducing the need for pesticides and other chemicals. IoT/sensor nodes are vital components in precision agriculture as they gather real-time data. Integrating data analytics and machine learning into the agricultural system improves its practicality and efficiency. Real-time data availability enhances precision in agriculture, and combining data analytics with this information leads to notable progress in the field. However, AIoT technology is gradually advancing in agriculture, but there is a need for a more rigorous research approach in this area. Additionally, the current literature lacks coherence and solid research on the interconnectedness of technology and agriculture. 2024 selection and editorial matter, Alex Khang, Vugar Abdullayev, Vladimir Hahanov and Vrushank Shah; individual chapters, the contributors. -
From bean to brain: Coffee, gray matter, and neuroprotection in neurological disorders spectrum
Coffee is a popular drink enjoyed around the world, and scientists are very interested in studying how it affects the human brain. This chapter looks at lots of different studies to understand how drinking coffee might change the brain and help protect it from neurodegenerative disorders especially like schizophrenia. With the help of available literature a link between the coffee mechanism and neurodegenerative disorders is established in this chapter. Researchers have found that drinking coffee can change the size of certain parts of the brain that control things like thinking and mood. Scientists also study how coffee's ingredients, especially caffeine, can change how the brain works. They think these changes could help protect the brain from diseases. This chapter focuses on how coffee might affect people with schizophrenia as hallucination is caused during and after excess consumption of caffeine. There's still a lot we don't know, but researchers are learning more by studying how different people's brains respond to coffee over time. Overall, this chapter shows that studying coffee and the brain could lead to new ways to help people with brain disorders. This study also draws ideas for future research and ways to help people stay healthy. 2024 Elsevier B.V. -
Evaluation of Consumer Experiences by Extended AIDUA Framework in the World of the Metaverse the Future of Next-Gen Hospitality
The hospitality industry is continuously exploring novel ways to enhance consumer experiences, and the advent of the metaverse presents exciting prospects for transforming guest interactions. The metaverse can provide an immersive, 3D social experience of a virtual world by using technologies like virtual reality and augmented reality, which helps bridge the gap between the real and virtual worlds. This study explores consumer experiences in the metaverse in the hospitality context. Using the extended AIDUA (artificial intelligence device usage acceptance) model, the research aims to comprehensively analyze customers willingness to accept the metaverse in the dynamic digital landscape. The objective of this study is to investigate how the metaverse revolutionizes consumer experiences in the hospitality sector, specifically in the context of room and amenity booking, in-house events, and virtual tours. In this study, a three-step cognitive appraisal process with utilitarian motivation and the attitude of the customers that determines customers willingness and objection to utilizing AI devices is evaluated through secondary data. The metaverse empowers guests to optimize in-house event participation, seamlessly navigate their stay through taking a virtual walkthrough to explore a higher-end suite, and touring the city virtually. Practical implications for industry practitioners and researchers seeking to exploit the potential of the metaverse to create an immersive and unforgettable consumer experience in the ever-evolving landscape of hospitality are explored in this chapter. 2024 selection and editorial matter, Park Thaichon, Pushan Kumar Dutta, Pethuru Raj Chelliah and Sachin Gupta; individual chapters, the contributors. -
Forecasting the Stock Market Index Using Artificial Intelligence Techniques
If the stock market would have a predictable to maximum accuracy, then every stockbroker and investor would have been billionaire. But it is not the ground truth. In a one-to-one interaction with stock analysts, who mention that the stock market is unpredictable and that is why their role is important, else everything would have been black and white. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
Business Forecasting and Error Handling Using AI
Business forecasting is the technique of accurately predicting the future of a business and outcomes using historical data and present trends. To evaluate historical data and find patterns, trends, and other elements that might be used to forecast future events, a variety of analytical tools and techniques are used. Business forecasting is a crucial component of strategic planning because it enables businesses to foresee market changes, spot possible risks and opportunities that may arise in the future, and make wise resource allocation and investment decisions. Businesses that use effective business forecasting can plan and carry out their programs that help them stay competitive, expand their operations, and meet their objectives. According to Glueck [1], Forecasting is a formal process of predicting future events that will significantly affect the functioning of an enterprise.. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar. -
Genetic Algorithms for Graph Theoretic Problems
[No abstract available] -
Portfolio Management Decision Support System Using Cryptocurrencies and Traditional Assets in Indian Context
The paper attempts to develop a portfolio management decision support system (PMDSS) to help the investors to ensure portfolio optimization in Indian context. For this, the study conducts a comparative analysis between portfolios with equities from Indian market and portfolios that includes cryptocurrencies along with equities. Considering the huge hype received by cryptocurrencies in the current scenario, we attempt to diversify portfolios by including risky assets like cryptocurrencies, specially focusing from Indian perspective. Till now, Portfolio Optimization with Monte Carlo Simulation and Hierarchical Risk Parity has not been implemented by combining portfolios of cryptocurrencies and Indian stocks together. Traditional assets for the study are selected upon their market capitalization, Earnings Per Share, Profit margin, Operating profit etc. and cryptocurrencies are chosen according to their market capitalization. Data on the daily prices of these assets are collected from 201920 to 202122. An attempt is made to optimize the portfolios by minimizing the portfolio standard deviation and maximizing the portfolio expected returns. This helps to minimize risk and maximize the possible returns that might arise from the portfolio after adjusting for the volatility of the asset classes respectively. Based on the results, we suggest not to incorporate cryptocurrencies in portfolios with Indian stocks. This is because the risk adjusted returns of cryptocurrencies are comparatively lower as compared to the other under study. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
The Accountability of Stakeholders in Combating Domestic Violence with Women in India
As per the Hindu tradition, women are considered as ardhangini and the western civilisation considers them as better half. Since ancient times, women have been considered as the epitome of love, kindness, care and above all the mother of mankind. But on the contrary, the most terrible and horrifying cruelties are imposed upon her. The predominant type of violence which is inflicted upon a woman is domestic violence also known as intimate partner violence. According to the World Health Organisation, almost one third, i.e., 27% of the women aged between 15 and 49 years, who have been in a relationship report that they have been subjected to some form of physical or sexual violence by their intimate partner. The issue of domestic violence has been addressed at both international and national levels, but still there exists a persistent gap in enforcing and implementing them. And this can be easily proved from the continuous rise in the cases of domestic violence worldwide, especially during the COVID times. The problem that needs to be addressed at hand is the role of several accountable stakeholders involved in the process of providing access to justice to the women affected by domestic violence. According to the Protection of Women from Domestic Violence Act (2005), in India, the several stakeholders include the protection officers, service providers, lawyers, police officers, shelter homes and judges. These are the people with whom the power to protect and help the women are vested, but instead the affected women fall a prey to this system due to various reasons like lack of resources, fewer power and many more which will be further discussed in the article. 2024 selection and editorial matter Dr. Shilpi Sharma and Baidya nath Mukherjee; individual chapters, the contributors. -
Artificial Intelligence for Bio-Inspired Security
[No abstract available] -
Ant Colony Systems- Enabled Wireless Network Communication
[No abstract available] -
Ind as convergence and its impact on value relevance of accounting variables
This study investigates the correlation between accounting variables and stock prices in India from 2011 to 2022, emphasizing the impact of the Convergence of Ind AS with IFRS. Specifically, it explores how this convergence influences the value relevance of accounting data using the Ohlson Model. Beyond established vari-ables like Earnings per Share (EPS) and Book Value (BPS), the analysis introduces additional factors such as Dividend per Share (DPS) and Research and Development (R&D). Employing Ohlsons Pricing Model (1995), the research assesses the rela-tionship between these accounting variables and stock prices for 47 consistently listed firms in the NIFTY 500 index. Results show that DPS and R&D enhance the value relevance of the Ohlson Model, with the adjusted upper R squaredupper R squared increasing from 0.2 in 2011 to 0.6 in 2022. While overall value relevance improves after Ind AS convergence, BPS remains consistent when controlling for EPS. The Author(s). -
IoT Security with Blockchain Technology in the Financial Sector
Blockchain technology is to create immutable device IDs to stop identity faking whereas Internet of Things (IoT) is used in payment automation and to create smart payment systems. Both are evolving technologies, and their integration offers promising results in financial sector across the globe. Their combination holds a great deal of potential and is going to represent the next generation of smart finance technologies. But the major weaknesses that are present in IoT technologies includes those related to data security, privacy, device authentication, secure communication, and smart contract administration. This chapter focuses on the use of blockchain networks to regulate access and improve security in financial transactions, boost automation and improve efficiency of IoT applications. Blockchain and IoT integration in the financial industry provides a pathway to a more integrated, efficient, and secure financial environment. The chapter discusses the advantages of integrating IoT and Blockchain technologies in the financial sector and the challenges in its applications, and the regulatory mechanism thereof. 2025 Taylor & Francis Group, LLC. -
Occupancy Monitoring to Prevent Spread of COVID-19 in Public Places Using AI
The chapter aims to automate the counting of people for occupancy monitoring and send an alert email if the occupancy exceeds the defined threshold in case of restricted occupancy guidelines. The study aims to reduce the manual error, effort, and time for people counting and provide a tool for footfall analysis. We propose and implement an occupancy monitoring system by counting the number of people entering and exiting a building/room using cameras and machine learning (ML) algorithms. The Single Shot Detector (SSD) algorithm, which is based on the MobileNet architecture, is used. This project provides an effective process for execution using either a recorded video file or a live stream from a camera. As the system automates counting people, it reduces human effort and error. It provides accurate results on time. The project can be implemented anywhere using a laptop and a camera for capturing the video. Thus, it provides high portability of the project. The system can leverage pre-installed CCTV cameras and systems in colleges, malls, offices, etc. Thus, it requires less additional expenses and is economically friendly for the organization/decision-making authority. This chapter includes implications for various use cases such as ensuring adherence to COVID-19 guidelines by organizations, streamlining janitorial services, prevention of stampedes, improving indoor air quality, improving electricity efficiency, etc. This project fulfills an identified need to automate the people counting process and generate alerts accordingly. 2025 by Apple Academic Press, Inc. -
Smart production monitoring using drones in cyber-physical agricultural systems
The population of the world has shown a notable swift in recent years and the need for food has also gradually increased. The extra demand could be met by smart agricultural systems because manual and traditional crop cultivation is tedious, time-consuming and requires manpower to a great extent. The increased population is not the only factor for the shortage of food; there are many other influencing factors involving crop damage due to insects, lack of monitoring, and many others that should be overcome by the implementation of smart technologies in agriculture and resulting in a revolution of the agriculture or it can be addressed as Agri 4.0. This chapter provides insight into the implementation of drone technology which will result in many positive shifts in Agri 4.0. To address the various associated problems, causes, and consequences in the production, the smart production system with the incorporating technologies shows the notable solutions. Through the underlying chapter, the need, usage, architecture, implementation, and other related aspects are discussed. 2024 Elsevier Inc. All rights reserved.