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Agricultural nanotechnologies: Future perspectives of bio-inspired materials
Bio-inspired designs have been used by humankind in understanding and modelling novel materials which have applications in diverse fields like disease diagnostics, drug delivery, agriculture, energy storage, industry, etc. Superhydrophobicity, directional adhesion, structural colour, self-cleaning, antireflection, etc. are some of the useful attributes for which we have relied a lot on nano level biomimetics. Bioinspired nanolevel designs have been explored in the field of agriculture too. Such nanomaterials and nanodesigns have been used to increase crop yields. They also find uses in fertilizer application and replacement of many harmful chemical pesticides, which are generally overused. Increasing population, increased longevity of people and the urgent need for sustainable environment have led to a dire need for exploration and adaptation of such novel technologies which can help in feeding the growing population. Nanoscale products and technologies can also help in reducing the accumulation of excess fertilizers, pesticides, etc. in soil, which can go a long way in cleaning up the environment. The current attempt is intended to portray the latest developments and future possibilities of bioinspired NT in diverse fields of agriculture like synthesis and delivery of novel pesticides and fertilizers, nanocarriers for gene delivery, sensors to monitor and assess soil conditions, plant pathogen detection and plant nanobionics to detect pollutants. 2023 Bentham Science Publishers. All rights reserved. -
Agricultural waste valorisation Novel Areca catechu L. residue blended with PVA-Chitosan for removal of chromium (VI) from water Characterization, kinetics, and isotherm studies
Arecanut, an industrial crop prevalent in tropical regions such as India, Sri Lanka, and parts of Southeast Asia, generates significant agricultural waste during processing. This study explores a waste-to-wealth approach by incorporating arecanut organic residue into Polyvinyl alcohol (PVA) - Chitosan blends via an eco-friendly continuous stirring method to develop an adsorbent film for removing chromium (VI) from water. Morphological analyses confirmed enhanced surface area, porosity, and roughness in the blended films. XRD and FTIR analyses indicated a semi-crystalline nature with a decrease in the characteristic peak intensity of PVA and chitosan, confirming the incorporation of arecanut residue. Optimal conditions identified OR-4 film, using 0.4 g of adsorbent, achieving 88.68 % removal of 173 mg/L chromium (VI) at pH 9.0, within 45 minutes at 40C. SEM images demonstrated significant surface roughness reduction before and after adsorption, confirming chromium adsorption. Kinetic studies revealed a pseudo-second-order model and adsorption isotherms confirmed film surface heterogeneity. This research advances eco-friendly materials for water purification and offers a sustainable solution for managing agricultural residues. 2024 Elsevier B.V. -
Agriculture 4.0 and smart farming: Imperatives of scaling up innovation and farmer capabilities for sustainable business
Smart agriculture adoption during industry 4.0 is creating new scenarios to farmers across the world. Smart farming promotes not only an increase in the agricultural productivity and incomes, but also building resilience to climate change. Small business farmers had to look at all possible means to cope with the technology applications for implementation of agro-transformation agendas for improved production and business performance. Smart farmers have to make use of several technology applications like drones and satellites, IoT (Internet of Things) based sensors, block chain and big data, biotech, farm maintenance technology (optimising water usage, production, and innovation technology) for better agricultural practices. Though such aggrotech opportunities have demonstrated business improvements, how far such smart farming revolution is well received by the agribusiness owners are less researched into. Henceforth, the purpose of this research is to establish the relationship between aggrotech innovation capabilities and farmer's capabilities associated with agriculture firms and its contributions to business performance. Following cross-sectional descriptive study design, and purposive sampling, the study addressed 3 direct and 2 indirect relationships in the model, on 212 farmers. The data was collected from Selangor state of Malaysia. The study applied Smart PLS SEM to analyse the data. The results show that the innovation (technology) capability and farmer's (people) capability have a positive relationship on business performance. The study also shows the partial mediation effect of technology change on innovation capability and business performance as well as employee capability and business performance. The study is novel in its form by applying Resource Based View theory on Smart agriculture, extending possibilities of generalization agriculture sector. 2021 Ecological Society of India. All rights reserved. -
Agriculture as a means of alleviating rural poverty: Pursuant to the sustainable development goal-1
Poverty is one of the worst problems prevailing in the world. The poorest in the world are often without food, have little or no access to education, basic amenities of life, and lack health facilities. Eradication of Global Poverty eradication is a herculean and complex task. The origination of 2030 Agenda to eradicate poverty was done after the successful completion of the anti-poverty Millennium Development Goal, but still, a vast number of people were living in poverty and a great number among them were living in extreme poverty. So, the 2030 Agenda for Sustainable Development called for the eradication of poverty in all poverty in forms from every corner of the world by almost half. In backward and developing nations, poverty is more rampant in rural areas. The economies of most of these nations are predominantly based on Agriculture and therefore progress in agriculture is viewed as a potent tool to eradicate rural poverty. However, there are serious issues that are required to be addressed in this regard. This chapter explores some vital issues related to agriculture which require the attention of the policymakers, to achieve the objective of reducing rural poverty through advancement in agriculture. 2023 Nova Science Publishers, Inc. All rights reserved. -
Agriculture water purifying device /
Patent Number: 363685-001, Applicant: S Nithyananthi. -
Agro-food traceability with efficient user interface using blockchain technology
Food traceability is crucial for food quality and safety to reduce vulnerabilities of product globalization. The traditional Agri-food production system does not offer easy traceability of the product at any point of the supply chain. Blockchain based production system resolves the challenges by reducing the complexity of traceability. Still no other study has presented Blockchain-based traceability platform with a lower impact on the environment and lower cost for each transaction sent by the supply chain. In the existing system, proof of work consensus protocol is used in blockchain which consumes more energy for transactions. The proposed traceability system is based on Ethereum Blockchain, which uses the Proof-of-Stake mechanism of consensus that requires minimal computational power, is highly scalable and environmentally sustainable. The user interface of consumer is specially designed that provides all the tracking information of the agro-food. The developed traceability platform digitizes the entire production chain making the data immutable and available in realtime. 2024 by IGI Global. -
Agroecological transformation through farmers' empowerment and IP reform: A human rights-based approach
The transition to agroecology is essential for achieving sustainable food systems, biodiversity conservation, and climate resilience. However, dominant intellectual property (IP) regimes often marginalize small-scale farmers by restricting seed sovereignty and traditional knowledge systems. By recognizing farmers' rights to seeds, knowledge, and fair market access, IP policies can shift from corporate-driven monopolization to collective stewardship models. The chapter advocates for a multi-stakeholder approach that integrates legal, economic, and ecological dimensions, ensuring that farmers' empowerment is at the core of agroecological transitions. By embedding human rights in IP governance, policymakers can foster more just, resilient, and biodiversity-rich food systems, ultimately advancing the global movement for agroecological transformation. This chapter argues that a human rights-based approach to IP reform can empower farmers as key agents of agroecological transformation. 2025, IGI Global Scientific Publishing. All rights reserved. -
Ahead of 2026 election, how can DMK retain credibility and control the narrative?
The path to Fort St. George lies as much through governance as through the peoples imagination. And in that realm, the verdict is never final -
AI and Big Data Analytics for Management of Nutraceuticals
This chapter explores the transformative impact of artificial intelligence (AI) and Big Data Analytics on nutraceutical management. As consumer demand for health-focused products such as supplements, functional foods, and herbal extracts grows, ensuring quality, safety, regulatory compliance, and personalization remains challenging. AI enhances formulation and quality assurance through predictive modeling and computer vision, while analyzing individual health data for personalized nutrition. Concurrently, Big Data leverages vast datasets from clinical trials to consumer feedback to forecast market trends, segment consumers, and guide R&D. The integration of AI and Big Data fosters deeper insights, driving innovation, safety, and tailored solutions. However, challenges like data privacy, standards, and ethics persist. Future developments may include AI-driven discovery of bioactives, real-time supply chain monitoring, and blockchain-based transparency. Embracing these innovations is essential for advancing safer, more effective, and personalized nutraceuticals that promote public health. Springer Nature Switzerland AG 2026. -
AI and Big Data: Harnessing Data Science for Enhanced Consumer Insights
Data science is revolutionizing modern marketing strategies. These strategies enhance consumer intelligence and streamline decision-making processes. Data science techniques are helping businesses to get deep insights into consumer behavior, preferences, and emerging trends. In this paper, we focus on how the trident of artificial intelligence, machine learning, and quantum computing is reshaping marketing practices. Additionally, we focus on how artificial intelligence, machine learning, and quantum computing will impact data processing capabilities in future. The paper emphasizes the need for responsible data practices and discusses ethical issues such as data privacy and algorithmic bias. Several case studies focused on personalized marketing to improve customer satisfaction for companies like Netflix, Amazon, and Spotify are used. The findings suggest that businesses aiming to stay competitive will need to integrate data science in the complex data-driven world. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
AI and Data Science: Transforming the Education Landscape
Artificial Intelligence (AI) and Data Science are revolutionizing the education landscape by providing innovative solutions for personalized learning, assessment, and administration. AI algorithms analyze vast amounts of educational data to identify student learning patterns, enabling tailored learning experiences that cater to individual needs. With predictive analytics, educators can identify at-risk students early, allowing for timely intervention and support. Moreover, AI-powered tools help streamline administrative tasks, freeing up teachers to focus more on instruction and less on paperwork. Data science also enables institutions to assess curricular effectiveness, ensuring continuous improvement of programs. As AI technologies evolve, they hold the potential to create a more engaging, adaptive, and efficient learning environment for all students, regardless of their backgrounds. 2026, IGI Global Scientific Publishing. All rights reserved. -
AI and data-driven digital platforms: the case for establishing global minimum standards in competition law
AI and data-driven platforms have the potential to enable foreclosures, exclusionary and exploitative practices, resulting in the distortion of competition in the digital markets. The inherent conundrum of boundary-less AI and data-driven systems and territorial application of competition laws has created problems in cross-border digital markets. Countries have adopted divergent approaches in enforcing competition law, with some following the per se rule to categorically prohibit MFN clauses and others employing the rule of reason, assessing the anti-competitiveness of such agreements based on effects. Moreover, the countries have adopted either ex-post or ex-ante or a combination of both to regulate digital markets, deepening the divergence in competition, allowing AI and data-driven practices to enable regulatory arbitrage. To establish divergences in regulating the digital markets, the research adopts a comparative approach, analysing the competition law statutes and case laws across jurisdictions. Although competition laws must duly account for domestic market conditions, bringing harmonisation in their enforcement across jurisdictions remains imperative. Adopting a global minimum standard for competition law is a necessary step towards bringing consistency in the application of the competition laws across countries and equipping the competition law enforcement body to confront AI and data-driven market distortions in cross-border digital platforms. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
AI and human collaboration in tourism: a framework for scalable, authentic, and engaging content
This study examines the effectiveness of AI-generated content in tourism marketing by comparing it to human-generated narratives. While AI enhances scalability and factual accuracy, its ability to replicate emotional engagement and cultural authenticity remains unexplored. Using the Information Quality Framework (IQF), the study employs readability analysis, sentiment analysis, and thematic analysis to assess AI- and human-generated content. AI-generated travel narratives were sourced from large language models, while human content came from tourism blogs and vlogs. Findings reveal that AI-generated content is well-structured and highly readable but lacks emotional depth and trust-building elements. Sentiment analysis shows stronger emotional responses in human narratives, while thematic analysis highlights richer cultural insights. The study proposes a Hybrid AI-Human Collaboration Model, leveraging AI's efficiency with human creativity. These insights contribute to AI ethics, tourism storytelling, and digital marketing, offering practical recommendations for integrating AI into tourism content creation. 2025 Asia Pacific Tourism Association. -
AI and IoT for universal health and well-being across generations
Over the last several years, the confluence of AI and the Internet of Things (IoT) has caused tremendous changes in many areas of our life, including the healthcare industry. Because of this cooperation, new possibilities have emerged with the aim of enhancing the health and welfare of people across all different generations. The ability to efficiently gather, analyze, and derive insights from large volumes of real-time data has revolutionized healthcare, allowing for better patient treatment and community health management. This is made feasible by combining algorithms powered by artificial intelligence with IoT-connected devices. Examining the gamechanging possibilities of AI and the IoT in the healthcare industry is the goal of this introductory piece. The function of AI and the Internet of Things in advancing health equity and wellness across diverse age groups is the primary emphasis of this study. Countless and varied uses of AI and the internet of things may be found in the medical field. Some examples of these uses include remote patient monitoring and the development of predictive analytics tools for use in illness prevention.Health outcomes and quality of life for individuals of all ages can be improved via the development of individualized therapies and treatment programs that cater to each person's specific needs. It is feasible to create these opportunities with the help of these technologies. Healthcare issues may be effectively addressed in a variety of locations, from densely populated cities to more rural places, by implementing solutions that leverage the internet of things and artificial intelligence. Because these solutions are both accessible and scalable, this is the result. It is possible for healthcare systems to overcome barriers to service delivery and access by utilizing these technologies. As a result, people of all ages and from all over the world will be able to live the kind of healthy, fulfilling lives they deserve. 2024, IGI Global. All rights reserved. -
AI and IoT in Digital Marketing: Enhancing Automation, Personalization, and Consumer Interaction
An interconnected system of Internet-enabled devices that can collect and transmit statistics via a wireless connection without the assistance of people is known as the Internet of Things (IoTs). Accordingly, the IoT's seductive power is causing significant shifts in the current corporate environment. The digital marketing industry stands to gain the most from this innovation, which is currently causing major shifts in many other sectors. Using a variety of digital marketing strategies, this innovation gathers numerous types of consumer statistics. IoT technological advancements' impact on digital marketing tactics and customer interaction has emerged as a crucial research topic as it begins to pervade many facets of everyday existence. This investigation examines the application of IoT-based machine learning (ML) in digital marketing for the food business. To give ML-based suggestions, consumer data is analyzed, interests are identified, and conduct is predicted using ML approaches. The ensemble technique aggregates the results of multiple ML techniques to produce an individual forecast. The accuracy matrices graphs for the K-nearest neighbor and decision trees produced excellent estimations, with 100% accuracy and 0.0 error, correspondingly. The nae Bayes method achieved 97.2% accuracy with a 0.029 error, successfully identifying the right tags across every category. The guided ensemble of 3 ML methods is demonstrated by effectively enhancing digital marketing tactics in the food distribution industry by reducing duration and expenses. 2025 IEEE. -
AI and IoT in Improving Resilience of Smart Energy Infrastructure
In todays world, we cant live without energy. Its essential for the growth and development of the economy. Changes in climate, sustainable growth, health, food security for the world, and environmental protection all require it if we are to make any headway. Governments around the world are looking for innovative ways to generate, control, supply, and save energy because of the rising cost and rising demand for it. Photovoltaic systems, hydropower, wind energy, tidal power, and geothermal energy are examples of traditional renewable energy sources that have advanced significantly in recent years. They, however, are unable to deal with environmental variations. It is critical to developing smart and cost-effective generators in order to meet the advanced worlds energy demands. In this chapter, we introduced the concept of smart energy, smart grid, and smart energy systems in a brief manner. Smart energy portfolio and smart energy management are introduced in the frst section. We also discuss how AI and IoT can be used to improve the different energy sources like wind power, solar power, geothermal power, etc. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
AI and Its Impact on the Growth of the Small Medium Enterprises: The Role of IT Service Management (ITSM) in AI Adoption-AI and Sustainable Development Goals (SDGs)
AI in SMEs (Small and Medium- sized Enterprises) refers to the deployment of artificial intelligence technology to develop business operations and competitiveness. Often more resource- constrained than large corporations, SMEs can leverage AI to streamline processes, improve decision- making, and gain a competitive edge. Nowadays technology is changing, and small businesses are making profit. For building resilient business models with AI, it helps to get more information about business models, the amount to be invested in business, products demanded by the customers and the level of risk capacity to be taken by a firm.AI helps in generating new skills and knowledge in the employees by giving personalised training and coaching. Empowering SMEs through data- driven decision making helps in making rational business decisions based on data rather than relying on intuition or observation. It helps making faster decisions, improving operational efficiency and understanding the value of data. 2026 by IGI Global Scientific Publishing. -
AI and Machine Learning Applications in Predicting Energy Market Prices and Trends
The worldwide energy market is intricate and unstable, shaped by several aspects including geopolitical occurrences, supply-demand variations, and regulatory modifications. Precisely forecasting energy prices and trends is essential for stakeholders, such as energy producers, dealers, and policymakers. This study investigates the utilization of artificial intelligence (AI) and machine learning (ML) to improve energy price forecasting models. Conventional forecasting methods frequently fail to account for the dynamic and non-linear characteristics of energy markets; however, AI/ML techniques, including neural networks, decision trees, and reinforcement learning, provide enhanced prediction precision. By including external variables such as meteorological conditions and economic metrics, AI models can produce more accurate and useful insights. Case studies illustrate the effective implementation of AI in energy markets, showcasing its capacity to surpass traditional methods. This article addresses difficulties such as data quality and computing expenses while delineating potential developments in AI-driven energy market forecasts. The Authors, published by EDP Sciences. -
AI and Machine Learning Enabled Software Defined Networks
The telecommunications industry has not been exempt from the technology sectors massive artificial intelligence (AI) and machine learning (ML) boom in recent years. Artificial intelligence (AI) and machine learning (ML) provide advanced analytics and automation that are in line with modern networking concepts like software-defined networking (SDN) and software-defined wide-area networks (SD-WAN). Work is being done to determine how AI/ML can benefit SD-WAN and to demonstrate these benefits in a real SD-WAN network using a workable example. Modern ML techniques and algorithms are the extent of AI/ML. Todays Internet is under constant threat from DDoS (Distributed Denial of Service) attacks. As the volume of Internet traffic grows, its getting harder and harder to tell whats legitimate and whats malicious. The DDoS attack was detected using a machine learning approach that makes use of a Random Forest classifier. To better detect DDoS attacks, we tweak the Random Forest algorithm. The proposed machine learning approach outperforms, as demonstrated by our results. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
AI and Multimedia Integration for Smart Mining and Renewable Energy Sustainability
This chapter focuses on how Artificial Intelligence (AI) and multimedia technologies are used to encourage sustainable smart mining and renewable energy optimization. AI boosts the accuracy in planning energy, smart grid use and supporting the management of demand, which saves money. The use of AI, predictive maintenance, geospatial analytics, and real- time monitoring in mining ensures optimisation of resource extraction and insignificant impacts on the environment. The research is powered by the international case studies and the initiatives of the private sector and points out the transformational impact AI can and is making in the sphere of operational efficiencies and sustainable industrial development in the spheres of energy and mining industries. 2026 by IGI Global Scientific Publishing. All rights reserved.