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Permanent URI for this collectionhttp://192.168.24.11:4000/handle/123456789/237
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Item Can AI and IOT Rescue India from its Own E Waste Crisis or Will We Just Have Smarter Trash?(MJS PUBLISHING HOUSE, 2025) Tulika SinghIndia s e-waste crisis is escalating at an alarning rate, with the country generating approximately 1.75 million metric tonnes ofe-waste in 2023 24, marking a 73% increase over the past five years. As digital consumption surges, Artificial Intelligence (Al) and the Internet of Things (loT) are being explored as potential solutions to tackle this mounting challenge. Alpowered waste sorting and deep-learning-based recognition systems promise higher efficiency in segregating electronic waste, while loT-enabled smart bins and tracking systems facilitate real time monitoring of disposal patterns. However, despite these technological advancements, the integration of AI and loT remains limited due to high costs, lack of infrastructure, and the dominance of the informal sector, which processes over 95% of India 's e-waste manually. Additionally, Extended Producer Responsibility (EPR) policies, which legally bind manufacturers to manage post-consumer electronic waste, are ofien poorly enforced, leading to greemwashing practices where companies overstate their recycling eforts without meaningful action. Blockchain technology is being explored to enhance transparency ine waste disposal by creating tamper-proof records of recycling processes, but its adoption remains in its infancy. Meanwhile, modular and self repairing electronic devices are emerging as a long-term solution to reduce e-waste generation, but the widespread adoption of such technology is hindered by corporate reluctance and consumer habits. While Al and loT present promising interventions, the reality remains that without regulatory reinforcement, economic incentives, and socio technological integration, India risks merely creating 'smarter trash rather than resolving the core issue. Addressing this crisis requires a multi-faceted approach, balancing innovation with policy reforms andItem AI for Public Good: Managing Health Risks and Opportunities(Nitya Publications, 2025) Tulika SinghArtificial Intelligence (AI) is reshaping public health paradigms, offering transformative benefits while posing novel legal and ethical challenges. This chapter explores AI’s role in advancing health as a global public good, emphasizing the need for a rights based, equity oriented governance framework. It redefines the concept of "public good" in the digital health era, analyzing how AI technologies intersect with the right to health and ethical imperatives outlined by WHO, UNESCO, and UNHRC. The chapter examines AI applications in disease surveillance, diagnostics, telemedicine, and precision medicine, highlighting both their promise and the risks of algorithmic bias, data inequities, and cybersecurity threats. It scrutinizes the Indian legal ecosystem including the IT Act 2000 and the Digital Personal Data Protection Act 2023 alongside global regulatory frameworks such as the EU Artificial Intelligence Act 2024, US FDA guidelines, and WHO's governance principles for health AI. Through a comparative legal lens, the chapter advocates for ethical AI deployment via transparency, explainability, and institutional capacity building. It proposes policy innovations like ethics by design, regulatory sandboxes, and public private collaboration to align AI with public health values. The chapter offers a roadmap for inclusive, accountable, and resilient AI governance that upholds human dignity in global health systems.Item Artificial Intelligence Assisted Teaching and Learning and Research of Environmental Sciences(Bentham Science, 2024) Tameena Khan, Manisha Singh,Saman Raza, Kulsum Hasmi, Seema Joshi, Priya Mishra, Abdul Rahman KhanArtificial intelligence (AI) has become the latest tool in facilitating the computer-assisted teaching-learning process. The Al-based teaching system is viewed as a personalized one-on-one student-teacher interaction. Al in education is becoming more common and has received a lot of attention recently. This growing interest is likely to have a big impact on higher education. Many educators and educational authorities are considering integrating Al topics into K-12 curricula, to provide school students with insights into these evolving technologies. Recent studies on Al curricula have mostly concentrated on identifying which Al tools are better for student learning and what subject matter knowledge and abilities need to be taught. Since the goal of these studies was to promote information, they designed their curriculum with appropriate content, effective delivery methods, and strategies to increase students competency levels. Environmental education seeks to explore natural processes and foster the development of skills and attitudes geared towards sustainability and the protection of the environment. Recently, Al has been widely used in geological, environmental, and related research. It can also assist in the exploration of energy resources and minerals. The use of Al in education teaching-learning and academic achievement has been elucidated in this chapter. This chapter also aims to explore the role of Al-assisted teaching of environmental sciences and how it impacts the overall learning experience. Understanding the role of Al in environmental sciences is very important as it can address crucial problems like climate change, early prediction of natural disasters, and many others. Currently, there is a need to develop accurate models at an affordable time and cost. Other than research, the implementation of Al in environmental education can lead to a change in students' aptitude and interest and can help in the development of sensitivity towards environmental protection.Item Machine Learning: navigating promises and pitfalls of AI(Shipra Publication New Delhi, 2025) Dhriti Tiwari, Sangeeta Suman