The most severe risks on a global scale over the next 10 years include climate action failure, extreme weather, biodiversity loss, human environmental damage, natural resource crises (Environmental) and social cohesion erosion, livelihood crises, infectious diseases (Societal) (The Global Risks Report -17th addition, 2022). Businesses today as well as the society as a whole cannot overlook these risks as they have an impact on sustainability. Sustainability reporting has become popular, particularly in the last decade, emerging as a result of the evolution of environmental and corporate social responsibility reports (Kuzey & Uyar, 2017) when global sustainability standard setters such as Global Reporting Initiative (GRI), Sustainability Accounting Standards Board (SASB), International Integrated Reporting Council (IIRC or ), Climate Development Project (CDP), etc. developed structured frameworks, topics and metrics to help companies report material sustainability information to their stakeholders (Partners, 2022).This paper aims to study ESG initiatives and effectiveness resulting responsible actions by all social factors through an assessment based on national ranking system for ESG disclosures and sustainability in Indian context. Infosys has been chosen to study as it has been aligning its initiatives with regulations on ESG and such investments made by the company attracts socially conscious investors and create value within their portfolio. On comparing Infosys performance with top ten companies highlights that Infosys has to go a long way in terms of social performance. ESG structures will serve Infosys as a potential benchmark to the Indian corporate sector and emerging world towards spreading awareness and achievement of sustainable development goals. Keywords: ESG, SDGs, Sustainability JEL Classification E

Artificial intelligence is being rapidly incorporated into healthcare systems, but it is not a panacea for all problems. Challenges include a shortage of medicinal datasets for training AI simulations, adversarial assaults, and dearth of confidence owing to its black box operating style are holding back AI's tremendous potential. We looked at how blockchain technology may raise the dependability also credibility of AI-based medical systems. To examine the most recent research articles on healthcare applications created using various AI approaches and Blockchain Technology, this paper performed a systematic literature review. This systematic literature review examines three distinct pathways in healthcare systems that include the ones that utilize natural language processing, those that employ computer vision, and those that rely on acoustic AI. As a consequence, we have created an intangible framework for AI-based healthcare applications utilizing Blockchain Technology that takes into account the requirements of every Computer Vision, NLP, and Acoustic AI application using etherscan.In this chapter, a Patient based Access Control Mechanism for a patient-centric e-Health System is presented to regulate the user resources. The proposed system establishes access control policies to automate the process of sharing health information across health service providers inside the e-Health system. The access control policies of the proposed system establish the access privileges and transfer permissions of the individuals involved in the Blockchain. The suggested method additionally enables data owners to revoke access, thereby restricting users' ability to view the data. Keywords: Healthcare, Computer Vision, Blockchain, Natural Language Processing, Acoustic AI, Adversarial Attack, Etherscan, Access Control.

This comprehensive review explores a multitude of waste segregation techniques and technologies employed in waste management. It covers various methodologies, including Deep Learning, Hyperspectral Imaging, Robotics, Optical Sensors, and more, each designed to improve waste sorting and enhance recycling efforts. The study provides a detailed comparison of these technologies, highlighting their accuracy rates and the specific types of waste they are designed to handle. These technologies offer promising solutions to address the growing challenge of waste management and environmental sustainability. The findings presented in this review serve as a valuable resource for researchers, policymakers, and waste management professionals working towards more efficient and sustainable waste segregation and recycling practices. Keywords: Waste segregation, Digital Image processing, Solid Waste, CNN, Raspberry Pi, SVM.