Ahmed Tanvir’s scientific contributions

Artificial intelligence (AI), Machine Learning (ML), and blockchain technology are revolutionizing businesses by fostering creativity, efficiency, and security across a range of sectors. This paper explores the mutually beneficial relationship between these technologies using bibliometrics and content analysis, shedding light on their emerging applications and new research directions. We identify key industries like banking, supply chain management, and healthcare where blockchain and artificial intelligence are significantly influencing these disciplines by looking at a broad range of academic and commercial publications. Findings indicate that combining blockchain's decentralized security characteristics with AI-driven predictive analytics enhances automated decision-making, fraud detection, and transparent transactions. In a similar vein, supply chain management employs AI to forecast demand and maximize inventory, while smart contracts driven by blockchain technology streamline transportation. Blockchain and AI integration are used in healthcare applications to improve diagnosis, safeguard patient information, and facilitate interoperable medical records. Despite these advancements, problems with scalability, regulatory ambiguity, and technical complexity are impeding widespread adoption. Multidisciplinary collaboration, innovative policymaking, and advancements in blockchain and AI infrastructures are required to address these issues. By mapping the most significant papers, organizations, and academics that are affecting the field, this study offers valuable information for future research and business endeavors in this transformative sector.

Globally, approximately one-third of the total food produced is wasted. The environmental effect of such wastage is the contribution to greenhouse gas emissions, and economically, money that could have been reinvested in the economy is lost. This research showcases the ability of IoT devices to gather data on wastage and management as they happen, as well as big data analytics in facilitating data acquisition for enhanced decision-making. The research proposal seeks to show how the use of these technologies can support waste minimization, efficiently utilize resources, and promote sustainability in the agro-food chain. Thus, a literature survey will be applied to outline the meth-odologies currently in use, the holes in current practice, and new ideas on how to incorporate IoT and big data in waste management. Furthermore, several case studies 'success stories' are highlighted to explain and quantify an actual application of these technologies in different sectors of the agro-food chain with tangible results in terms of reduction of the number of wastes and gains in efficiency. The application of Internet of Things (IoT) technologies and big data analytics for real-time handling of agro-food waste is a major problem in the agro-food sector. The conclusions highlight the positive effect of IoT and big data in tackling agro-food waste; at the same time, they give practical suggestions for the key players throughout the supply chain. Thus, our study gives insights into a shift in the management of agro-food waste through efficient technology and rallying policymakers, industry experts, and researchers to fully capture technological improvements for development.