Warehouse logistics has been fundamentally changed by the blistering development of e-commerce, global supply chains and consumer demands to be delivery in less time. Manual and semi-manual warehouse systems are gradually becoming incapable of satisfying contemporary requirements with respect to speed, accuracy, scale, and lowering operating costs. Consequently, robotics has become an important enabling technology of the next-generation warehouse. This paper will provide an in-depth analysis of integrating robotics into the operations of the contemporary warehouse logistics setting as seen through the architecture, operational processes, operational performance, and challenges in implementation. The paper discusses the different categories of warehouse robots, such as: autonomous mobile robots (AMRs), automated guided vehicles (AGVs), robotic picking of goods and collaborative robots (cobots). An extensive literature review underscores current developments, algorithm methods and industrial implementations. The suggested methodology presents a warehouse architecture based on modular robots that incorporates a perception system, a navigation system, a task allocation system and a fleet management system. Measures of performance evaluation including throughput, accuracy of order fulfillment, energy and operational cost are evaluated. The findings reveal a high level of productivity, scalability as well as reliability over traditional systems. The paper will end with the suggestions of research directions on how to continue with it in future, as the approaches of artificial intelligence, digital twins, and human/robot collaboration have been identified as the primary catalysts of intelligent warehouse ecosystems.
B. K· International Journal of Mod...· 0 citations
Smart farming has become a paradigm shift within the agricultural sphere of contemporary society by using high-tech sensing, communication, and data analytics solutions to improve productivity-sustainability and decision-making. One of such technologies is unmanned aerial vehicles (UAVs also known as drones) which have received so much popularity in the field of crop health monitoring because it can capture high-resolution and real-time data on large pieces of Agriculture. This paper has provided an analytic research on the drone-based crop health monitoring systems in terms of their architecture, sensing modalities, data processing methods and the performance evaluation. Multispectral and hyperspectral imaging sensor systems introduced with the UAV systems allow accurate determination of the state of crops in terms of their vigor, herbal deficiencies, water stress, and disease epidemiology. The interpretation of aerial data is also improved with the help of machine learning and deep learning algorithms that allow automatizing the process of organizing crops according to their condition and predicting them. The paper examines the literature that is available, some of the gaps in research, and finally suggests an orderly approach to the implementation of a drone-based crop health monitoring system. The outcomes of experimental study based on simulated and real field experiments indicate the greater accuracy of assessment of vegetation health when compared to the conventional terrestrial techniques. The results suggest that drone-based monitoring can help to significantly decrease the costs of labor force, enhance the accuracy of yield forecasting, and facilitate agricultural intervention. The paper concludes by explaining the constraints in regulatory, data management, and scalability and discusses future research directions based on the autonomous and intelligent smart farming ecosystems.
B. K· International Journal of Mod...· 0 citations
This paper proposes an Explainable Deep Reinforcement Learning (XDRL) framework to automate and personalize credit limit adjustments based on customer behavior, financial data, and macroeconomic indicators, and learns optimal credit limit strategies that balance risk, customer satisfaction, and profitability.
B. K, Meena Krishnan· International Journal of Int...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
