In comparison to Industry 4.0, Industry 5.0 is seen as the next industrial revolution, with the goal of leveraging the creativity of human experts in combination with efficient, intelligent, and accurate machines to provide resource-efficient and user-preferred solutions. With the improvements in social networks, cloud, and the internet of things (IoT)-based technologies, the requirement for a strong cyber security system, particularly in the healthcare sector, is increasing. Cyber Trafficking, Threat Behavior, and Malicious Activity Monitoring for Healthcare Organizations provides a comprehensive review of techniques and applications of Industry 5.0-enabled intelligent healthcare-centric cyber security. The goal of this book is to close the gap between AI and cyber security. Covering topics such as malicious activity, the dark web, and smart healthcare systems, this premier reference source is an essential resource for healthcare administrators, IT managers, system developers, system architects, IT specialists, students and educators of higher education, librarians, researchers, and academicians.

In today's world, smart healthcare supports the out-of-hospital concept, which transforms and offers higher care standards. This is accomplished with individual requirements with the help of public opinion. Moreover, smart healthcare systems are generally designed to sense individual health status data, which can be forwarded to clinical professionals for interpretation. Swarm intelligence analysis is a valuable tool for categorizing public opinion into different sentiments. Dynamics of Swarm Intelligence Health Analysis for the Next Generation discusses the role of behavioral activity in the evolution of traditional medical systems to intelligent systems. It further focuses on the economic, social, and environmental impacts of swarm intelligence smart healthcare systems. Covering topics such as healthcare data analytics, clustering algorithms, and the internet of medical things, this premier reference source is an excellent resource for healthcare professionals, hospital administrators, IT managers, policymakers, educators and students of higher education, researchers, and academicians.

The purpose of this book is to explore the utility of remotely sensed data acquired for land-use /land-cover (LULC) classifications. The Resourcesat-1 Data is a high resolution (i.e. 5.8-meter), multispectral (3 bands: red, green and near infrared) dataset. Resourcesat-1 imagery has been selected for this study because of its low cost and potential for small scale land use and land cover classifications similar to the success the Landsat (30 meter, multispectral: 7 band) imagery has achieved with large scale classifications. The study has been done using a subdivision in Jharia Coal Field region i.e. Jharia town and the surrounding (rural) property. Supervised (parametric and nonparametric) classification procedures were conducted for the Jharia town area using ERDAS Imagine 9.2. Random sample points were generated for accuracy assessment via a ground based visual assessment of each point's LULC class. By using a 6 class LULC scheme, a supervised classification of the Resourcesat-1 imagery resulted in classification accuracy of 83.07%.

Jharia coalfield in the State of Jharkhand is the prime coking coal reserve in the country. The coal field lies in the Damodar River Valley, and covers about 280 square km, but due to unscientific mining which resulted in severe land degradation. On a rough estimate about 75 percent of the total coal reserves in the coalfield are still available and there is a need for long-term planning. Unfortunately, coal mining has left a severe impact on the land environment. In the present study, extensive use of remote sensing imagery has been used to find the impact of mining in the land environment. Change detection in land use and land cover has been carried out by digital comparison method using satellite image of 2004 and 2009 of Indian Remote Sensing Satellite. On the other hand, Due to a lot of activities in the coalfield many problems generate in the environment, from those, one is land degradation, due to that a large part of land is damaged, a huge part of agriculture land and settlement land also degraded. So selected study area, Jharia Coalfield is suitable for the study of Land Capability Classification.