Sartajvir Singh – författare

Hyperautomation in Precision Agriculture: Advancements and Opportunities for Sustainable Farming is the first book to focus on the integration of multiple techniques and technologies to create an ecosystem sustaining approach that doesn’t compromise soil health or environmental safety as it increases crop yield. The book highlights the integration of state-of-the-art tools and working models to address the various challenges in the field of agriculture. It also identifies and discusses the potential and challenges of hyperautomation in sustainable agriculture with respect to efficiency improvement and human enhancement of automated operations.Hyperautomation is a true digital transformation in sustainable agriculture utilizing advanced techniques such as robotic process automation (RPA), digital process automation (DPA), unmanned aerial vehicle (UAV), controlled-environment agriculture (CEA), remote sensing, internet of things (IoT), crop modeling, precision farming, sustainable yield, image analysis, data fusion, artificial intelligence (AI), machine learning (ML), and deep learning (DL).Provides a comprehensive overview of the current state-of-the-art of automation in agricultureEnables improved productivity and resource optimizationPresents advanced monitoring/mapping methods in soil properties, nutrients, crop growth, and yield

Google Earth Engine and Artificial Intelligence for Earth Observation: Algorithms and Sustainable Applications explores a wide range of transformative data fusion techniques of Artificial Intelligence (AI) technologies applied to Google Earth Engine (GEE) techniques. It includes a wide range of scientific domains that can utilize remote sensing and geographic information systems (GIS) through detailed case studies. This book delves into the challenges of AI-driven tools and technologies for Earth observation data analysis, offering possible solutions and directly addressing current and upcoming needs within Earth observation. Google Earth Engine and Artificial Intelligence for Earth Observation: Algorithms and Sustainable Applications is a useful reference for geospatial scientists, remote sensing experts, and environmental scientists utilizing remote sensing to apply the latest AI techniques to data obtained from GEE for their research and teaching.Includes utilization of AI with GEE tools for a spectrum of scientific domains in remote sensing and geographic information systems (GIS) including natural hazard assessment, aquatic and hydrological applications, and forest coverHighlights the challenges and possible solutions for AI-driven tools and technologies for Earth observation data analysisIncludes detailed case studies showing specific considerations and exceptions for applications of AI in GEE for Earth observation

Earth Observation using Scatterometers: State-of-the-Art Techniques, Applications, and Challenges explores the critical role scatterometers play in addressing natural disasters, climate action, and food security. It provides comprehensive guidance on leveraging scatterometers for real-time applications, including advanced techniques like super-resolution mapping and multi-source data fusion. This book is an essential resource for understanding the challenges and opportunities of scatterometer satellite datasets. In addition to covering the latest advancements in algorithms and emerging applications, it empowers professionals to efficiently analyze vast amounts of Earth observation data.The book addresses scatterometers' expanding applicability in oceanography, agriculture, the cryosphere, and related Earth-science fields, making it invaluable for scientists, geospatial data analysts, and students of Remote Sensing and Geoscience.Provides detailed instruction on the applications of scatterometers to a wide range of Earth sciences, including benefits and case studies showing real world useCovers the use of scatterometers in analyzing and responding to natural disasters, including analysis of sea-ice melt, cyclone predictions, etc.Includes techniques for monitoring the cryosphere and global climate, with dedicated methodology and data analysis

Invest in Artificial Intelligence in Remote Sensing for Disaster Management to gain invaluable insights into cutting-edge AI technologies and their transformative role in effectively monitoring and managing natural disasters. Artificial Intelligence in Remote Sensing for Disaster Management examines the involvement of advanced tools and technologies such as Artificial Intelligence in disaster management with remote sensing. Remote sensing offers cost-effective, quick assessments and responses to natural disasters. In the past few years, many advances have been made in the monitoring and mapping of natural disasters with the integration of AI in remote sensing. This volume focuses on AI-driven observations of various natural disasters including landslides, snow avalanches, flash floods, glacial lake outburst floods, and earthquakes. There is currently a need for sustainable development, near real-time monitoring, forecasting, prediction, and management of natural resources, flash floods, sea-ice melt, cyclones, forestry, and climate changes. This book will provide essential guidance regarding AI-driven algorithms specifically developed for disaster management to meet the requirements of emerging applications.

The integration of Radio Detection and Ranging (RADAR) remote sensing and Artificial Intelligence (AI) provides a platform for understanding various Earth's surface processes and their predictive analysis. This book offers state-of-the-art techniques and applications to address real-time challenges through AI-based RADAR remote sensing. Furthermore, it explores the potential applications of AI in emerging areas of remote sensing and image processing.