03895nam a22006135i 4500 978-3-031-67679-6 DE-He213 20251030112941.0 cr nn 008mamaa 240906s2024 sz | s |||| 0|eng d 9783031676796 978-3-031-67679-6 10.1007/978-3-031-67679-6 doi S1-972 TVB bicssc TEC003000 bisacsh TVB thema Iqbal, Muhammad Azhar. author. aut http://id.loc.gov/vocabulary/relators/aut 83832 Digital Agriculture [electronic resource] : An Introduction / by Muhammad Azhar Iqbal. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XIII, 151 p. 51 illus., 50 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda SpringerBriefs in Agriculture, 2211-8098 Chapter – 1 Fundamentals of Digital Agriculture -- Chapter – 2 Digital Agriculture Ecosystem -- Chapter – 3 Data Acquisition in Digital Agriculture -- Chapter – 4 Data Communication in Digital Agriculture -- Chapter – 5 Data Storage in Digital Agriculture -- Chapter – 6 Data Analytics in Digital Agriculture -- Chapter – 7 Impacts and Future Directions of Digital Agriculture. The success of modern-day agriculture lies in the digitalization of agricultural systems. The primary aim of this book is to provide a starting point to understand the fundamentals and design of digital agriculture systems with reference to the enabling technologies that deal with the production, improvement, and protection of crops/plants and livestock. The other associated objectives of this book include the explanation of the design and deployment of IoT-based digital agriculture systems in such a simple way that agriculture students understand straightforwardly. Therefore, this book is an effort to partially fill the gap associated with the understanding of the development and deployment of digital agriculture systems (including both precision and smart farming). We believe that with the provided details of enabling technologies and their usage in digital agriculture systems, agriculture students will find it easier to comprehend the designing of small-/large-scale IoT-based digital agriculture systems. This book provides insight into different technologies, architectures, and case studies that will ultimately help students to understand the concept of Digital Agriculture and its related applications. It enables students to realize the importance of open issues and future challenges of digital agriculture systems. Agriculture. 68079 Artificial intelligence Data processing. Machine learning. 55059 Biology. 68861 Agronomy. 69554 Agriculture Economic aspects. Agriculture. 68079 Data Science. Machine Learning. 55059 Biological Sciences. 68865 Agronomy. 69554 Agricultural Economics. SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031676789 Printed edition: 9783031676802 Printed edition: 9783031676819 SpringerBriefs in Agriculture, 2211-8098 83833 https://doi.org/10.1007/978-3-031-67679-6 ZDB-2-SBL ZDB-2-SXB 63163 63163