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Price Distribution

Price distribution over 62 days • 1 price levels

Days at Price

Price Analysis

Most common price: £160 (62 days, 100.0%)

Price range: £160 - £160

Price levels: 1 different prices over 62 days

Description

The integration of 3D printing and digital twins into smart agriculture transforms traditional farming practices by enhancing precision, efficiency, and sustainability. As the agricultural sector faces challenges like climate change, resource limitations, and food shortages, these advanced technologies offer innovative solutions. 3D printing enables the rapid production of farming tools and equipment, while digital twins allow real-time monitoring, simulation, and optimization of agricultural processes. They provide farmers with data-driven insights and tools to improve productivity and reduce waste. Further exploration of the role of 3D printing and digital twins may revolutionize smart agriculture and shape the future of food production. 3D Printing and Digital Twins in Smart Agriculture explores how 3D printing and digital twin technologies are applied to improve efficiency, precision, and sustainability in smart agriculture. It examines their potential to transform farming practices through real-time data analysis, customized tools, and predictive modeling. This book covers topics such as sensor technology, sustainability, and data science, and is a useful resource for engineers, agriculturalists, policymakers, academicians, researchers, and scientists.

Product Specifications

Format: hardcover
ASIN: B0FTCQX47G
Category: Books > Subjects > Computing & Internet > Computer Science
Domain: Amazon UK
Release Date: 24 September 2025
Listed Since: 01 October 2025

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3D Printing and Digital Twins in Smart Agriculture

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It has never been this cheap. We have no record of a lower price.

3D Printing and Digital Twins in Smart Agriculture

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

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Generative Adversarial Networks for Remote Sensing

Leveraging Urban Computing for Sustainable Urban Development

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