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4 books on AI for Agriculture [PDF]
February 24, 2025 | 27 |
These books explore the applications of artificial intelligence in agriculture for crop monitoring, disease detection, yield prediction, and resource optimization.
1. IoT and AI in Agriculture: Self- sufficiency in Food Production to Achieve Society 5.0 and SDG's Globally
2023 by Tofael Ahamed
In a universe not entirely unlike ours, where cows are suspiciously intelligent and tomatoes are known to have existential crises, a group of well-meaning researchers decided it was high time to drag agriculture kicking and screaming into the 21st century. Armed with IoT gadgets that beep impressively and AI algorithms that occasionally understand what they’re doing, they set out to tackle the twin terrors of climate change and overpopulation, all while trying to keep humanity from starving itself silly. From South Asia’s sweltering rice paddies to Southeast Asia’s bustling plantations, they’ve devised clever ways to outsmart pests, tweak sunlight and convince fertilizers to behave themselves. They even got drones involved—because, frankly, why wouldn’t you? As the authors of IoT and AI in Agriculture point out, it’s not just about feeding nine billion people by 2050; it’s about doing so without turning the planet into a sad, overheated puddle. By the end, you’ll find yourself cheering for smart sensors and wondering if crops might one day start composing poetry about their optimized watering schedules.
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2. Innovation in Agriculture with IoT and AI
2022 by Suchismita Satapathy, Debesh Mishra, Arturo Realyvásquez Vargas
"Innovation in Agriculture with IoT and AI" is the sort of book that takes one look at the humdrum state of traditional farming and says, “What if we tossed in some AI, IoT and ML to shake things up a bit?” And shake things up it does, whisking readers into a world where tractors might actually talk back (politely, of course), gadgets know your mental workload better than you do and agricultural safety becomes something other than “just don’t stand under the big, sharp thing.” Packed with case studies and bristling with ideas so forward-thinking they probably have their own Instagram accounts, this book is a must-have for anyone who’s ever thought farming should be a bit more sci-fi.
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3. The Digital Agricultural Revolution: Innovations and Challenges in Agriculture through Technology Disruptions
2022 by Roheet Bhatnagar, Nitin Kumar Tripathi, Nitu Bhatnagar, Chandan Kumar Panda
In a universe not entirely unlike our own—except for the fact that it’s teetering on the brink of agricultural chaos—comes The Digital Agricultural Revolution, a book that bravely asks: "What if artificial intelligence could save your crops before they develop existential crises?" Written by an ensemble of brilliant minds (and presumably no small amount of caffeine), it delves into everything from machine learning models that know your tomatoes better than you do, to deep learning systems that might someday outwit your local aphid population. With climate change gleefully wreaking havoc—droughts here, floods there and the occasional crop pest behaving like it’s auditioning for a disaster movie—this book proposes not to panic, but to innovate. Packed with prototypes, case studies and ideas so groundbreaking they might actually break the ground, it’s essentially a Hitchhiker’s Guide for anyone who thinks “digital disruption” might sound less terrifying if it involved fewer weeds and more wheat.
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4. Machine Learning and Artificial Intelligence for Agricultural Economics: Prognostic Data Analytics to Serve Small Scale Farmers Worldwide
2021 by Chandrasekar Vuppalapati
In a universe not entirely unlike our own, where tractors hum with the quiet sophistication of quantum computers and fields dream in algorithms, Machine Learning and Artificial Intelligence for Agricultural Economics boldly ventures into the untamed wilderness of small-scale farming. Chandrasekar Vuppalapati, part-time agricultural economist and full-time software wizard, presents a guide that’s equal parts cosmic hitchhiker’s map and blueprint for agrarian AI supremacy. Within its pages, data science teams will learn how to wrestle economic models into submission, crafting apps that promise to sprinkle a little machine-learning stardust on the humble farmer’s daily grind. Expect adventures in prognostic analytics, algorithmic sorcery and optimization strategies so clever they might just convince wheat to harvest itself. Whether you’re an earnest student, a bewildered researcher, or a software engineer wondering why your code keeps attracting cows, this book is your ticket to a greener, smarter and distinctly more algorithmic future.
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
1. IoT and AI in Agriculture: Self- sufficiency in Food Production to Achieve Society 5.0 and SDG's Globally
2023 by Tofael Ahamed
In a universe not entirely unlike ours, where cows are suspiciously intelligent and tomatoes are known to have existential crises, a group of well-meaning researchers decided it was high time to drag agriculture kicking and screaming into the 21st century. Armed with IoT gadgets that beep impressively and AI algorithms that occasionally understand what they’re doing, they set out to tackle the twin terrors of climate change and overpopulation, all while trying to keep humanity from starving itself silly. From South Asia’s sweltering rice paddies to Southeast Asia’s bustling plantations, they’ve devised clever ways to outsmart pests, tweak sunlight and convince fertilizers to behave themselves. They even got drones involved—because, frankly, why wouldn’t you? As the authors of IoT and AI in Agriculture point out, it’s not just about feeding nine billion people by 2050; it’s about doing so without turning the planet into a sad, overheated puddle. By the end, you’ll find yourself cheering for smart sensors and wondering if crops might one day start composing poetry about their optimized watering schedules.
Download PDF
2. Innovation in Agriculture with IoT and AI
2022 by Suchismita Satapathy, Debesh Mishra, Arturo Realyvásquez Vargas
"Innovation in Agriculture with IoT and AI" is the sort of book that takes one look at the humdrum state of traditional farming and says, “What if we tossed in some AI, IoT and ML to shake things up a bit?” And shake things up it does, whisking readers into a world where tractors might actually talk back (politely, of course), gadgets know your mental workload better than you do and agricultural safety becomes something other than “just don’t stand under the big, sharp thing.” Packed with case studies and bristling with ideas so forward-thinking they probably have their own Instagram accounts, this book is a must-have for anyone who’s ever thought farming should be a bit more sci-fi.
Download PDF
3. The Digital Agricultural Revolution: Innovations and Challenges in Agriculture through Technology Disruptions
2022 by Roheet Bhatnagar, Nitin Kumar Tripathi, Nitu Bhatnagar, Chandan Kumar Panda
In a universe not entirely unlike our own—except for the fact that it’s teetering on the brink of agricultural chaos—comes The Digital Agricultural Revolution, a book that bravely asks: "What if artificial intelligence could save your crops before they develop existential crises?" Written by an ensemble of brilliant minds (and presumably no small amount of caffeine), it delves into everything from machine learning models that know your tomatoes better than you do, to deep learning systems that might someday outwit your local aphid population. With climate change gleefully wreaking havoc—droughts here, floods there and the occasional crop pest behaving like it’s auditioning for a disaster movie—this book proposes not to panic, but to innovate. Packed with prototypes, case studies and ideas so groundbreaking they might actually break the ground, it’s essentially a Hitchhiker’s Guide for anyone who thinks “digital disruption” might sound less terrifying if it involved fewer weeds and more wheat.
Download PDF
4. Machine Learning and Artificial Intelligence for Agricultural Economics: Prognostic Data Analytics to Serve Small Scale Farmers Worldwide
2021 by Chandrasekar Vuppalapati
In a universe not entirely unlike our own, where tractors hum with the quiet sophistication of quantum computers and fields dream in algorithms, Machine Learning and Artificial Intelligence for Agricultural Economics boldly ventures into the untamed wilderness of small-scale farming. Chandrasekar Vuppalapati, part-time agricultural economist and full-time software wizard, presents a guide that’s equal parts cosmic hitchhiker’s map and blueprint for agrarian AI supremacy. Within its pages, data science teams will learn how to wrestle economic models into submission, crafting apps that promise to sprinkle a little machine-learning stardust on the humble farmer’s daily grind. Expect adventures in prognostic analytics, algorithmic sorcery and optimization strategies so clever they might just convince wheat to harvest itself. Whether you’re an earnest student, a bewildered researcher, or a software engineer wondering why your code keeps attracting cows, this book is your ticket to a greener, smarter and distinctly more algorithmic future.
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
