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AI, IoT and Remote Sensing for Precision Agriculture

Transform farm data into smart agriculture decisions using AI, IoT, remote sensing, and precision farming analytics.

★ 4.1 (31 ratings)18–20 Jun 20265:30 IST3 Days (60-90 Minutes each day)Certificate
The live sessions are over · get the full recording

About This Course

AI, IoT and Remote Sensing for Precision Agriculture is a 3-day hands-on workshop designed to introduce participants to the practical use of smart technologies in modern farming and agricultural monitoring.

Participants will learn how AI, IoT sensors, satellite imagery, drone-based monitoring, and remote sensing platforms can be used to collect, analyze, and visualize farm-level data. The workshop covers soil moisture monitoring, temperature and humidity tracking, crop health analysis, irrigation intelligence, vegetation index interpretation, and yield-related decision insights.

Aim

The aim of this workshop is to help participants understand how AI, IoT, and remote sensing technologies can be integrated for precision agriculture, crop monitoring, irrigation intelligence, yield estimation, and smart farming decision-making.

Workshop Objectives

  • Introduce the fundamentals of precision agriculture and smart farming systems.
  • Explain the role of AI, IoT, and remote sensing in modern agriculture.
  • Help participants understand field-level data such as soil moisture, temperature, humidity, crop health, and vegetation status.
  • Introduce IoT sensors and real-time farm data collection workflows.
  • Demonstrate smart farm system mapping for soil, crop, and irrigation monitoring.
  • Explain IoT architecture for smart agriculture applications.
  • Introduce MQTT communication and HiveMQ-based data publishing/subscription.
  • Guide participants in creating virtual IoT sensor setups using Wokwi.
  • Demonstrate Python-based sensor data reading, cleaning, and basic analytics.
Next: Day-by-day →

Workshop Structure

📅 Day 1: Foundations of AI, IoT and Remote Sensing in Precision Agriculture

  • Introduction to precision agriculture and smart farming systems
  • Understanding the role of AI, IoT, and remote sensing in modern agriculture
  • Basics of soil monitoring, crop monitoring, irrigation intelligence, and yield estimation
  • Understanding field-level data: soil moisture, temperature, humidity, crop health, and vegetation status
  • Introduction to IoT sensors and real-time farm data collection
  • Basics of satellite and drone-based crop monitoring
  • Developing a smart agriculture framework for data-driven farm decision-making

🛠️ Hands-on:

  • Hands-on 1: Smart Farm System Mapping for Soil, Crop, and Irrigation Monitoring
  • Hands-on 2: Virtual IoT Sensor Setup for Soil Moisture and Environmental Data

🧰 Tools Covered: Wokwi, MQTT / HiveMQ, Google Sheets, Python

📅 Day 2: IoT-Based Farm Monitoring and Irrigation Intelligence

  • Understanding IoT architecture for smart agriculture
  • Working with virtual sensors for soil moisture, temperature, humidity, and crop environment monitoring
  • Introduction to MQTT communication for real-time sensor data transfer
  • Using HiveMQ for IoT data publishing and subscription
  • Connecting sensor data workflows for smart irrigation decision-making
  • Using Python for sensor data reading, cleaning, and basic analytics
  • Designing irrigation alerts based on soil and crop condition indicators

🛠️ Hands-on:

  • Hands-on 1: IoT-Based Soil and Crop Monitoring using Wokwi and MQTT / HiveMQ
  • Hands-on 2: Python-Based Irrigation Intelligence and Alert Logic Development

🧰 Tools Covered: Wokwi, MQTT / HiveMQ, Python, Google Colab

📅 Day 3: Remote Sensing, Yield Estimation and Farm Decision Dashboards

  • Introduction to satellite remote sensing for agricultural monitoring
  • Using Sentinel Hub for crop health and vegetation analysis
  • Understanding vegetation indices for precision agriculture
  • Basics of NDVI and crop stress interpretation
  • Using QGIS for spatial visualization of farm and crop health data
  • Introduction to yield estimation using remote sensing and field indicators
  • Creating decision-ready dashboards for crop monitoring, irrigation planning, and smart farming insights

🛠️ Hands-on:

  • Hands-on 1: Crop Health and Vegetation Index Analysis using Sentinel Hub / QGIS
  • Hands-on 2: Mini Project: Smart Farming Dashboard for Soil, Crop, Irrigation, and Yield Insights

🧰 Tools Covered: Sentinel Hub, QGIS, Python, Google Colab, MQTT / HiveMQ

Who Should Enrol?

  • Students and postgraduate learners in agriculture, environmental science, data science, computer science, biotechnology, engineering, and related fields.
  • PhD scholars and researchers working in precision agriculture, smart farming, IoT, AI, remote sensing, GIS, and crop monitoring.
  • Academicians and faculty members interested in teaching or researching AI-enabled agriculture and digital farming.
  • Agriculture professionals, agritech learners, and farm technology enthusiasts.
  • Data science and AI learners interested in real-world agricultural applications.
  • Remote sensing, GIS, and drone imaging learners interested in crop monitoring and farm analytics.
Next: Dates →

Important Dates

Registration Ends

June 18, 2026
IST 4:30 PM IST

Workshop Dates

June 18, 2026 – June 20, 2026
IST 5:30 IST

Workshop Outcomes

  • Explain the role of AI, IoT, and remote sensing in precision agriculture.
  • Identify key field-level data indicators used in smart farming systems.
  • Understand soil monitoring, crop monitoring, irrigation intelligence, and yield estimation workflows.
  • Design a smart agriculture framework for data-driven farm decision-making.
  • Set up a virtual IoT sensor workflow for soil moisture and environmental monitoring.
  • Understand MQTT-based communication for real-time IoT data transfer.
  • Use HiveMQ for publishing and subscribing to IoT sensor data.
  • Process and analyze basic farm sensor data using Python and Google Colab.
Next: Fees →

Recording fee

Participants in India

₹2,499

Participants outside India

$50

  • All session recordings
  • Study material
  • Certificate after completion
  • 1-year access

Get the recording

The live sessions of this workshop are over, so the live fees no longer apply. The recordings are being uploaded. They appear in your dashboard as soon as they are ready, and we will e-mail you then.

Next: FAQ →

Frequently asked questions

Will I get the recording?

Yes. Paid participants get the session recordings and study material in their NanoSchool dashboard (My registrations → Recorded Lectures / Study Material).

What if I miss a live session?

Watch the recording in your dashboard and send your questions to the mentor through the support desk.

Do I get a certificate?

Yes, an e-certificate of participation after the workshop, with a QR code anyone can verify and an "Add to LinkedIn" button.

Which fee category applies to me?

Choose the category that matches your current role: Student, Ph.D. Scholar / Researcher, Academician / Faculty or Industry Professional.

How can I pay?

By card, UPI or PayPal on the payment page; international bank transfer is also available there.

What is the refund policy?

See our Returns, Refunds & Cancellation policy: Returns, Refunds & Cancellation policy

Need Help?

We’re here for you!


(+91) 120-4781-217
 WhatsApp +91 99581 61117

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