THE INTERNET OF THINGS (IoT) IN AGRICULTURE
“Leveraging Smart Technologies to Optimize Agricultural Productivity, Sustainability, and Efficiency”
Course Schedule
| Date | Venue | Fees (Face-to-Face) |
|---|---|---|
| 15 – 19 Sep 2025 | London, UK | USD 3495 per delegate |
Course Introduction
Agriculture is rapidly evolving through the integration of Internet of Things (IoT) technologies. Smart sensors, connected devices, and data analytics now enable real-time monitoring and precision control of farming operations—from soil conditions and crop health to irrigation and equipment management. IoT in agriculture not only improves yields but also supports sustainable farming and resource efficiency.
This 5-day course explores how IoT technologies are transforming modern agriculture. Participants will gain practical insights into sensor networks, communication protocols, edge computing, and big data applications in agriculture. Through case studies, hands-on exercises, and solution design workshops, professionals will learn to plan and implement IoT-enabled smart farming systems.
Course Objectives
By the end of this course, participants will be able to:
• Understand the fundamentals and components of IoT architecture in agriculture
• Identify use cases for IoT in crop monitoring, livestock management, and supply chains
• Evaluate sensor types, connectivity options, and data integration techniques
• Design and deploy basic IoT solutions tailored to agricultural needs
• Analyze and interpret IoT-generated data to support decision-making
Key Benefits of Attending
• To adopt modern technologies that improve agricultural productivity and quality
• To enable real-time monitoring of crops, livestock, and environmental conditions
• To reduce input waste and promote sustainable resource use
• To increase operational transparency and automate routine tasks
• To prepare for the digital transformation of farming and agribusiness
Intended Audience
This program is designed for:
• Agricultural engineers and farm managers
• Agri-tech entrepreneurs and consultants
• Policy-makers and smart farming planners
• IT, IoT, and data science professionals in the agriculture sector
• Researchers and academics exploring precision agriculture
Individual Benefits
Key competencies that will be developed include:
• IoT solution design and implementation for agriculture
• Knowledge of sensor selection, network configuration, and data protocols
• Use of dashboards, cloud platforms, and mobile apps for farm management
• Understanding IoT security, scalability, and integration challenges
• Ability to assess ROI and sustainability outcomes from IoT deployments
Organization Benefits
Upon completing the training course, participants will demonstrate:
• Improved productivity, efficiency, and yield forecasting in agricultural operations
• Reduced waste through precision irrigation, fertilization, and pest control
• Built-in traceability and real-time reporting across the food supply chain
• Capacity to innovate using cutting-edge technologies and smart systems
• A more data-driven approach to agricultural planning and policy
Instructional Methdology
The course follows a blended learning approach combining theory with practice:
• Strategy Briefings – IoT architecture, market trends, and smart farming policies
• Case Studies – Global examples of IoT in greenhouse, dairy, and crop farming
• Workshops – Design IoT systems using sensors, gateways, and dashboards
• Peer Exchange – Cross-sector experiences in deploying agri-IoT systems
• Tools – Farm monitoring apps, cloud dashboards, open-source hardware kits
Course Outline
Detailed 5-Day Course Outline
Training Hours: 7:30 AM – 3:30 PM
Daily Format: 3–4 Learning Modules | Coffee breaks: 09:30 & 11:15 | Lunch Buffet: 01:00 – 02:00
Day 1: Introduction to IoT and Smart Agriculture
Module 1: Fundamentals of IoT and Digital Agriculture (07:30 – 09:30)
• What is IoT and how it applies to farming
• Key components: sensors, connectivity, platforms
Module 2: Smart Farming Use Cases and Market Landscape (09:45 – 11:15)
• Applications in crops, livestock, aquaculture, and forestry
• Global adoption trends and key players
Module 3: IoT Architecture and Communication Protocols (11:30 – 01:00)
• MQTT, LoRaWAN, NB-IoT, Zigbee – pros and cons
• Data flow from device to cloud
Module 4: Workshop – Mapping IoT Needs to Farm Scenarios (02:00 – 03:30)
• Develop a use-case map for smart agriculture
Day 2: Sensor Technologies and Farm Connectivity
Module 1: Agricultural Sensors – Selection and Deployment (07:30 – 09:30)
• Soil moisture, temperature, humidity, pH, livestock tags
• Mounting, calibration, and maintenance
Module 2: Connectivity Options for Rural and Remote Farms (09:45 – 11:15)
• Wi-Fi, GSM, LoRa, satellite, mesh networks
• Connectivity planning and infrastructure needs
Module 3: Gateways, Edge Devices, and Data Transmission (11:30 – 01:00)
• Edge computing basics and data preprocessing
• Role of gateways in hybrid architectures
Module 4: Hands-On – Sensor Setup and Network Design (02:00 – 03:30)
• Design a sensor network for a greenhouse or open-field scenario
Day 3: Data Collection, Storage, and Analysis
Module 1: Data Acquisition and IoT Platforms (07:30 – 09:30)
• Cloud-based and on-premise options
• API integration and interoperability
Module 2: Visualization and Decision Support Tools (09:45 – 11:15)
• Dashboards, alerts, and predictive insights
• Farm management systems (FMS)
Module 3: Analytics and Machine Learning in Agriculture (11:30 – 01:00)
• Yield forecasting, disease prediction, and irrigation optimization
Module 4: Workshop – Build a Sample Dashboard (02:00 – 03:30)
• Use sample data to create visual reports and alerts
Day 4: IoT Deployment, Integration, and Security
Module 1: End-to-End Solution Design and Integration (07:30 – 09:30)
• Bringing sensors, platforms, and analytics together
• Planning an IoT deployment roadmap
Module 2: IoT Security Risks and Mitigation (09:45 – 11:15)
• Data integrity, device authentication, and access control
• Cybersecurity considerations for remote operations
Module 3: Cost, ROI, and Sustainability Evaluation (11:30 – 01:00)
• Cost-benefit models for smart agri projects
• Measuring environmental and economic impact
Module 4: Simulation – Design an End-to-End Farm IoT System (02:00 – 03:30)
• Group project for specific agricultural scenarios
Day 5: Innovation, Policy, and Future of Smart Agriculture
Module 1: Emerging Trends in IoT and AgriTech (07:30 – 09:30)
• Blockchain, drones, robotics, and satellite data integration
Module 2: Standards, Regulations, and Data Ethics (09:45 – 11:15)
• Data ownership, privacy, and ethical considerations
• National and international IoT standards in agriculture
Module 3: Final Project Presentations (11:30 – 01:00)
• Group presentations of designed IoT solutions
Module 4: Certification and Course Wrap-Up (02:00 – 03:30)
• Discussion, feedback, and certificate distribution
Certification
Participants will receive a Certificate of Completion in The Internet of Things (IoT) in Agriculture, validating their ability to design, implement, and evaluate smart farming technologies for modern agricultural practices.