Simplifying The Complexities Of Agriculture With IoT

IoT Smart Farming

The Internet of Things can be of immense help in increasing the sustainability and productivity of agriculture. Data generated by IoT based drones and soil sensors can help farmers make informed decisions about the irrigation and sowing of crops, among other things. Amazon offers a range of services for IoT device management as well as data collection and analysis, which can be used by farmers to build a range of agricultural applications and solutions.

Bharatram Vaidyanathan had spent two decades immersed in the fast-paced world of IT. But as the years passed, he found himself growing increasingly frustrated and weary of the relentless pressure and stress that came with his job. He yearned to return to his roots in Michaelpatti, his native village. So he quit his high-paying IT job and headed back to his homeland, seeking a life that was more in harmony with nature.

When Bharat returned to Michaelpatti, he was greeted by acres of uncultivated land surrounding his own plot. This sight inspired him to expand his land holdings, purchasing an additional 40 acres. However, this decision came with its own set of challenges.

The first problem Bharat faced was a severe shortage of labour. The younger generation had mostly migrated to cities in search of better job opportunities, leaving a scarcity of skilled farmworkers in the village. Moreover, water wastage was rampant due to outdated irrigation methods, and cattle encroachment was damaging his crops. Weeds were also taking over the fields, competing with his crops for valuable nutrients.

Determined to turn things around and make a success of his agricultural venture, Bharat began researching modern farming techniques. It wasn’t long before he stumbled upon the concept of IoT (Internet of Things) in agriculture. He realised that this technology could be the solution to his problems.

Bharat started by implementing IoT sensors in his fields. Soil moisture sensors were installed to monitor the exact moisture levels in the soil, allowing him to optimise irrigation and reduce water wastage. He also installed cameras and motion sensors to deter cattle from entering his fields.

To address the labour shortage, Bharat invested in agricultural drones equipped with cameras and sensors. These drones could monitor the crops, identify weed-infested areas, and even assist in planting seeds and applying fertilisers.

He then set up a smart irrigation system that could be controlled remotely from his smartphone. With weather data from IoT-connected weather stations, he could make informed decisions about when and how much to irrigate, further conserving water and improving crop yields.

As time passed, Bharat’s farm started to flourish. The IoT technology he had embraced had transformed the way he managed his land. He no longer had to worry about water wastage, cattle intrusion, or labour shortages. His fields were weed-free, and his crops were thriving.

Word of Bharat’s success soon spread throughout the village, inspiring other farmers to adopt IoT in their farming practices. Together, they were not only reaping the benefits of increased productivity but also contributing to the sustainable and economic development of their taluk.

IoT in agriculture

IoT has significant applications in agriculture, often referred to as ‘agri IoT’ or ‘smart farming’. IoT technology enables farmers to collect and analyse real-time data from their farms, making agriculture more efficient and adaptable to changing conditions.

IoT in agriculture has the potential to revolutionise the industry by increasing productivity, reducing costs, and promoting sustainability. It empowers farmers with valuable data-driven insights and tools to make more informed decisions.

Here are some key aspects of IoT in agriculture.

Precision agriculture: IoT sensors, such as soil moisture sensors, weather stations, and GPS-enabled equipment, allow farmers to monitor and control various factors like soil conditions, temperature, humidity, and crop health with high precision. This data helps optimise resource usage, reduce waste, and increase crop yields.

Crop monitoring: IoT devices can be used to monitor crop growth and health. Drones equipped with cameras and sensors can capture images of fields and provide valuable insights into plant health, pest infestations, and crop stress. Farmers can then take targeted actions to address these issues.

Livestock management: IoT devices like RFID tags and wearable sensors can be used to monitor the health and location of livestock. Farmers can track individual animals, monitor their vital signs, and receive alerts in case of illness or distress.

Smart irrigation: IoT-based irrigation systems can be programmed to deliver water only when and where it’s needed. Soil moisture sensors can detect moisture levels and trigger irrigation systems accordingly, reducing water wastage and optimising crop hydration.

Weather forecasting: Access to real-time weather data through IoT helps farmers make informed decisions about planting, harvesting, and pest control. It allows them to mitigate the risks associated with adverse weather conditions.

Supply chain management: IoT can improve the tracking and traceability of agricultural products throughout the supply chain. Sensors and RFID tags can be used to monitor the temperature and humidity of crops during storage and transportation, ensuring product quality.

Smart greenhouses: IoT sensors and actuators can be used to control temperature, humidity, and lighting in greenhouses automatically. This optimises growing conditions for crops, extending the growing season and improving yield.

Data analytics: IoT-generated data can be analysed using advanced analytics and machine learning algorithms to provide actionable insights. Farmers can make data-driven decisions about planting, harvesting, and resource allocation.

Remote monitoring: Farmers can remotely monitor their farms using smartphones or computers. This enables them to respond quickly to issues and make adjustments to farm operations from anywhere.

Resource efficiency: IoT helps reduce resource wastage by optimising the use of water, fertilisers, pesticides, and energy. This not only reduces costs but also minimises the environmental impact of agriculture.

Market access: IoT can provide farmers with access to real-time market information, helping them make informed decisions about when and where to sell their products to get the best prices.

Sustainability: IoT-enabled precision agriculture practices can contribute to sustainable farming by reducing environmental impact, conserving resources, and minimising the use of chemicals.

Drones as IoT devices

Drones, also known as unmanned aerial vehicles (UAVs), are increasingly being used as IoT devices in agriculture to gather data, monitor crops, and make informed decisions for improved farming practices.

Equipped with cameras and sensors, drones can fly over agricultural fields to capture high-resolution images and data about crop health. These images can be analysed using IoT technology to detect early signs of disease, nutrient deficiencies, or pest infestations. This real-time monitoring allows farmers to take prompt action to mitigate issues.

Drones are integrated with GPS technology and IoT sensors to precisely measure and map fields. This information is used to optimise irrigation, fertilisation, and pesticide application, reducing resource wastage and improving crop yields.

Drones can carry sensors that measure soil moisture, pH levels, and nutrient content. This data helps to make data-driven decisions about soil management, such as when and where to irrigate or apply fertilisers.

Drones can provide real-time weather data, including temperature, humidity, wind speed, and precipitation levels. This information helps farmers make informed decisions about planting, harvesting, and protecting crops from adverse weather conditions. They can also be used to monitor and manage livestock. IoT-enabled drones can track the location of animals, assess their health, and even provide real-time video feeds for remote monitoring.

Drones can also be equipped with sprayers to apply pesticides or fertilisers precisely where needed. IoT technology controls and optimises the spraying process based on data from sensors, reducing chemical usage and minimising environmental impact.

All the data collected by drones can be sent to cloud-based IoT platforms for analysis. Farmers and agronomists can access this data remotely to make data-driven decisions, track trends over time, and create predictive models for better crop management.

Using historical data, drones can help predict crop yields for a season. This information is crucial for crop planning, resource allocation, and marketing strategies.

In case of natural disasters or crop damage, drones can be used to assess the extent of the damage quickly and accurately.

IoT and soil sensors

The use of soil probes as IoT devices in agriculture enhances precision farming, resource efficiency, and environmental sustainability. It empowers farmers to make informed decisions, optimise crop management, assess soil conditions, and boost yields while conserving water and fertilisers.

These IoT-equipped probes, armed with sensors for soil moisture, temperature, pH, and nutrient levels, continually gather real-time field data. This data is wirelessly transmitted to a central control system or cloud-based platform via technologies like Wi-Fi, cellular networks, or LoRaWAN. Farmers and agronomists access this data through web or mobile apps, enabling remote monitoring and timely decision-making.

Soil moisture sensors on these probes relay information about soil moisture levels at varying depths, allowing automated irrigation systems to trigger irrigation only when necessary, thus preventing water wastage.

IoT-enabled soil probes, equipped with nutrient sensors, assess soil nutrient levels and recommend precise fertiliser application rates, reducing excess fertiliser use and nutrient runoff. Integration of these sensors with weather forecasting services enables farmers to make informed decisions based on upcoming weather events, influencing planting and harvesting schedules.

Moreover, these IoT-based soil probes can be integrated with other farm equipment and actuators, granting farmers remote control over irrigation systems, valves, and devices based on real-time soil data, weather forecasts, and preset conditions.

The probes also send alerts and notifications to farmers’ smartphones or email addresses when soil conditions deviate from desired levels, facilitating rapid responses to issues such as soil moisture depletion or pH imbalances.

Furthermore, IoT systems store historical soil data, allowing for trend analysis and identification of patterns. This historical data informs strategies for long-term soil health improvement, crop rotation planning, and farming practice optimisation.

The scalability of IoT-enabled soil probes makes them suitable for both small-scale and large-scale agricultural operations, providing versatile solutions for modern farming.

Weed management with IoT

An automated weed removal robot powered by IoT is a state-of-the-art solution for precise and efficient weed control in agriculture. This robot seamlessly combines robotics, sensors, and connectivity to identify and eradicate weeds while significantly reducing the need for herbicides and manual labour.

IoT-based robots excel in delivering precise and targeted weed control, thereby minimising herbicide usage and mitigating potential harm to crops. These autonomous machines cover expansive areas swiftly, resulting in time and labour cost savings. The data gathered by the robot helps form weed management strategies.

The reduction in herbicide use and the enhancement of weed control practices foster environment-friendly and sustainable farming practices. Over time, the decreased reliance on herbicides and reduced labour costs leads to substantial savings for farmers. IoT-based weed removal robots are versatile and can be tailored to different field sizes and crop types.

Here’s how an IoT-based weed removal robot operates.

Sensors and data collection: Equipped with various sensors including cameras, infrared sensors, and GPS, the robot scans the field, discerning weeds from crops. Continuous data collection includes image capture and assessment of crop and weed health and growth stages. This data is then processed and analysed in real-time or transmitted to a central system or cloud platform via IoT connectivity.

Weed identification: Utilising a deep learning-based convolutional neural network (CNN) algorithm, the robot accurately identifies and classifies weeds based on their physical characteristics such as appearance, size, colour, and growth patterns. The system boasts the ability to distinguish between crops and weeds with exceptional precision.

Precision herbicide application: Once weeds are pinpointed, the robot employs precision application technology, directing herbicides solely towards the identified weeds. This precise targeting minimises herbicide usage and chemical exposure to crops. Some robots opt for mechanical methods like cutting, tilling, or uprooting to eradicate weeds without resorting to herbicides.

Autonomous navigation: Relying on GPS and mapping data, the robot autonomously navigates within the field. It adheres to predetermined paths or employs obstacle detection and avoidance mechanisms to manoeuvre around obstructions.

Remote monitoring and control: Farmers and agronomists can remotely oversee the robot’s progress, making real-time adjustments via a web-based or mobile application. This remote control allows for route modifications, herbicide application adjustments, or the pausing of operations when needed.

Data logging and analysis: The robot systematically records data pertaining to weed density, distribution, and treatment effectiveness. Historical data is securely stored, facilitating comprehensive analysis and enabling farmers to make informed decisions about weed management and future optimisation.

Weather integration: The robot may seamlessly integrate with weather forecasting services to make well-informed decisions regarding operation timing, accounting for weather conditions such as wind speed and rainfall forecasts.

IoT-based irrigation systems

Data is transmitted via IoT connectivity to a central system for analysis. Based on this data, the system makes informed decisions about when and how much to irrigate a crop.

IoT-based irrigation systems offer water efficiency, energy savings, improved crop health, cost savings, environmental sustainability, data insights, and scalability. They prevent over-irrigation and water wastage, leading to higher crop yields. By conserving water and energy and reducing the risk of over-irrigation, these systems contribute to more sustainable and environment-friendly farming practices. IoT-based irrigation systems can be adapted for farms of various sizes, from small family farms to large commercial operations.

Farmers can remotely monitor and control the system through web-based or mobile applications, allowing real-time adjustments to irrigation schedules.

IoT services from Amazon

Amazon Web Services (AWS) offers a range of IoT services to help farmers and organisations build and manage IoT applications and solutions. These services ease the complexities of IoT, including device management, data collection and analysis, and connectivity.

AWS IoT Core: This is the central service for IoT on AWS. It provides the ability to connect IoT devices to the cloud securely and at scale. It supports MQTT and HTTP protocols for device communication and provides features for device authentication, authorisation, and message routing.

AWS IoT Device Management: This service allows you to register, organise, monitor, and remotely manage IoT devices at scale. We can use it to maintain device information, push firmware updates, and track device health.

AWS IoT Analytics: AWS IoT Analytics enables you to collect, process, and analyse IoT data. It offers features for data ingestion, transformation, storage, and visualisation. You can use it to build real-time and batch analytics pipelines for IoT data.

AWS IoT Events: This service helps you detect and respond to IoT events and triggers actions based on defined rules. For example, you can use AWS IoT Events to trigger alerts or initiate automated workflows when certain conditions are met.

AWS IoT Greengrass: Greengrass extends AWS IoT to the edge, allowing you to run IoT applications and perform local processing on IoT devices. It enables devices to operate even when they are not connected to the internet, and provides features for local data caching and machine learning inference.

AWS IoT SiteWise: AWS IoT SiteWise is used for industrial IoT applications. It helps collect, structure, and analyse data from industrial equipment and processes, allowing you to monitor and optimise industrial operations.

AWS IoT Things Graph: This service lets you visually connect different devices and web services to build IoT applications using a drag-and-drop interface. It simplifies the integration of various IoT components.

AWS IoT Device Defender: Device Defender is a security service that continuously audits your IoT configurations and identifies potential security issues. It helps you monitor and protect your IoT environment from security threats.

AWS IoT FleetWise: This service is designed for fleet management, enabling you to manage and monitor large numbers of connected vehicles, such as cars, trucks, or drones.

Amazon FreeRTOS: Amazon FreeRTOS is an operating system for microcontrollers that makes it easy to securely connect small, low-power devices to AWS IoT services.

AWS IoT 1-Click: This service simplifies the deployment of IoT devices with just one click, making it easier for customers to set up simple IoT solutions like dash buttons.

Using AWS IoT services for a smart farm

Let’s now see how we can use the AWS services listed above for using IoT in a smart farm.

  • Third-party drones send data through AWS Lambda for protocol conversion.
  • Sensors or cameras running FreeRTOS send data to AWS IoT Greengrass, providing protection from intermittent connectivity.
  • AWS IoT Greengrass streams enable ingestion from edge devices to Kinesis Data Streams.
  • Real-time video via Amazon Kinesis Video Streams is used for streaming and replaying video content.
  • Real-time insights are derived with Amazon Managed Service for Apache Flink and users are notified via Amazon Simple Notification Service.
  • Analytics is enabled with OpenSearch, and Amazon Simple Storage Service is used for a data lake strategy.
  • Owned data, like planting records or farm finances, is transferred securely into your data lake with AWS Direct Connect.
  • Data from a sensor ecosystem hosted on AWS with AWS PrivateLink is consumed securely.
  • Users are empowered with insights delivered via Amazon API Gateway or visualisations with Amazon QuickSight.
  • Machine learning (ML) models are built and deployed for edge inference with Amazon SageMaker. Amazon SageMaker Ground Truth is used to manage data labelling workflow.
  • Each time a new file is written into Amazon S3, AWS Glue Crawler crawls the data to infer the schema and make it available into the AWS Glue Data Catalog. Amazon Athena does on-demand querying.
  • A Lambda function is used to import the AWS IoT Device Defender reports into AWS Security Hub, in order to centralise incident response.

IoT in agriculture is poised to bring about significant advancements and transformations in the way we cultivate, manage, and monitor crops. Implementing IoT in agriculture with AWS IoT services empowers farmers with the tools and insights needed to optimise their operations, reduce costs, improve crop quality, and make more informed decisions.

I would like to thank Balakrishnan Srinivasan (CTO – Hybrid Cloud Application Modernization Services, IBM India) for encouraging me to write this article, Sudeshna Majumder (associate partner – GIC Migration Factory Leader, IBM Consulting) for giving me the time to write this real-time experience, and Harsh Mehta (delivery manager, IBM India) for helping me release this article for publishing.


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