Internet of things in Agriculture

The internet and physical world are connected via IoT, resulting in automation. In the monitoring system, farming analysis, and system function, IoT allows operations to eliminate numerous human interventions. The system not only detects changes in plants, soil, and environment but also optimizes the standard process through analysis of large and rich data collections
.IoT has become a tool to increase agricultural production in a cost-effective manner for farmers. Various application areas of IoT

Technologies used: Some of the technologies used in agriculture are:-

1) Robotics

With the shortage of labor across the globe increase the demand of automation, slowly agribots start gain attention among farmers..

• Weeding Robots:
  An increasing number of plants have become resistant to pesticides, benefiting the environment as well as farmers who used to spray pesticides throughout the farm. These smart agribots use digital image processing to compare weed photos in their database to crops in order to weed or spray them directly with their robotic arms.

• Machine Navigation
  Through GPS, remote controlled toy cars, tractors, and heavy equipment can be operated automatically from the comfort of your home. These integrated automatic machines are extremely accurate and self-adjust when terrain changes, simplifying the labor intensive tasks. Their movements and work progress can be tracked via smart phones. With advances in machine learning, these technology-driven motors are becoming smarter and more independent, with features such as automatic obstacle detection.

• Harvesting Robotics
  Agribots are solving the labor shortage problem by picking crops. Having the ability to operate 24 hours a day, these machines are ideal for picking fruits and vegetables. These machines use a combination of image processing and robotic arms to determine which fruits to pick, thus determining the quality. Orchard fruits, such as apples, are prioritised for agribot harvesting because of their high operational costs. High-value crops like tomatoes and strawberries can also benefit from greenhouse harvesting with these bots. These bots can be used in greenhouses to accurately identify crop stages and harvest them at the appropriate time.

• Material Handling
  With the assistance of robots, manual labor tasks can be performed. By lifting heavy materials and performing precise tasks such as plant spacing, they optimize the space and quality of the plant, reducing production costs.

2) Drones

One of the major industries to incorporate drones is agriculture. Using drones equipped with cameras and sensors, farms can be scanned, mapped, and surveyed. Drones can be used on the ground or in the air.. Drones that survey fields on wheels are known as ground drones. Unmanned aerial vehicles (UAVs) or unmanned aircraft systems (UASes), sometimes known as aerial drones, are flying robots . In conjunction with sensors and GPS, drones can be controlled remotely or automatically by software-controlled flight plans that are integrated into their embedded systems. By using the drone data, insights can be gained regarding crop health, irrigation, spraying, planting, soil and field, plant counting, and yield prediction, among other things. Drones can be hired for agricultural surveys (drone as a service) or purchased and parked near farms for charging and maintenance.

3) Remote Sensing

Sensors, such as weather stations, are put along farms to collect data, which is then communicated to analytical tools for examination.. Sensors are devices sensitive to anomalies. Farmers can use an analytical dashboard to keep tabs on their crops and take action based on what they learn.

• Monitoring Crops:
  Sensors positioned throughout the farms track changes in light, humidity, temperature, shape, and size of the crops. Any anomaly is detected by the sensors, is analysed and the farmer is notified. Thus remote sensing can help to Keep an eye on the spread of diseases and the growth of crops..

• Weather conditions:
  Sensor data on humidity, temperature, moisture precipitation, and dew detection aids in identifying the weather pattern in farms so that appropriate crops may be cultivated.

• Soilquality:
  The examination of soil quality aids in evaluating nutritional value and drier parts of farms, as well as soil drainage capacity and acidity, allowing for the adjustment of irrigation water requirements and the selection of the most advantageous form of cultivation.

4) Computer Imaging

Computer imaging entails the employment of sensor cameras placed across the farm or drones equipped with cameras to create photos that are then processed digitally. A digital image is processed using computer algorithms to produce the output. The processing of images in different spectral intensities, such as infrared, compares the images obtained over time and detects anomalies, allowing farmers to study limiting factors and manage the farms more

This area is a very relevant interdisciplinary domain in BCA because it integrates fundamental ideas from programming, data analytics, artificial intelligence, sensor networks, and image processing. DCSMAT students can create applications that support sustainable development and smart farming since the Internet of Things is at the heart of the agricultural industry’s digital transformation.