IoT Applications in Agriculture: IoT & How Is It Implemented In Agriculture?
IoT Applications in Agriculture
What Is Iot? - The Simple Explanation
Agriculture is experiencing an unprecedented level of technological adoption. There are a lot of new agricultural technologies that look very promising for the future of farming. The Internet of Things (IoT) started out as a new agricultural technology but has now become more widely used. By the simplest definition, IoT applications in agriculture are nothing more than the Internet controlling things.
IoT technology is used every time you look at your smartwatch to count calories or ask Alexa or Siri to figure out how much a pie is worth. The Internet of Things, or IoT, is just that—things controlled by the Internet. IoT devices are so-called "smart" that can send data over a network. A Coca-Cola vending machine at Carnegie Mellon University in 1982 was one of the first network-connected devices. It could report if the drinks were cold or not.
What Does IoT Mean?
Kevin Ashton, co-founder and executive director of the Massachusetts Institute of Technology (MIT) Auto-ID Laboratory, coined the term "Internet of Things" while he was giving a presentation at Procter and Gamble (P&G) as their Brand Manager in 1999. The purpose of Ashton's presentation to P&G was to introduce RFID tags, which are used to manage the supply chain and make it easier to track the location and stock of each product coming out of it.
In 2000, LG Electronics released a refrigerator that was connected to the Internet and rode the RFID wave. It was called the Internet Digital DIOS. By scanning their RFID tags, it tracked the variety of food items stored there as well as their respective quantities. Even though most people thought the Internet Digital DIOS refrigerator was too expensive for their needs, it eventually led to the internet management of more household appliances.
Although the term "Internet of Things" was first used in 1999, Cisco Internet Business Solutions Group (IBSG) claims that the term "Internet of Things" only emerged between 2008 and 2009 when more "things or objects" than people were connected to the Internet. The number of devices connected to the Internet reached 12.5 billion in 2010 thanks to the growth of smartphones, tablet PCs, and other smart devices. At the same time, the world's population grew to 6.8 billion, bringing the number of connected devices per person to more than one (1.84, to be exact).
IoT Technologies in Agriculture
Smart agriculture IoT products are made to help monitor crop fields by automating irrigation systems and using sensors. Farmers and associated brands can, as a result, effortlessly monitor the state of the field from any location.
Examine the various IoT applications in agriculture using a variety of IoT solutions:
1. Robotics In Agriculture
Automation has advanced since the industrial revolution in the 1800s to handle complex tasks more effectively and boost production. A growing number of farmers are beginning to pay attention to agriculture robots, or Agribots, as a result of rising demands and a global labor shortage. Due to labor shortages in the United States alone, crop production decreased by approximately 213 crores, or 3.1 billion dollars, annually. Agrobots have gained prominence as a result of recent advancements in AI technology and sensors that enable machines to learn from their surroundings. Utilizing the full potential of the Internet of Things in agriculture, we are still in the early stages of an ag-robotics revolution, with the majority of products still in the early stages of trial and R&D.
Weeding Robots
These intelligent Agri robots use digital image processing to look at the images of weeds in their database to see if they are similar to crops, then use their robotic arms to weed out or spray them directly. Plants that are resistant to pesticides are good for the environment and farmers used to spray the whole farm with pesticides because more and more plants are doing so. Herbicides are used in an estimated 13,000 kilograms (3 billion pounds) per year, which reduces their overall cost by 1,725 crores ($25 billion).
Machine Navigation
Tractors and heavy plowing equipment can be operated automatically from the comfort of one's own home using GPS, just like remote-controlled toy cars that require a controller to operate. When these integrated automatic machines detect differences in the terrain, they are extremely accurate and self-adjust, simplifying labor-intensive tasks. Smartphones make it simple to monitor both their movements and the progress they've made at work. These tech-driven motors are enabling advanced farming using IoT independently with features like automatic obstacle detection thanks to advances in agricultural IoT and machine learning.
Harvesting Robotics
Using agribots to select crops is a solution to the labor shortage problem. These cutting-edge machines are able to run round-the-clock and can handle the delicate process of picking fruits and vegetables. These machines use image processing and robotic arms to select the fruits to be picked, controlling their quality. Orchard fruits like apples are a prime target for agribot harvesting because of their high operating costs. These bots can also be used for the greenhouse harvesting of high-value crops like strawberries and tomatoes. These bots can be used in greenhouses to accurately identify the crop's stage and harvest it when it's ready.
Material Handling
Alongside workers, robots can perform dreadful manual labor tasks. They are able to lift hefty objects and carry out precise tasks like spacing plants, maximizing space and plant quality, and lowering production costs.
2. Drones In Agriculture
Various farming activities, such as crop monitoring, crop spraying, soil analysis, and mapping, are enhanced and improved by using drones in agriculture. In fact, agriculture is one of the most significant applications of drones. Farm imaging, mapping, and surveying are all carried out by drones outfitted with sensors and cameras. There are both aerial and ground-based drones. Ground drones are mobile robots that look over the fields. Flying robots are aerial drones, also known as unmanned aircraft systems (UAS) or unmanned aerial vehicles (UAVs). Drones can be controlled from a distance or they can fly on their own using software-controlled flight plans in their embedded systems that coordinate with GPS and sensors. Crop health, irrigation, spraying, planting, soil and field, plant counting, yield prediction, and many other topics can be deduced from drone data. Drones can be purchased and stored near farms, where they can be recharged and maintained, or they can be scheduled for farm surveys (drone as a service). To better make use of IoT applications in agriculture, the drones must be transported to nearby labs following the surveys for data analysis.
3. Remote Sensing In Agriculture
The use of IoT-based remote sensing, which makes use of sensors placed alongside farms like weather stations to collect data and transmit it to analytical tools for analysis, is revolutionizing the way data is acquired from various nodes in a farm. A device that detects anomalies is called a sensor. The analytical dashboard allows farmers to monitor the crops and take action based on insights.
Crop Monitoring
The crops are monitored for changes in light, humidity, temperature, shape, and size by sensors placed along the farms. The farmer is informed of any anomaly that is analyzed by the sensors. As a result, remote sensing can monitor crop growth and aid in disease prevention.
Weather conditions
In order to cultivate suitable crops, sensors collect data on humidity, temperature, moisture precipitation, and dew detection, which aids in determining farm weather patterns.
Soil quality
The nutrient value and drier areas of farms, as well as the capacity for soil drainage or acidity, can be determined through soil health analysis, which enables the selection of the most advantageous cultivation method and the adjustment of the amount of water required for irrigation. By providing insight into when and how to increase organic matter, the soil health data can also help leverage regenerative agriculture, resulting in improved soil structure and eventually paving the way for climate-smart agriculture.
4. Computer Imaging In Agriculture
Computer imaging involves producing images that are subjected to digital image processing through the use of sensor cameras that are positioned throughout the farm or drones that are equipped with cameras. The fundamental idea behind digital image processing is to use computer algorithms to process an input image. Analyzing limiting factors and assisting in better farm management are made possible by image processing, which compares images obtained over time and examines them in various spectral intensities, such as infrared.