IoT Applications in Agriculture

WHAT IS IOT? - THE SIMPLE EXPLANATION

Everytime you look at your smart watch to count calories or ask Alexa or Siri to calculate the value of pie, you are using what is IoT tech. IoT by simplest of definitions is just that - Internet controlling things. IoT devices are ‘smart’ devices that can transfer data over a network. One of the first network connected devices was a 1982 Coke vending machine at Carnegie Mellon University which was able to report if the drinks were cold or if there were drinks at all.

The term Internet of Things was coined in 1999 by Kevin Ashton, co-founder and executive Director of the MIT Auto ID centre, while he was giving a presentation at Procter and Gamble as their Brand Manager. The presentation that Ashton made for Procter and Gamble was meant to introduce RFID tags to manage the supply chain so that the location and stock at hand of each item coming out of it can be more easily monitored.

Riding the RFID wave LG Electronics then put out a refrigerator known as the Internet Digital DIOS back in the year 2000 which was connected to the Internet. It kept track of the kind of food items that were stored in it as well as their respective quantities by scanning their RFID tags. Though the Internet Digital DIOS refrigerator didn’t sell well because most people thought it was too expensive for their needs, it would eventually pave the way for more house appliances to be managed via internet.

According to Cisco Internet Business Solutions Group (IBSG), though the term was coined in 1999, the Internet of Things was born in between 2008 and 2009 at simply the point in time when more “things or objects” were connected to the Internet than people. Citing the growth of smartphones, tablet PCs, etc the number of devices connected to the Internet was brought to 12.5 billion in 2010 while the world’s human population increased to 6.8 billion, making the number of connected devices per person more than 1 (1.84 to be exact) for the first time in history.

APPLICATIONS OF IOT IN AGRICULTURE - THE NEED AND IMPLEMENTATION

IOT In Agriculture

ROBOTICS

Since the industrial revolution in the 1800s, automation is only getting advanced to efficiently handle more sophisticated tasks and increase production. With increasing demands and shortage of labor across the globe, agriculture robots or commonly known as Agribots are starting to gain attention among farmers. Crop production decreased by an estimated 213 crores approx ($3.1 billion) a year due to labor shortages in the USA alone. Recent advancements in sensors and AI technology that lets machines to train on their surroundings has made agrobots more notable. We are still in the early stages of an ag robotics revolution with most of the products still in early trial phases and R&D mode.

Weeding Robots
Weeding Robots

These smart agribots use digital image processing to look through the images of weeds in their database to detect similarity with crops and weed out or spray them directly by their robotic arms. With increasing number of plants becoming resistant to pesticides they are a boon to the environment and also to farmers who used to spread the pesticides throughout the farm-an estimated 13000 kgs (3 billion pounds) of herbicides applied at a cost of 1725 crores ($25B) each year, thus reducing their overall cost.

Machine Navigation
Machine Navigation

As remote controlled toy cars are enabled with a controller, tractors and heavy ploughing equipments can be run automatically from the comfort of home through GPS. These integrated automatic machines are highly accurate and self adjust when they detect difference in terrains, simplifying the labor intensive tasks. Their movements as well as work progress can be easily checked on smartphones. With advancements in machine learning these tech driven motors are becoming smarter and independent with features such as automatic obstacle detection.

Harvesting Robotics
Harvesting Robotics

Utilizing agribots to pick crops is solving the problem of labor shortages. Working the delicate process of picking fruits and vegetables these innovative machines can operate 24/7. A combination of image processing and robotic arms is used by these machines to determine the fruits to pick hence controlling the quality. Due to high operational costs crops that have an early focus on agrobot harvesting are orchard fruits like apples. Greenhouse harvesting also finds applications with these bots for high value crops like tomatoes and strawberries. These bots can work in greenhouses to aptly determine the stage of crop and harvest them at the right time.

Material Handling
Material Handling

Robots can perform dreaded manual labor tasks working alongside the labors. They can lift heavy materials and perform tasks like plant spacing with high accuracy therefore optimizing the space and plant quality, and reducing production costs.

DRONES

Using of Drones in Agriculture

Agriculture is one of the major industries to incorporate drones. Drones equipped with sensors and cameras are used for imaging, mapping and surveying the farms. There are ground based drones and aerial drones. Ground drones are bots that survey the fields on wheels. Aerial drones- formally known as unmanned aerial vehicles (UAVs) or unmanned aircraft systems (UASes) are flying robots. Drones can be remotely controlled remotely or they can fly automatically through software-controlled flight plans in their embedded systems, working in coordination with sensors and GPS. From the drone data, insights can be drawn regarding crop health, irrigation, spraying, planting, soil and field, plant counting and yield prediction and much more. Drones can either be scheduled for farm surveys ( drone as a service ) or can be bought and stored near farms where they can be recharged and maintained. After the surveys the drones need to be taken to nearby labs to analyse the data that has been collected.

REMOTE SENSING

Remote Sensing in Farming

IoT based remote sensing utilizes sensors placed along the farms like weather stations for gathering data which is transmitted to analytical tool for analysis. Sensors are devices sensitive to anomalies. Farmers can monitor the crops from analytical dashboard and take action based on insights.

  • Crop Monitoring

    Sensors placed along the farms monitor the crops for changes in light , humidity, temperature, shape and size. Any anomaly is detected by the sensors is analysed and farmer is notified. Thus remote sensing can help prevent the spread of diseases and keep an eye on the growth of crops.

  • Weather conditions

    The data collected by sensors in terms of humidity, temperature, moisture precipitation and dew detection helps in determining the weather pattern in farms so that cultivation is done for suitable crops.

  • Soil quality

    The analysis of quality of soil helps in determining the nutrient value and drier areas of farms, soil drainage capacity or acidity, which allows to adjust the amount of water needed for irrigation and the opt most beneficial type of cultivation.

COMPUTER IMAGING

Computer Imaging

Computer imaging involves the use of sensor cameras installed at different corners of the farm or drones equipped with cameras to produce images which undergo digital image processing. Digital image processing is the basic concept of processing an input image using computer algorithms. Image processing views the images in different spectral intensities such as infrared, compares the images obtained over a period of time and detects anomalies thus analysing limiting factors and helps better management of farms.

  • Quality control
    Quality control

    Image processing combined with machine learning uses images from database to compare with images of crops to determine the size, shape, color and growth therefore controlling the quality.

  • Sorting and grading
    Sorting and grading

    Computer imaging can help sort and grade the produce based on their size, color and shape.

  • Irrigation Monitoring
    Irrigation Monitoring

    Irrigation over a period of time helps in mapping of irrigated lands. This helps in deciding during pre harvest season whether to harvest or not.

IOT IN AGRICULTURE- IN SIMPLE WORDS

Connectivity Across 30 Bn Devices by 2020

Internet of Things (IoT) device is every object that can be controlled through the internet. IoT devices have become pretty popular in consumer markets with wearable IoWT (Internet of Wearable Things) such as smartwatches and home management products like Google home. It is estimated over 30 billion devices could be connected to the Internet of Things by 2020. The applications of IoT in farming target conventional farming operations to meet the increasing demands and decrease production loses. IoT in agriculture uses robots, drones, remote sensors and computer imaging combined with continuously progressing machine learning and analytical tools for monitoring crops, surveying and mapping the fields and provide data to farmers for rational farm management plans to save both time and money.

FAQs

What is IoT?

IoT is abbreviated form of Internet of Things. IoT is a broad terminology given to every object that can relay information when connected to network. The term Internet of Things was coined in 1999 by Kevin Ashton, co founder and executive Director of the MIT Auto ID centre, while he was giving a presentation at Procter and Gamble as their Brand Manager which was meant to introduce RFID tags to manage the supply chain so that the location and stock at hand of each item coming out of it can be more easily monitored.

How is IoT integrated in agriculture?

Agriculture implements IoT through use of robots, drones, sensors and computer imaging integrated with analytical tools for getting insights and monitor the farms. Placement of physical equipment on the farms monitors and records data which is used to get insights.

How is IoT integrated in agriculture?

Agriculture implements IoT through use of robots, drones, sensors and computer imaging integrated with analytical tools for getting insights and monitor the farms. Placement of physical equipment on the farms monitors and records data which is used to get insights.

We are a multinational corporation who is into precision farming and plan to adopt agritech farm management system which lets us manage activities on all farms from head office.
What are the key differences between Saas and IoT agritech that should be considered before investing ?
SaaS

SaaS

  • No physical equipment required to be placed on farms
  • High skilled labor not required
  • No equipment required on farms
  • No hardware maintenance costs, Insights are accessible on laptop or PC screens and data stored in clouds
  • Yearly or monthly subscription plans available at low cost, low risk investment
  • High resolution satellite images for monitoring, GPS geotagging and weather analysing
  • Holitistic supply chain management
  • Very scalable , single application for management of multiple farms around the globe
  • Labor logs and chemical usage data available
  • Can be integrated with existing devices and IoTs
  • One stop solution for managing all the operations pre and post harvest
IoT

IoT

  • Sensors, robots, drones and cameras required to be placed on farms to monitor and operate.
  • Requires high skilled field staff to implement and manage bots and insights of IoT lingua
  • Equipments are expensive and fragile
  • Recurring maintenance costs for hardware
  • Heavy initial investments
  • Computer imaging is done via sensor cameras and drones with manual operators
  • No supply chain management
  • Not scalable, each farm data has to be managed separately
  • No log info
  • Difficult to integration with already implemented devices
  • Each equipment has a defined set of operation, not one can show all stats
What are infrastructure requirements for adopting smart farming IoT?
  • The high initial investments in sensors, drones and bots and their setting up.
  • Hiring highly trained field staff for operating and management.
  • Connectivity to power to charge and operate the drones and robots.
  • Hardware maintenance costs.
  • Continuous connectivity to the internet.
How easy is it to operate IoT agritech ?

IoT in agritech uses technology which integrates sensitive physical hardware with analytical software. Analytical dashboard is mostly a software that is processing the data recorded by equipments. Hence a sound technical knowledge of robotics and computer based intelligence is a prerequisite for operating, maintaining and understanding the insights of these valuable equipments.

I am a food processor who owns several farms throughout the world. How can I integrate IoT for multiple farm management?

Since IoTs require physical devices, each farm will need to install their own set of sensors and bots which will record the data related to that farm only. So every farm will have their own separate dashboard for viewing the insights. Integrating and scaling IoT for several farms in a single platform is not possible unlike SaaS agritech such as CropIn which lets you integrate and manage multinational operations through a single platform.

x

SUBSCRIBE NOW

Get regular updates on AgriTech trends, global news and the agri ecosystem