4 Easy Steps to Integrate IoT Based Smart Farming

4 Easy Steps to Integrate IoT Based Smart Farming


Smart Farming and the internet of things (IoT) will be key to the Australian agricultural industry, increasing food production in order to feed a global population of 9.6 billion by 2050.

Smart farming in Australian agriculture will allow farmers to increase efficiency, reduce waste and improve productivity. The use of IoT combined with machine learning (ML) can transform agriculture by making better-informed decisions and enabling greater market research regarding inputs and outputs in the Australian agriculture and farming sectors.

How to integrate Australian agriculture and IoT-Based Smart Farming in 4 easy steps

At the core of IoT and smart farming in Australian agriculture is the data that a farmer can retrieve from things (“T”) and transmit over the Internet (“I”). To optimise Australian agriculture and the farming process, IoT devices installed on a farm should collect and process data in a repetitive cycle that enables farmers to react quickly to emerging issues and changes in conditions.

Steps for integrating smart farming in Australian agriculture in simplistic terms will follow a cycle similar to the following:

Step 1. Installation & Observation

Installation of devices and sensors in Australian agriculture today will enable farmers to record observational data from the crops, livestock, soil, or atmosphere which will then be observed and analysed. It is feasible that in the very near future, devices will be able to detect crop type and pasture type by satellite.

Step 2. Diagnostics

Data captured from devices and sensors are fed into cloud-hosted IoT platforms with predefined decision rules and models in place, whereby smart farming technology can ascertain the condition of the examined object and identify any deficiencies or needs. There are smart farming solutions for all forms of Australian agriculture; cropping, livestock, horticulture, dry land, irrigation and or combinations of above.

Step 3. Decisions

After the analysis and revelation of issues or needs, the farmer, and/or machine learning-driven components of the IoT platform can determine location-specific treatment, application or course of action should be taken. Questions smart farming can help answer include:

  • “Do I need to fertilise? When, where, how much, what type? Does all of my paddock need the same amount? What areas of my property have nutrient deficient soil?”
  • Is my crop at risk from frost? What loss could I incur? Do I need crop derivative protection for frost?
  • Is my weight gain on livestock on track to meet forward contracts with processor or feedlots?

Step 4. Action 

After farmer evaluation and implementation of specific action identified as required, the cycle can then repeat from step one. This also enables greater depth of knowledge gained from each process cycle to drive more in-depth analysis and insight, fine-tuning the farming practice and input application which can improve cost efficiency and product output.

Proliferating Smart Framing and IoT

Smart Farming and use of IoT enables greater precision in the timing of farm activities and decisions, which is critical in Australian agriculture. Smart farming and IoT has the potential to enhance the accuracy of input and output management within supply chains. The sharing of information within the ecosystem of smart farming businesses can lead to greater profitability for the Agricultural industry as a whole. The concept of farms working in “silos” will be eradicated, and a once traditional industry will transform into a modern, sophisticated network of smart farming enterprises, poised to meet and exceed expectations from the growing global population.

Australian Agriculture via Smart Farming and IoT will lead to improved efficiency and productivity. Smart farming and technology has the opportunity to put farmers into a position of being price makers and not price takers.

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This article was originally published on www.kg2.com.au on May 13, 2020.