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What is smart farming

Smart farming, also known as precision agriculture or precision farming, is the future of agriculture. It involves the use of technology such as the Internet of Things (IoT), sensors, drones, satellite imagery, GPS technology, and data analytics to monitor and manage agricultural processes to increase efficiency in food production. 

Traditional farming vs. smart farming

While traditional farming methods have sustained our population for centuries, the pressures of globalisation and climate change have created a need for more efficient, precise, and environmentally sustainable practices.  

Traditional farming methods, which rely heavily on manual labour, are now seen as inefficient and outdated as they come with costly labour requirements and resource inefficiency.  

In contrast, smart farming uses advanced technologies, such as IoT-powered systems, to enhance efficiency and precision. The integration of devices like sensors, drones, and satellite imagery leads to data-driven decisions that reduce overheads, the early detection of disease that improves crop yields and animal welfare. Not to mention the environmental improvements that precisions farming techniques have with maintaining biodiversity conservation.  

What are the advantages of smart farming?

The shift from traditional to smart farming holds enormous potential for agriculture. Smart farming not only reduces environmental impact and waste but it also improves crop quality and yield. The integration of technology also helps farmers adapt to shifting demands and stay compliant with environmental regulations, promoting sustainability and long-term agricultural success.

As technology continues to evolve, researchers are continually exploring innovative methods and tools to make farming even more efficient and sustainable.  

Smart farming for cropping  
By giving cropping farmers precise control over their operations through the use of real-time data collection, they can make smarter decisions on planting, irrigation, fertiliser and pest control. For example, by continually monitoring soil conditions, the optimal planting time can be determined for crop rotations, enhancing soil fertility and productivity.  

The Grains Research and Development Corporation (GRDC) has invested in a Post Doctoral Fellowship focused on maximising crops and minimising weeds with smart phase farming, exploring how a precision agriculture pasture management system would impact weed growth.  

Smart farming for livestock  
Smart farming is improving livestock management by integrating advanced technologies to monitor and manage animal health, grazing strategies, and pasture conditions. For instance, the Australian Wool Innovation (AWI) is investing in research to remotely monitor sheep with the use of solar ear tags.  

The AWI Smart Tags enable producers to make informed management decisions, as they can monitor animal health, receive wild dog alerts, improve their grazing strategy and better manage reproduction.  

Similarly, Meat and Livestock Australia (MLA) led an improved pasture management systems project, which has engaged producers to demonstrate how feed budgeting and remote sensing pasture assessment tools can improve pasture management systems for cattle producers.  

The rise of smart farming technologies

Smart farming technologies have evolved as tools to optimise agricultural operations. Some of the most impactful and user-friendly smart farming solutions in the market include:

  • Machine learning: Self-learning technologies empower farmers to forecast changes in climate conditions, soil and water parameters, carbon levels, as well as the spread of diseases and pests. For example, Bitwise Agronomy uses computer vision, machine learning, and artificial intelligence (AI) to accurately calculate crop elements like yield, shoot length and ripeness.  
  • Remote monitoring and control systems: Highly sensitive sensors enable farmers to monitor minute fluctuations in environmental conditions, livestock movements, irrigation and security systems in real-time. For example, Protag’s smart livestock tag allows farmers to remotely monitor the health and location of their livestock.  
  • Drones: Producers can remotely monitor paddocks from afar. For example, Drone Hand enables remote livestock monitoring through an autonomous drone flight app.  
  • Satellite Imagery: Enabling crop and weather monitoring, soil analysis and yield projection over large areas. For instance, the Cotton Research and Development Corporation (CRDC) is developing a platform for monitoring and analysing cotton canopy nitrogen levels and projecting yield using calibrated aerial and satellite imagery.
  • Internet of Things (IoT): This allows for the integration of all tools and solutions into a cohesive system, enabling seamless data exchange and automated actions based on established patterns. For example, Mirragin: Project Isidore have developed two systems that solve internet connectivity challenges in rural areas.  
  • AI-powered technologies: These are systems or tools that use AI algorithms and techniques to perform tasks or make decisions autonomously. For example, Yarta’s AI-powered consultant offers farmers personalised recommendations and insights, facilitating informed decision-making and accelerating productivity.

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