Smart farming overview

Smart Farming

Smart Farming – The United Nations Food and Agricultural Organisation (FAO) has predicted that the global population will hit 8 billion people by 2025 and by 2050, 9.6 billion. In order to feed this population, there must be a 70% increase in food production. This is a somewhat worrying statistic as there are barriers to fulfilling this requirement. These include limited availability of land for arable farming; the changing climate; fresh water supplies; and the increasing average age of farmers brought about by fewer young people entering the industry as a result of urbanisation.

In order to meet these challenges, the FAO wants to see farming sectors equipped with 21st-century techniques and digital technologies. This will remove reliance on farmer expertise and intuition and replace it with fact-based Information and Communication Technology (ICT).

Precision agriculture, or smart farming, is based upon the use of technologies established in other industries such as environmental monitoring for pollution or fleet management telematics.


Optimisation of land

Smart farms are needed to ensure that each hectare of land used for farming is working to its optimum, with farmers implementing the most up to date methods to achieve the best financial return, quality of product and quantity.

Smart farming, similar to other M2M implementations, uses ICT-based support systems backed up by real-time data gleaned from big data, GPS analysis, and other relevant sources. This system of farming will give information on all stages of production which has not been possible historically. It will ensure a better understanding as to what is happening out in the fields in order to improve efficiency and prevent waste.

The farmers themselves are an important part of precision agriculture but the skill sets required are shifting, and it is vital that they are trained in these technological solutions in order to increase the food yields needed to feed the global population. Farmers need knowledge of climate forecasting, environmental controls, robotics and GPS technology, to name but a few.


M2M implementation in smart farming

Information is gathered from IT systems and is subsequently collated and analysed to produce a response appropriate to the data received. This information is then passed to farmers to allow them to take appropriate action. This information may be related to crop behaviour, machine status or animal behaviours. Farmers already submit copious quantities of information for analysis, including soil mapping, fertiliser use, weather data and animal health, and this is used to influence farming decisions taken within the M2M framework. Data is at the heart of this technologically advanced smart farming system.


Data storage

The UK Government has tried to ensure that there is a regulatory framework in place for other ‘smart’ industries, for example, smart metering. Considerations such as customer privacy, data ownership and sharing of data for other purposes is as relevant to the agricultural sector and smart farming as it is to the electricity industry. It has been found that farmers are reluctant to share data collected on their farms and so trust needs to be established between the farmers and those analysing and using the data collected. Horizon 2020 and FP7 initiatives, funded by the EU, are concerned with these very issues.



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