M2M and the Future of Farming

M2M and the Future of Farming

As IoT continues to seep into more aspects of our lives, it is enabling significant shifts in how people, businesses, and society as a whole operate. The technology’s budding role in the agriculture industry, in particular, hails the promise of enabling more sustainable agriculture, increasing production for higher yields, and expanding the profit margins of farmers.

This is especially pertinent at a time when, according to the UN, an estimated 690 million people were expected to go undernourished in 2020. As populations continue to grow, food requirements are expected to increase exponentially, and farming will require a radical overhaul.

 

The Dairy Industry is No Cash Cow

Throughout history, farming has always been known to be one of the most arduous and labour-intensive sectors, and this is particularly the case for dairy farming. Undoubtedly you will have seen articles proclaiming the plight of dairy farmers barely getting by or being bullied by supermarkets and other injustices. As a result, governments usually step in, in order to stabilise milk producers as the profit margins are minuscule or non-existent.

However, Smart Farming — otherwise known as precision agriculture— is revolutionising the industry. It is allowing farmers to optimise every step of their processes, enabling them to not only save on costs and in turn generate higher profits but also reduce harmful emissions and mitigate the effect on the environment making for more sustainable farming.

There’s no shortage of success stories. The Smart Farming initiative in Ireland works primarily with smaller farmers in key areas such as energy usage, soil fertility and machinery, to improve their processes. In one of their case studies, optimising machinery by turning off machinery like tractors during idle time and altering tyre pressure to suit the weather and ground conditions together achieved a saving of EUR 365.

They say every little helps, and they weren’t wrong. Overall, that particular farm saved upwards of EUR 8,300. Optimising and automating systems can result in significant savings, even for smaller farms.

 

Key Technologies in the Development of Smart Farms

At its core, precision agriculture involves collating data from hundreds, thousands, or even tens of thousands of devices and then carrying out analysis to enable improved decision making. However, the digital transformation of farms is still at an early stage. According to a report by Eurostat, agricultural applications had been adopted by over half of all those surveyed.

However, the research also showed that these were only used for basic tasks such as obtaining weather information, information on crop monitoring, protection or fertilisation. What’s more, in a survey focused specifically on dairy farmers in Germany, only 18% of those surveyed appeared to have adopted milking robots, 2.6% have adopted feeding robots or automated feeding systems, and only 0.6% have embraced body scoring condition technologies.

Yet when looking at the next ten years, by 2030, 49% of respondents expect to deploy autonomous tractors, 45% plan to have deployed drones, and 43% envision utilising autonomous field robots. If the latter half of respondents were yet to adopt agricultural applications at the time of the survey, this suggests that current standards of data collection and analysis are still heavily reliant on traditional methods and perhaps in some cases the farmer’s own gut feeling.

Additionally, the divide between the data that farmers are currently yielding from precision agriculture and what they expect to have access to in the next ten years seems wide. To achieve a better connected agricultural enterprise and meet their 2030 goals, businesses in the sector will need to begin planning for investment in several areas. Three keys elements that make up the golden triangle of Smart Farming, are a good place to start:

  1. Sensors (or IoT) – everything on the farm can be monitored through the widespread use of sensors strategically placed to optimise operations. Some examples may include pH sensors to measure the soil’s acidity, temperature sensors, and moisture sensors to measure adequate water levels. These all create data and readings that can be used for analysis.
  2. The Network – all these sensors meant nothing without a network with which to unify them so that all the readings and data can be transferred to a central point (either locally or on the cloud). 5G and related technologies will undoubtedly see significant growth within the agricultural sector, especially in connection to developments such as field drones or autonomous tractors.
  3. Analysis of Big Data – the sensors are creating troves of data every day which need to be analysed in a way that lends insights that can be actioned. For example, in order to carry out soil sampling: a pH sensor can monitor over months or even years that in a particular area of a field, the alkalinity is too high, thus being detrimental to crop production. However, by spreading some limestone over the area, the pH can be raised to suitable levels and thus increasing crop yield.

 

Key Connectivity Technologies Identified

Of this golden triangle, investment in improving the network and all-around connectivity is perhaps the most pertinent. The sensors exist, as does the software to analyse the data, however, gaps in network coverage and quality are hampering the development of precision agriculture. These devices and sensors require immense amounts of resources and data speeds, with little tolerance for lag. As the quantity increases too, creating exponential amounts of data, 4G is being pushed to its limits.

The latest 5G technology is well placed to meet this growing demand in data. It’s the revolution networks need and it is enabling autonomous farms to become more of a widespread reality. It is also increasingly essential for enabling edge infrastructure, where computing can take place on the device rather than remotely via the cloud, which cuts down latency and is already proving essential for machinery such as autonomous tractors. In addition, with the introduction of real-time two-way communications and accuracy, data can be shared more quickly and efficiently. Meanwhile, faster and more accurate management decision making based on fresh data will improve performance, productivity and increase yields.

As the number of IoT devices increases exponentially, it has become more important than ever to maintain low latency, unbroken connectivity. D-Link’s range of M2M connectivity solutions enables equipment to connect to the Internet securely and with dual-SIM and WAN failover support to ensure constant connection. While the D-Link Edge Cloud Solution (D-ECS), for example, offers essential management features for optimising cellular connectivity for a wide range of M2M and IoT devices crucial in a precision agriculture scenario, keeping a handle on things even as operations expand and become increasingly complex.

Precision agriculture holds a lot of promise, especially in terms of increasing yields to meet the nutritional needs of growing populations whilst being sustainable in the long term. Whether it can meet these promises will depend on a number of factors, one of which is investment in next-generation connectivity, specifically M2M. The next decade will prove an interesting one, with even more developments expected in the agricultural sector, many of which will rely on the continued and widespread development of M2M, and how policy facilitates its utilisation around the globe.

Neil Patel, Director European Marketing and Business Development

Voix très réputée dans l'industrie du réseau, Neil Patel est le fer de lance du marketing et du développement commercial européens de D-Link depuis près d'une décennie.