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As it strives to attract young people into the agriculture value chain, Farmers Pride International has joined both Climate Smart and Smart Farming Generation.

"Smart farming" is an emerging concept that refers to managing farms using technologies like the Internet of Things (IoT), robotics, drones and Artificial Intelligence (AI) to increase the quantity and quality of products while optimizing the human labour required by production.

This is a management concept focused on providing the agricultural industry with the infrastructure to leverage advanced technology – including big data, the cloud, and the internet of things (IoT) – for tracking, monitoring, automating and analysing operations.

Climate-smart agriculture involves farming practices that improve farm productivity and profitability, help farmers adapt to the negative effects of climate change and mitigate climate change effects, e.g. by soil carbon sequestration or reductions in greenhouse gas emissions.




Smart Farming Technologies

What is a Smart Farm?

Smart Farming is an emerging concept that refers to managing farms using modern Information and Communication Technologies to increase the quantity and quality of products while optimizing the human labour required.

Among the technologies available for present-day farmers are:

  • Sensors: soil, water, light, humidity, temperature management

  • Software:  specialized software solutions that target specific farm types or use case agnostic IoT platforms

  • Connectivity: cellularLoRa, etc.

  • Location: GPS, Satellite, etc.

  • Robotics: Autonomous tractors, processing facilities, etc.

  • Data Analytics: standalone analytics solutions, data pipelines for downstream solutions, etc.

How are these technologies already changing agriculture, and what new changes will they bring in the future?

Autonomous and Robotic Labour

Replacing human labour with automation is a growing trend across multiple industries, and agriculture is no exception. Most aspects of farming are exceptionally labor-intensive, with much of that labour comprised of repetitive and standardized tasks—an ideal niche for robotics and automation.

We’re already seeing agricultural robots—or AgBots—beginning to appear on farms and performing tasks ranging from planting and watering, to harvesting and sorting.  Eventually, this new wave of smart equipment will make it possible to produce more and higher quality food with less manpower.

Driverless Tractors

The tractor is the heart of a farm, used for many different tasks depending on the type of farm and the configuration of its ancillary equipment.  As autonomous driving technologies advance, tractors are expected to become some of the earliest machines to be converted. 

In the early stages, human effort will still be required to set up field and boundary maps, program the best field paths using path planning software, and decide other operating conditions.  Humans will also still be required for regular repair and maintenance.

Reducing Labour, Increasing Yield and Efficiency

The core concept of incorporating autonomous robotics into agriculture remains the goal of reducing reliance on manual labour, while increasing efficiency, product yield and quality.

Unlike their forebears, whose time was mostly taken up by heavy labour, the farmers of the future will spend their time performing tasks such as repairing machinery, debugging robot coding, analysing data and planning farm operations.

As noted with all of these agbots, having a robust backbone of sensors and IoT built into the farm’s infrastructure is essential. The key to a truly “smart” farm relies on the ability of all the machines and sensors being able to communicate with each other and with the farmer, even as they operate autonomously.

What farmer wouldn’t want a bird’s eye view of their fields?  Where once this required hiring a helicopter or small aircraft pilot to fly over a property taking aerial photographs, drones equipped with cameras can now produce the same images at a fraction of the cost.

In addition, advances in imaging technologies mean that you’re no longer limited to visible light and still photography.  Camera systems are available spanning everything from standard photographic imaging, to infrared, ultraviolet and even hyperspectral imaging. Many of these cameras can also record video.  Image resolution across all these imaging methods has increased, as well, and the value of “high” in “high resolution” continues to rise.

All these different imaging types enable farmers to collect more detailed data than ever before, enhancing their capabilities for monitoring crop health, assessing soil quality and planning planting locations to optimize resources and land use.  Being able to regularly perform these field surveys improves planning for seed planting patterns, irrigation and location mapping in both 2D and 3D.  With all this data, farmers can optimize every aspect of their land and crop management.

But it isn’t just cameras and imaging capabilities making a drone-assisted impact in the agricultural sphere—drones are also seeing use in planting and spraying.

The Connected Farm: Sensors and the IoT

innovative, autonomous agbots and drones are useful, but what will really make the future farm a “smart farm” will be what brings all this tech together: the Internet of Things.

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Smart Farming

The IoT-Based Smart Farming Cycle


The core of IoT is the data you can draw from things (“T”) and transmit over the Internet (“I”).


To optimize 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 ambient conditions. Smart farming follows a cycle like this one:

1. Observation 

Sensors record observational data from crops, livestock, soil, or the atmosphere. 

2. Diagnostics

 The sensor values are fed to a cloud-hosted IoT platform with predefined decision rules and models—also called “business logic”—that ascertain the condition of the examined object and identify any deficiencies or needs.

3. Decisions 

After issues are revealed, the user and/or machine learning-driven components of the IoT platform determine whether location-specific treatment is necessary and if so, which.

4. Action 

After end-user evaluation and action, the cycle repeats from the beginning.

IoT Solutions to Agricultural Problems

Many believe that IoT can add value to all areas of farming, from growing crops to forestry. In this article, we’ll talk about two major areas of agriculture that IoT can revolutionize:

  1. Precision farming

  2. Farming automation/robotization

1. Precision Farming

Precision farming, or precision agriculture, is an umbrella concept for IoT-based approaches that make farming more controlled and accurate. In simple words, plants and cattle get precisely the treatment they need, determined by machines with superhuman accuracy. The biggest difference from the classical approach is that precision farming allows decisions to be made per square meter or even per plant/animal rather than for a field.

By precisely measuring variations within a field, farmers can boost the effectiveness of pesticides and fertilizers, or use them selectively.

2. Precision Livestock Farming

As in the case of precision agriculture, smart farming techniques enable farmers better to monitor the needs of individual animals and to adjust their nutrition accordingly, thereby preventing disease and enhancing herd health.

Large farm owners can use wireless IoT applications to monitor the location, well-being, and health of their cattle. With this information, they can identify sick animals, so that they can be separated from the herd to prevent the spread of disease.

Automation in Smart Greenhouses

Traditional greenhouses control the environmental parameters through manual intervention or a proportional control mechanism, which often results in production loss, energy loss, and increased labor cost.

IoT-driven smart greenhouses can intelligently monitor as well as control the climate, eliminating the need for manual intervention. Various sensors are deployed to measure the environmental parameters according to the specific requirements of the crop. That data is stored in a cloud-based platform for further processing and control with minimal manual intervention.

Agricultural Drones

Agriculture is one of the major verticals to incorporate both ground-based and aerial drones for crop health assessment, irrigation, crop monitoring, crop spraying, planting, soil and field analysis and other spheres.

Since drones collect multispectral, thermal and visual imagery while flying, the data they gather provide farmers with insights into a whole array of metrics: plant health indices, plant counting and yield prediction, plant height measurement, canopy cover mapping, field water pond mapping, scouting reports, stockpile measuring, chlorophyll measurement, nitrogen content in wheat, drainage mapping, weed pressure mapping, and so on.

Importantly, IoT-based smart farming doesn’t only target large-scale farming operations; it can add value to emerging trends in agriculture like organic farming, family farming, including breeding particular cattle and/or growing specific cultures, preservation of particular or high-quality varieties etc., and enhance highly transparent farming to consumers, society and market consciousness.

Internet of Food, or Farm 2020

If we have the Internet of Things (IoT) and the Internet of Medical Things (IoMT), why not have one for food? The European Commission project Internet of Food and Farm 2020 (IoF2020), a part of Horizon 2020 Industrial Leadership, explores through research and regular conferences the potential of IoT technologies for the European food and farming industry.

IoT has fostered the belief that a smart network of sensors, actuators, cameras, robots, drones, and other connected devices will bring an unprecedented level of control and automated decision-making to agriculture, making possible an enduring ecosystem of innovation in this eldest of industries.

Third Green Revolution

Smart Farming and IoT-driven agriculture are paving the way for what can be called a Third Green Revolution.


Climate-Smart Agriculture

Over the next 20 years, increasing productivity and income from smallholder crop, livestock, fishery and forestry production systems will be key to achieving global food security.


Most of the world’s poor are directly or indirectly dependent on agriculture, and experience has shown that growth in agriculture is often the most effective and equitable strategy for reducing poverty and increasing food security. Climate change multiplies the challenges of achieving the needed growth and improvements in agricultural systems, and its effects are already being felt. Climate-Smart Agriculture (CSA) is an approach to dealing with these interlinked challenges in a holistic and effective manner. This brief is intended to give an overview of the approach and its main features, as well as answers to frequently asked questions about it.

Climate-smart agriculture is an approach to help guide actions to transform and reorient agricultural systems to effectively and sustainably support the development and food security under a changing climate. “Agriculture” is taken to cover crop and livestock production, and fisheries and forest management. CSA is not a new production system – it is a means of identifying which production systems and enabling institutions are best suited to respond to the challenges of climate change for specific locations, to maintain and enhance the capacity of agriculture to support food security in a sustainable way.

The concept was first launched by FAO in 2010 in a background paper prepared for the Hague Conference on Agriculture, Food Security and Climate Change (FAO, ”Climate-Smart” Agriculture Policies, Practices and Financing for Food Security, Adaptation and Mitigation. 2010), in the context of national food security and development goals, to tackle three main objectives (FAO, Climate-Smart Agriculture Sourcebook. 2013): • Sustainably increasing food security by increasing agricultural productivity and incomes; • Building resilience and adapting to climate change • Developing opportunities for reducing greenhouse gas emissions compared to expected trends

Sustainably increasing agricultural productivity and incomes


Around 75% of the world’s poor live in rural areas and agriculture is their most important income source. Experience has shown that growth in the agricultural sector is highly effective in reducing poverty and increasing food security in countries with a high percentage of the population dependent on agriculture (World Bank, World Development Report. 2008). Increasing productivity as well as reducing costs through increased resource-use efficiency are important means of attaining agricultural growth. “Yield gaps” indicating the difference between the yields farmers obtain on farms and the technically feasible maximum yield, are quite substantial for smallholder farmers in developing countries (FAO,


The State of Food and Agriculture. 2014). Similarly, livestock productivity is often much lower than it could be. Reducing these gaps by enhancing the productivity of agro-ecosystems and increasing the efficiency of soil, water, fertilizer, livestock feed and other agricultural inputs offers higher returns to agricultural producers, reducing poverty and increasing food availability and access. These same measures can often result in lower greenhouse gas emissions compared with past trends.

Building resilience to climate change

It is possible to reduce and even avoid these negative impacts of climate change – but it requires formulating and implementing effective adaptation strategies. Given the site-specific effects of climate change, together with the wide variation in agro-ecologies and farming, livestock and fishery systems, the most effective adaption strategies will vary even within countries. A range of potential adaptation measures have already been identified which can provide a good starting point for developing effective adaptation strategies for any particular site. These include enhancing the resilience of agro-ecosystems by increasing ecosystem services through the use of agro-ecology principles and landscape approaches. Reducing risk exposure through diversification of production or incomes, and building input supply systems and extension services that support efficient and timely use of inputs, including stress tolerant crop varieties, livestock breeds and fish and forestry species are also examples of adaptation measures that can increase resilience.

Developing opportunities to reduce greenhouse gases emissions compared to expected trends


Agriculture, including land-use change, is a major source of greenhouse gas emissions, responsible for around a quarter of total anthropogenic GHG emissions. Agriculture contributes to emissions mainly through crop and livestock management, as well as through its role as a major driver of deforestation and peatland degradation. Non-CO2 emissions from agriculture are projected to increase due to expected agricultural growth under business-as-usual growth strategies.

There is more than one way agriculture’s greenhouse gas emissions can be reduced. Reducing emission intensity (e.g. the CO2 eq/unit product) through sustainable intensification is one key strategy for agricultural mitigation (Smith, P. et al. in Climate Change 2014: Mitigation of Climate Change Ch. 11. IPCC, Cambridge Univ. Press, 2014). The process involves the implementation of new practices that enhance the efficiency of input use so that the increase in agricultural output is greater than the increase in emissions (Smith, P. et al. in Climate Change 2014: Mitigation of Climate Change Ch. 11. IPCC, Cambridge Univ. Press, 2014).

Another important emissions reduction pathway is through increasing the carbon-sequestration capacity of agriculture. Plants and soils have the capacity to remove CO2 from the atmosphere and store it in their biomass – this is the process of carbon sequestration. Increasing tree cover in crop and livestock systems (e.g. through agro-forestry) and reducing soil disturbance (e.g. through reduced tillage) are two means of sequestering carbon in agricultural systems. However, this form of emissions reduction may not be permanent – if the trees are cut or the soil plowed, the stored CO2 is released. Despite these challenges, increasing carbon sequestration represents a huge potential source of mitigation, especially since the agricultural practices that generate sequestration are also important for adaptation and food security.

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