Smart farming: How IoT, robotics, and AI are tackling one of the biggest problems of the century

Smart farming: How IoT

The world's human population currently stands at around 7.6 billion and is projected to reach 11.2 billion by 2100. We will therefore need a food production and distribution system that can accommodate another 3.6 billion people—ideally while consuming as little additional land and leaving as small an environmental footprint as possible, in order to maintain vital ecosystem services and conserve Earth's remaining wildlife.

That's clearly a challenge given that around half of the world's habitable land is under agriculture of some kind—with a high proportion of this used for livestock farming (Figure A).

In a widely reported recent study, Poore and Nemecek (2018) note that a shift away from meat and dairy consumption would go a long way towards relieving pressure on agricultural land and reducing environmental impact: "Meat, aquaculture, eggs, and dairy use ~83% of the world's farmland and contribute 56 to 58% of food's different emissions, despite providing only 37% of our protein and 18% of our calories."

Moving to a diet that excludes animal products, say the study's authors, could reclaim 3.1 billion hectares of global farmland (a 76% reduction), while reducing food's greenhouse gas emissions by 6.6 billion metric tons of CO2eq (a 49% reduction), among other environmental benefits.

Of course, it will take time to effect a major shift in dietary preferences—primarily in developed countries—and global land use patterns, although emerging technologies like lab-grown meat may have an increasingly important role to play here.

On the crops side, big advances in production have been made in recent decades, and modern technology is poised to deliver even more.

Farming output can increase in two basic ways: By increasing the yield per unit area (intensification), or by expanding the area under cultivation (extensification). Increased cereal production has largely been achieved by intensification over the last 50 years (Figure B). Only 16% more land was used for cereals in 2014 than in 1961, for example, while global cereal production increased by 280%. During the same period, the world's population increased 136%, which means that cereal production per person has increased even as the population has more than doubled.

These increases were largely delivered by the post-WW2 Green Revolution—a suite of technologies and farming practices involving high-yielding crop varieties, agro-chemicals (fertilisers, herbicides, and pesticides), irrigation, and mechanisation. Industrial-scale agriculture, often using genetically modified (GM) crops, has undoubtedly delivered many benefits, but there are costs too. These include high levels of inputs (which can become pollutants if inefficiently applied), the development of resistance to pesticides and herbicides, and the use of large, expensive, and environmentally damaging farm machinery.

These and other issues have sparked interest in sustainable intensification, where the goal is to increase production from existing farmland while minimising environmental damage, thereby maintaining the land's capacity to continue producing food, and also helping to preserve biodiversity.

Precision agriculture, also known as "smart farming" or "precision farming," is a key component of sustainable intensification. This combines remote sensing, IoT devices, robotics, big data analytics, artificial intelligence, and other emerging technologies into an integrated high-resolution crop production system.

One of the biggest drawbacks of industrial-scale farming is the use of large, heavy machinery such as tractors, sprayers, and harvesters, which compact the soil and compromise a crop plant's ability to develop a healthy root system. Soil compaction is an important factor—perhaps the important factor—in the slowing of crop yield increases that has been observed in recent decades—here, for example in the UK (Figure C).

Another drawback of industrial-scale farming is its low resolution.

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