I don’t want to live in a world where there’s no organic food. Do you?
We will need to produce 70% more food than we do today to feed 2.3 billion people that will be added to the world’s population by 2050. And we will have to do this in spite of increasing effects of climate change, scarcity of resources, and growing levels of inequality around the world.
How do we ensure increase in food production? How do we make sure we produce enough food to cater to the fast-growing population, whether rich or poor?
We cannot continue doing things the way we do and expect improved results.
We must evaluate our current processes and actions and find ways to improve on the way we treat the earth and agriculture which essentially keeps us alive.
For many years now, agriculture as a profession has been a fertile, but not very attractive industry. This has become increasingly pronounced in recent years.
In the Global Opportunity Report of 2016, smart agriculture was identified as the opportunity with the biggest potential of positive impact on society – ahead of the digital labour market and closing the skills gap.
Different countries have different needs and pain points that needs to be addressed.
What may seem like a molehill in a developed country could easily be a mountain in a developing country.
Example: A country like Norway is exploring ways to incorporate renewable energy into fish farming in a bid to reduce carbon emission while Nigeria, my home country, hasn’t figured out how to generate enough electricity for residents and businesses.
Farmers around the world face different challenges and while some of these challenges are unique to specific farmers in specific countries, a general problem they all face is increasing crop yield – producing more.
How do they increase output and automate production processes? How do they reproduce better seeds, understand the weather better, improve the quality of the soil, all so their crops can grow in better conditions?
These are some of the questions that the introduction of artificial intelligence and machine learning into the agricultural sector can answer.
With the help of data scientists and machine learning, farmers can solve and answer most of the questions above using the predictive abilities of artificial intelligence.
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According to IBM, 90% of all crop losses are due to weather problems. By feeding weather data into machine learning algorithms, farmers will be able to predict the weather, know when to plant and how best to avoid damage.
Farmers can feed simple bits of unstructured data like what the weather is like on a particular day and how it has affected their crops into an artificial intelligence algorithm such as WorkFusion‘s. This algorithm takes this data, works through it repeatedly until it notices patterns and starts to make the most accurate predictions possible. This way, the farmers know what is coming and are prepared for it.
In India, a Bengaluru-based startup named CropIn Technology Solutions offers a B2B farm management software that uses “Machine Learning, Satellite Monitoring, Data Storage, and Weather Analysis technology mechanism to maximize yield per acre whilst identifying the risk and favourable areas for cultivation,” according to Entrepreneur. Its software serves big seed companies, crop insurance providers, governments, and banks.
Farmers are not trained normally trained to gather and analyse data, it’s why there need to be more startups and companies that offer this as a service.
People who already have data science competence need to turn their attention to the fruitful field of agriculture. IBM is doing so with IBM Watson Machine Learning, but they are just one company.
More entrepreneurs need to arise to this challenge-cum-opportunity to save the planet by focusing on the impact that artificial intelligence can have on agriculture (and food production!) around the world.
Our farmers need people that will help them analyse data around factors like humidity, soil pH, air pressure, precipitation and temperature. These are the factors that will determine plant strength, predict the best time for irrigation, and increase food production in a time when the world really needs it.