Italy, as most Countries in the world, used to be a country of farmers and farmers were at the same time considered “dense” and “field-smart”. We even have a saying in Italian about the “intelligenza contadina” -farmer intelligence- meaning a kind of intuitive grasp of reality, been smart on concrete things.
Indeed, farming has been an exercise in data analytics well before we had an idea of what data analytic is about. Farming means understanding the soil and its changes over time, make educated guesses on weather (wind, rain, sunlight…) watch out for pests and a sense of timing… Couple this with a sense of economics, market evolution, availability of seeds, fertilisers, tools and you get avery complex environment. No wonder that sometimes the yields were unsatisfactory.
Experience was the guiding beacon, but even that failed sometime.
The industrial revolution drained farms from workers enrolling them in factories but that would not have been possible if at the same time new tools could dramatically change the workforce need in agriculture. Nowadays agriculture productivity is hundred times more than 2000 years ago (which, by the way, remained the same till the industrial revolution in Europe). In the last 50 years productivity has multiplied by 5 times, thanks to tools, fertilisers and seed selection.
These successes are not sufficient to tackle the growth in population worldwide and innovation seems to be the way to further improve productivity.
Artificial Intelligence, particularly data analytics harvesting the huge amount of data (and data streams), seems to be a must in this search for increased productivity. As shown in the figure, farms are incredible generators of data points, thanks to pervasive use of IoT, including aerial imagining taken from drones. Other streams of data come from weather forecast, biological monitoring (pests, seeds type and so on). The information emerging from data analytics are used in planning, in early detection of plant diseases, monitoring of weeds resulting in higher yield and less use of pesticides and herbicides. As the number of farmers shrinks, robotisation increases and that has been the trend for the last two decades. What could have been robotised easily has been robotised. Further penetration calls for smarter robots that can understand the environment and adapt their behaviour. This is where AI comes in.