How big data can revolutionise agriculture in poor countries

News IT @it

9:41 am

8 January 2019

One in every nine people in the world suffers from hunger. Despite worldwide efforts and the creation of the UN’s Sustainable Development Goals, one of which is the Zero Hunger goal, to be achieved by 2030, the situation is getting worse rather than better. In the space of three years, we’re back to the levels of a decade ago.

The worst-affected regions of Sub-Saharan Africa, South-East Asia and Latin America have the highest demographic rate and rely almost exclusively on the agricultural sector. These are vulnerable areas where a freak weather event is all it takes to paralyse the production of crops like wheat, corn, rice and more. These are the raw materials upon which the entire local economy depends – and shortages can leave thousands upon thousands of people with empty stomachs.

 

Bottom-up approach to understanding the situation

Now, people are starting to try to tackle the problem of hunger and promote rural development from the bottom up, starting with the smallest players – tiny regional producers and small farms. The Food and Agriculture Organisation (FAO), Melinda Gates Foundation and a number of local governments are currently in the process of launching a project with a budget of $500 million designed to help these small-scale producers.

At the heart of the initiative is a push to correct the massive lack of information on the millions of rural dwellers and producers who live in conditions of poverty. Currently, these people are virtually invisible in the eyes of surveys, statistics and future planning. We know virtually nothing about their properties, their methods of growing and rearing, their harvests or their problems. Yet gaining a deep understanding of local practices, the variety of plants and seeds grown and the earnings taken and sacrifices made by each and every agricultural worker is vital if we are to measure the impact of action implemented and plan future steps with full knowledge of the facts. And this is where big data comes in.

 

Meticulous analysis: the role of data

The information gap we’ve discussed is the clearest sign we have that the monitoring strategies employed thus far have failed. Such strategies rely on reports provided by the countries involved, but these can often be incomplete and are not carried out regularly enough, meaning that their information quickly becomes obsolete. According to the experts, it’s vital that we adopt a more systematic, meticulous approach to respond to the urgent need to gather new, better data.

The first thing to do is set precise key parameters. The team behind the new project backed by the FAO, for example, looked at livestock farmers’ access to veterinary services, discovering that this was extremely limited (if not non-existent) in the poorest areas. It’s this kind of evidence that policy experts cannot afford to ignore.

Secondly, it’s important that we take advantage of all available forms of technology as they become more accessible. For instance, the well-known agricultural machinery producer John Deere has for years been supporting initiatives around monitoring crops using sensors and subsequently combining this information with data gathered by orbiting satellites (or drones) to create a detailed snapshot of the crop situation in a specific region. One of the results of such initiatives has been to identify exactly where it is necessary to use pesticides, thus leading to a saving in time in money by focusing solely on at-risk areas and avoiding unnecessary use elsewhere.

Clearly, it’s also of fundamental importance that any information gathered is processed transparently and made available (in an easy-to-understand way) to agricultural workers. As such, it’s not just data we need, but also the infrastructure required to share it, communicate it and ensure it can actually be used.

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