After the flood making information beautiful
Agri-TechE 
To survive in a complex world humans have evolved the skill to extract information quickly from patterns. This ability is exploited by infographics, graphics that display data as pictures. Familiar examples include the London Underground map, which supports navigation, and the Met Office maps, which allow weather prediction.
After the flood is now taking this type of data visualisation to a new dimension with artificial intelligence. It takes insights from multiple interactions (people-machine and machine-machine) and displays the findings as deceptively simple dashboards.
Personalised food production
After the flood’s Chairman Nick Cross (pictured right), who also manages his family farming business in Suffolk, explains: “Traditional data analytics are based on collecting data and then providing retrospective insights.
“We are moving into a new era of active data that uses real-time data to provide intelligent services. Perhaps there will come a time when food production will be personalised!”
Instead of creating static images using historical data, After the flood creates a dynamic interpretation of live data. This allows fast reactions and the ability to create systems that learn from experience to respond to changes in their environment.
Within agri-food this could be using customer buying behaviours to predict demand for perishable goods, or monitoring fungal spores and weather conditions to allow preventative, precision spraying.
Nick continues: “I think there will be exciting opportunities to create intelligent data flows between customers, stores and the producers themselves, allowing farmers to be more responsive to specific consumers’ tastes and dietary needs.”
Information is beautiful
After the flood has won an ‘Information is Beautiful’ award for its London Squared Map (see below)
In partnership with Future Cities Catapult, After the flood turned London’s boroughs into a choropleth – or series of shaded cells – that can contain numerous types of data more effectively than a traditional geographical map.
The London Squared Map allows data to be compared across boroughs very easily, and governmental and other agencies are able to edit it to create their own versions for their web pages; for example the London Fire Brigade is one of several organisations that now use it. Some versions even place Instagram images inside the squares.
Managing for the public good
Nick says: “Who knows how the application of AI will really play out with farmers at the sharp end. If you go back 15 years or so, few people would have predicted the impact of cameras on mobile phones and how this has changed the way we live and interact.
“There is already a lot of noise about the role of AI in developing efficient crop production techniques.
“My guess is that there will also be exciting opportunities as farmers take on the challenge of managing land resources for the public good – because we will have to develop a much more sensitive, localised and dynamic picture of the impact we’re having on things like soil, climate change and invertebrates.”
Find out more
Nick Cross will be presenting at the Agri-TechE Pollinator “The AI’m of machine learning in agriculture” on 20 February 2018 at The Sainsbury Laboratory, 47 Bateman Street, Cambridge, CB2 1LR.
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