Saving the Bees with Big Data Analytics and AI

29 Jul
Saving the Bees with Big Data Analytics and AI

Saving the Bees with Big Data Analytics and AI

Philip Carnelley IDC

Philip Carnelley
AVP, European Software Group

Read full bio  @Pcarnelley

If bees die out, humans have only four years to live. This statement has been widely quoted and is often attributed to Albert Einstein, although there seems to be no evidence that he actually said it.

But whoever said it, and whether or not the “four years” figure is correct, the sentence points to an incredibly important truth: over three-quarters of food production around the world depends on the actions of natural pollinators (mainly bees); but also, that pollinators are dying out at an alarming rate, around 30% per year. This is jeopardizing our food supply (that’s $600 billion worth of agricultural activity) and 1.4 billion agriculture-dependent livelihoods.

And, no one actually knows why this decline is happening.

There are several plausible hypotheses, including pesticide over-use, global deforestation, the increase in mono-agro practices (farming a single product) and even the actions of individual beekeepers in encouraging the wrong sort of bees (non-indigenous ones) in their hives. It’s probably a combination of these. But no one actually knows.

Evidence is badly, and urgently, needed.

A non-profit organization, The World Bee Project (WBP), has been launched to try to address this problem, backed by scientists from the University of Reading in the UK. Oracle, through its Tech for Good initiative, forms the third leg of the project, supporting the WBP by giving it free consulting, some money for kit (e.g., sensors) and, perhaps most important, use of its cloud storage and analytics tools.

I was lucky enough to visit some of the smart beehives set up as part of the project, near Oracle’s offices in Reading, in the UK (photographed above), and to be briefed on this important and fascinating project.

The smart beehives are wired up to monitor the hives’ weight, temperature, humidity, sound (of the bees) and ambient weather. In some cases there is video recording of bee behaviour, too. The senor controller feeds its data back into the Oracle cloud where the Reading University scientists can access and analyse it to understand more about the bees’ behaviour.

From that quite simple sensor data, a lot can be deduced, thanks to advanced analytics and machine learning — for instance, where the bees are feeding — and that information can be correlated with other data, like what’s growing round about the hive, how the weather has been changing and so on. For example, something that will no doubt appeal to other beekeepers: AI algorithms can deduce when the bees are about to “swarm” — this is predictive maintenance on beehives, in effect.

But of course two beehives can be easily observed. The ambitious goal of this project is global analysis of many hives. The aim of the WBP is to create a “world hive network” of remotely monitored honeybee hives and bumble bee nests. This will generate significant new data on the impact of different factors on the health of bees, such as land use, agricultural practices and forage quality. The aim is to gain a deeper understanding of disease, parasites, predator species, and control measures, in part by comparing what’s going on in different parts of the world, where different factors and outcomes can be observed.

This is where the cloud storage and analytics will really come into its own, enabling global storage, access and analysis of the information gathered — and sufficient computing power to really make something of that data, using AI on the Big Data generated by the world hive network sensors.

So, for the global economy, for the bees themselves, for food producers and food consumers (that’s all of us), it’s great to see this collaboration between a non-profit group, academia and the tech industry to address this issue. It’s also pleasing to see Big Data analytics proving its worth in this way.

If you want to know more about the impact of Big Data Analytics and AI, please contact Philip Carnelley or go to https://uk.idc.com/trends/artificial-intelligence.

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