In short, the Internet of Things, big data and Artificial Intelligence is being used to interpret the language of bees to gain a true understanding of biodiversity and environmental health.
“We’re starting to understand the characteristics of communication in the beehive,” says John Abel, vice president of cloud and technology at Oracle for the UK, Ireland and Israel.
“Already, we understand certain actions of the bee. For example, flying in a figure 8 is not random. It is very specific. Certain tones bees use will indicate food or water. The way the bee shudders and rotates within the figure 8 will indicate to the rest of the colony what it found and where it is. If the heat or sound in the hive changes, it can mean the hive is preparing to swarm.
“If the queen bee is too large to fly – because when it is in the hive, its job is to create the future bees of the hive – the queen’s workers have to prepare the queen for flying, and that takes 20 odd days. You can hear a difference in the noise when they are doing that. If the queen not getting a lot of food, it’s preparing to lose weight to leave the hive.
“Thanks to artificial intelligence analysing the acoustic recordings in the hive, we can hear all of this clearly from the sound in the hive. Are they talking? No. But are they communicating? Definitely.”
If it were left only to AI, however, the project would be a dead end. Experts from Reading University and the World Bee Project initially visited Oracle’s sprawling campus in Reading to teach the machines the patterns that they already understood. The machines, in turn, used these patterns to build further knowledge by inference. This is the fundamental process of machine learning, which can ultimately evolve into artificial intelligence.
“Once the machines understand these patterns, they begin to learn more quickly, and the more quickly they learn, the quicker they can self-teach. We can then use big data to correlate sounds with behaviour.”
At first sight, it is not obvious why Oracle would get involved in a project like this. Its branding appears nowhere on the hives or even on the website of the World Bee Project. The clue lies in the lessons that are being learned about how big data can be leveraged more effectively by organisations when human experts give machines their basic training.
“Most enterprises struggle with big data, because they have to learn a bunch of technology they have to wire together,” says Abel. “When businesses look at data and analytics, they work in isolation, and they get insight in a one-dimensional way. In the same way, if we just analysed the sound of bees in isolation of other data, it would have no correlation with the biodiversity of the environment.”
The result, in the business world, is that organisations analyse data in silos, and have tremendous difficulty combining data and insights across these silos. It is a similar issue to what banks face when they know all about clients’ patterns of use of their current accounts, but cannot link it to their home loan history, and therefore are unable to make informed decisions about new products or loans for those clients.
In the world of bees, that would be the equivalent of understanding the sounds they make, on the one hand, and having climate and food production data on the other, but not being able to understand the link between the two. Oracle uses what is called a data lake, literally to pool all forms of data – acoustic, relational, spatial, among other – and then use machine learning to spot the patterns not just within each data set, but between the sets.
“Our big advantage is that we can handle all those in a single data repository. We then use machine learning to start creating a single data view of all the data we capture, and teach it what relationship we already know exists between data. The machine can then find the metaphorical needle in the haystack.
“Knowing there’s pollution data doesn’t help us. We need to know what type of pollution is impacting the bees in what way. We need that relation between what is affecting the hive and how we can fix it.”
Oracle and the World Bee Project have set up similar IoT hives in London and Tel Aviv. The variety of ecosystems represented – from rural England to its urban heart to the Middle East – provides an evolving picture of the impact of different environments on the ability of bees to do their job.
Abel believes that the benefits of the project will flow through strongly to many countries on the African continent.
“Across Africa, farmers use mobile devices to find crop grain prices at market. Now we’ve developed a chatbot which lets farmer engage with experts in beekeeping in different countries to understand how to improve biodiversity, which improves pollination, which improves crops.”
According to the World Bee Project, more than three-quarters of the world’s food crops rely at least in part on pollination by insects and other animals.
“There are more than 20,000 species of wild bees alone, plus many species of butterflies, flies, moths, wasps, beetles, birds, bats and other animals that contribute to pollination,” it states. “Pollinated crops include those that provide fruit, vegetables, seeds, nuts and oils. Many of these are important dietary sources of vitamins and minerals, without which the risks of malnutrition might be expected to increase. Several crops also represent an important source of income in developing countries from, for example, the production of coffee and cocoa.”
In short, understanding the language of bees contributes not just to technology advances, but to the very survival of the human race.
* Arthur Goldstuck is founder of World Wide Worx and editor-in-chief of Gadget.co.za. Follow him on Twitter and Instagram on @art2gee
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