The Internet of Things (IoT) does more than just let you kickstart your kettle when you’re on the loo. It can be used to help order food online when your fridge stocks are running low and manage your heating when you need to stay at work late. But hyperconnectivity can do more than just home-help. It can help save the planet too.
For tech and AI to have such impact it’s important that multiple strands of technology come together in harmony. Big data, machine learning, complex algorithms and tools that allow communities to use open data, all help to create tools that contribute towards tech becoming globally useful.
AI is clearly already helpful from a business perspective. It can help HR departments decide who is most employable based on supplied data, and algorithms can even be employed to calculate the efficiency of a worker based on how much time they spend emailing or browsing the web. But tech has so much more scope than just as an office tool. Environmentally friendly AI is becoming more relevant, as people are starting to explore the positive ways tech can impact the environment. A recent report published by PwC was presented at Davos outlined 80 ways AI could be applied to help save the environment.
Improving urban pollution is one way tech can be applied positively. The topline is the potential for driverless cars, which will see a reduction in carbon emissions as electric automobiles become the driverless car future. In a similar way, driverless car fleet management will take cars off the road and boost road-use efficiency. While a city full of driverless vehicles is still a long way off, there are other, more immediate ways cities can employ tech to become more environmentally friendly.
Improving traffic flow can have a massive impact on pollution in the city. As well as reducing snarling jams and improving the physical environment for city dwellers, helping traffic flow means air-corridors have a chance to circulate fresh air into a city, rather than simply blowing pollution further into homes. IBM is employing an artificial intelligence machine which can predict pollution 72 hours in advance, and analysts are keen to use this information to fight city air pollution.
IBM is rolling out the Green Horizon initiative in China, where air pollution kills approximately 4,000 people each day. Information about pollution is collected from data points throughout the city, shows where congested or polluted hot-spots are, and takes into account upcoming weather data which can affect pollution levels. Cities like Beijing can then use this information to regulate traffic flow for example, and targeting excessively polluting factories or mills.
As well as increasing urban sustainability, AI can also play a big part in rural areas too.
Start-ups are also experimenting with using drones to protect the Amazon rainforest, by employing tools to collect data information from hard-to-reach places. Drones can gather an enormous amount of data from the rainforest, and a non-profit called the Amazon Conservation Society is using them to help manage a large swathe of rainforest. Researchers use AI software to compare two different images of the forest, where the overlay can show discrepancies and alert researchers to whether logging is taking place. It doesn’t always mean logging is happening - it could be farm clearing or another activity - but it helps researchers focus their attention on a smaller space in what is an extraordinarily large area.
It’s not just trees benefitting from hyperconnectivity in the Amazon. Drones and the data they collect helps to keep tabs on the dwindling population of Amazonian pink dolphins by tracking their pods. Drones can help to categorise just how many dolphins there are, and what conservation methods are needed to support the pink mammals.
More generally, companies like Microsoft are starting to use AI to better understand the way land is used by analysing land cover maps. This helps to explore how land is being used, and how efficiently - for example, are there areas that need special environmental protection? Are there underutilised areas that could be developed in a different, more sustainable way? One example where AI is used is through the application Earth Cube, which shows the impact of development on the earth, whether that’s on the rivers, crust, or ozone layer. This is especially beneficial when taking into account the impact of a new mine or quarry, and could deter companies from acting without having the excuse of not knowing the real impact of their actions.
Dr Kevin Curran, Senior IEEE Member and Professor of Computing and Intelligent Systems at Ulster University explains how some of the world’s biggest global issues, including climate change and water pollution, could be solved through advances in IoT. “Through its ability to collect an unprecedented amount of data, IoT can combine this data with advances in computing, machine learning and automation to help design solutions to tackle climate change and protect the earth’s resources.”
Using Internet of Things is one way to help reduce the environmental impact of human activity. Curran delves deeper: “Sensor-enabled devices are already helping monitor the environmental impact of cities, collect details about sewers, air quality, and garbage. In rural areas, sensor-enabled devices can monitor woods, rivers, lakes, and our oceans. A simple example is WaterBee, a smart irrigation system that collects data on soil content and other environmental factors from a network of wireless sensors to reduce water waste. The system then examines the data it collects to selectively water different plots of land based on need. Smart irrigation systems such as these save energy, water, and money and give us a glimpse of what IoT is capable of in the future. Using a prototype, fourteen sites in Europe were able to reduce their water usage on average by 40 per cent. And this is just the tip of the iceberg, the potential is huge.”
Our growing population has a huge and devastating impact on our planet. With that impact comes greater responsibility – using AI and machine learning in ways that go beyond just making a quick buck (or a quick cup of tea) can be a way of giving back and supporting the environment.