Advances in software-based technologies such as Artificial Intelligence (AI) and The Internet of Things (IoT) are fundamentally changing the world we live in at an unprecedented pace. Only a few years ago, self-driving cars, facial ID recognition on your phone, or being able to instruct a virtual assistant such as Apple’s SiriTM to perform tasks on your behalf, which all function using AI and IoT technology, would have seemed in the realm of science fiction. These technologies are now a reality, and can help to make many aspects of our lives much more convenient.
Recently, citizens, businesses and governments around the world have been looking beyond the technology itself, and turning their attention to whether AI and IoT can be the key to reducing the negative impact of human activities on the ecosystem in order to conserve the natural environment, and thus support a more environmentally sustainable future. Many believe these technologies may be critically important in the global response for saving the planet.
AI is the method by which computers perform tasks that normally require human intelligence. It involves the use of specifically designed computer algorithms which understand, analyse, and learn from data, to then adapt their performance of a task. AI allows computers or machines to mimic the actions of humans, for example to recognise objects, understand and respond to language, and solve complicated problems.
IoT refers to the billions of internet-connected devices around the world which collect and share data. These devices often include sensors which capture a range of different data types, such as motion, images, light, heat, and proximity, and then transfer this data via the internet or other networks automatically, without the need for human interaction.
It is widely believed that these technologies can help to overcome some of the most pressing environmental challenges facing the world today, and some companies are already looking at ways to do this. Below we look at how AI and IoT can be used to overcome these urgent environmental challenges.
One of the most obvious solutions for reducing carbon footprint in the energy sector is by developing renewable or clean energy sources. However, transitioning the energy industry to 100% renewable energy sources is unlikely to happen soon.
Fortunately, AI and IoT technologies have the potential to reduce greenhouse gas emissions across all energy sources, including fossil fuels. For example, AI could be used to accurately forecast, in real time, the supply and demand of energy from energy grid networks, driving higher efficiency and reducing waste. These supply and demand predictions could be localized, based on predictions of upcoming weather or events in the local area, for example.
Furthermore, by more accurately predicting energy demand, the proportion of energy in a grid network produced by renewable energy sources can actually be increased, thus reducing carbon dioxide emissions. This is because storing energy from renewal sources such as solar or wind power can be difficult, and so intelligent forecasting energy demand can lead to modifying supply and reducing the need for energy storage.
“Using AI for environmental applications has the potential to reduce global green house gas emission by around 1.5 - 4.0% by 2030– equivalent to a reduction of up to 2.4 gigatons of CO2 emissions.”
AI and IoT technologies could also be used to enhance the efficiency of renewable energy production itself. For example, localised monitoring of the weather, as detected by IoT sensors, could be analysed by AI technology to find an optimal position of solar panels and wind turbines to maximise power generation.
Many animal species are close to extinction, owing directly to human activity reducing their natural habitat. IoT and AI technology can help to reverse this trend. For example, AI technology can be used to automatically recognise endangered species and monitor their behavioural patterns non-invasively, for example using camera or motion sensors, or even AI-enabled drones. Tracking animal species in this manner could be used to determine situations that threaten these animals in order to understand why they are endangered, or to monitor and stop poaching activities.
AI-enabled drones can also be used to map forest areas and recognise and intelligently monitor changes in land use, vegetation, deforestation, and the effects of natural disasters on the landscape.
A combination of IoT sensors and AI processing can be used to record and monitor air quality or pollution in real time, and even detect the source of the pollution more efficiently. For example, AI-enabled air purifiers can be used to collect environmental data, measure pollution levels and automatically adjust the filtration power of the purifier to combat changes in levels of air pollution. A similar solution could be used to detect gas leaks, in order to provide warnings more quickly, or even to self-diagnose the source of the gas leak.
Some cities around the globe are already implementing AI and IoT enabled traffic lights to reduce air pollution. Camera sensors are used to detect the amount of traffic from different directions and to adjust a red signal length accordingly, thus minimising driving time and reducing the amount of pollutants released by vehicles.
Similarly to air pollution, changing levels of water pollution can also be monitored using IoT sensors and AI. A particular benefit for ocean health is that these sensors can gather data from locations or ocean depths which are difficult, or even impossible, for humans to reach. This technology could also be used to remotely identify and track illegal fishing, or even for autonomous ocean rubbish collection.
Climate change, and in particular global emissions, has, of course, had an effect on the weather. Many now consider that global emissions are also influencing natural disasters, such as flooding. AI and IoT technology can be used to accurately predict future weather and natural disasters, and their impact on the global community and the environment, taking into account these changes due to climate change.
Weather forecasts, and the prediction of when natural disasters may occur, has been carried out for many years using predictive statistical models. But, combining these known predictive models with IoT sensors and AI technology accelerates the data acquisition and analysis, and allows for the prediction of the influence of multiple natural hazards on one another.
Interconnected sensor platforms and drones are already being used to monitor weather conditions, earth tremors, floods, and changes in sea level. This data can be fed into AI-powered predictive analysis tools to predict the occurrence and impact of natural disasters more quickly, allowing for automated warnings or alerts which enable earlier human evacuations to save lives.
AI and IoT technology can clearly help in many aspects of the global response for saving the planet. In fact, a report from Microsoft and PwCon “How AI can Enable a Sustainable Future” predicts that using AI for environmental applications has the potential to reduce global greenhouse gas emission by around 1.5 - 4.0% by 2030 – equivalent to a reduction of up to 2.4 gigatons of CO2 emissions. Nevertheless, it is unlikely that these technologies will overcome the global environmental challenges working alone. Multiple complimentary technologies such as robotics, electric vehicles, and renewable energy sources, will also be needed, to work in combination with AI and IoT in addressing these challenges.
Furthermore, the processing power, and therefore energy consumption, required by IoT and AI technologies is substantial. To counterbalance the large energy usage required by these technologies, renewable or clean energy sources are likely to be vital in unlocking the full potential of AI and IoT in pursuing a more environmentally sustainable future.
It is clear that reducing and even reversing the negative effects of human activities on the planet is crucially important, and it is time to act now. Therefore, with great urgency, we should accelerate the research and innovation in the AI and IoT spaces, in order to help save the planet.
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Lucy is a Senior Associate and Patent Attorney at Mewburn Ellis. She works primarily in the computer software, electrical engineering, transport, and mechanical engineering sectors. She is involved with all stages of the patent process, particularly in the drafting and prosecuting of applications in the UK and at the EPO. She also has experience in oppositions and opinion work.
Email: lucy.coe@mewburn.com
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