Artificial intelligence (AI) is rapidly becoming a critical tool in the fight against climate change. With global temperatures on the rise and the planet facing unprecedented environmental challenges, there is growing recognition that new and innovative solutions are needed to mitigate the effects of climate change. AI is being used to address some of the most pressing environmental issues, from deforestation and energy waste to poaching and climate adaptation in agriculture.
By harnessing the power of machine learning, data analytics, and the Internet of Things (IoT), AI is helping to reduce greenhouse gas emissions, improve energy efficiency, protect endangered species, and promote sustainable agriculture. In this article, we explore 4 ways AI is being used to help the environment and how these strategies can be adopted by West African regions facing similar challenges.
Saving the Environment with AI (Global Strategies)
Saving trees with AI ‘guardians’
One way AI is being used to save trees is through the implementation of “guardians.” Rainforest Connection, a nonprofit organization, attaches acoustic monitoring sensors to trees to “eavesdrop” on the surrounding forest and transmit the audio in real-time to the cloud. The data is analyzed by a machine learning model that can recognize sounds linked to illegal logging, such as a chainsaw or truck. Alerts are then sent out to authorities on the ground.
Cutting energy waste in buildings
Hong Kong, a financial center with a population of 7.5 million, has buildings that are accountable for approximately 60% of its carbon emissions. Specifically, a quarter of its total electricity usage is attributed to HVAC systems in commercial buildings. Another use of AI is to cut energy waste in buildings. The Neuron app, developed by design firm Arup, uses 5G and Internet of Things sensors to gather real-time data from a building’s energy management system. It then uses an algorithm to analyze this data and optimize the heating and cooling system, as well as make predictions for the building’s future energy demand. This approach can save 10-30% of the energy used in a typical commercial building.
The agriculture sector is also facing the effects of climate change, including unpredictable temperatures, extreme weather events, and invasive pests. Agriculture, forestry, and land use account for about 18% of global CO2 emissions, and agriculture irrigation is responsible for 70% of water use worldwide. Fertilizers and pesticides used on fields can also end up in groundwater and nearby rivers.
To address these issues, Germany-based startup Agvolution has developed an AI system that draws on data from solar-powered sensors monitoring the microclimate around crops. The devices measure temperature, humidity, radiation, and soil moisture in the field, while algorithms use these insights to make precise recommendations about plant health and exactly how much water and fertilizer to use. This can both boost yields and reduce wasted resources. The company says this can increase ecological and economic efficiency by up to 40%.
Cloud computing for renewable energy
Renewable energy is a crucial step in transitioning away from fossil fuels. However, ensuring power grids’ stability becomes more challenging with clean energy sources such as solar making up a more significant share of the energy mix.
When clouds move over solar panels, the power supply can suddenly drop off, posing a problem for network operators trying to ensure there is enough power in the grid at any given time. To fill any gaps, they need to have generation reserves running in the background that can quickly be ramped up when there is a risk of a power shortage. And these reserves usually come from fossil fuels.
Nonprofit Open Climate Fix has teamed up with the UK’s National Grid to use AI to provide more accurate solar forecasts to reduce reliance on fossil-powered reserves. Their machine learning model is being trained on over a decade of satellite imagery over Europe to get a precise picture of how clouds develop. They also use solar readings from more than 25,000 solar power systems across the UK to predict how much power solar panels will be able to produce. The nonprofit says these short-term forecasts can reduce emissions generated in the UK by around 100,000 tons of CO2 per year.
Lessons for West Africa
Forest conservation through AI “guardians”
West African regions can adopt the same approach by attaching acoustic monitoring sensors to trees in their forests, and then transmitting audio data in real-time to the cloud for analysis. Machine learning models can then be trained to recognize sounds linked to illegal logging, and alerts can be sent to authorities to curb deforestation.
Energy conservation in buildings
In densely populated cities in West Africa, such as Lagos and Accra, HVAC systems in commercial buildings are responsible for a significant portion of energy consumption. However, by using AI-powered apps like Neuron, real-time data can be gathered from energy management systems to optimize heating and cooling systems and predict future energy demands, resulting in a 10-30% reduction in energy usage.
Agriculture is a vital part of West Africa’s economy, and the region can adopt AI-powered farming techniques that draw on data from sensors monitoring the microclimate around crops. By measuring temperature, humidity, radiation, and soil moisture in the field, and using algorithms to make precise recommendations about plant health and water and fertilizer use, yields can be increased, and resources wasted reduced by up to 40%.
Precision solar forecasting & environmental monitoring
AI-powered models can be used to provide more accurate solar forecasts to reduce the reliance on fossil fuels. West African regions can benefit from such technology, given the abundance of solar resources in the region. West African regions can use AI to monitor their environment and collect data on air and water quality, biodiversity, and other environmental indicators. Such data can be used to create more effective policies and practices that protect the environment.