By Dawn Bishop - Alcea Content Writer
Sustainable development is a hot topic that impacts all of us daily. There is a necessity to find a balance between the needs of the human population and that of the natural world and our planet. Balance is critical, and it’s not something that has always been achieved. However, with the advent and increasing capabilities of new technologies, like artificial intelligence (AI) there are new ways of using technology to help find, restore and enable that balance.
In this, the first of three articles on different aspects of AI for sustainable development, we’re going to look at four key areas of sustainable development and give examples of the AI tools that are available right now for use in these areas;
1. Environmental monitoring
2. Remote sensing and satellite imagery
3. Environmental data analysis
4. Wildlife conservation
And, for each area we’ll be sharing a brief overview of the area and examples of AI tools available to support the work in those areas. But first, let’s get an overview of what sustainable development is.
What is sustainable development?
Sustainable development is a way of meeting current human needs for things like economics and wellbeing, without ruining the planet's ability to meet those same needs for future generations. It's about finding a balance between progress that improves lives today, and protecting the environment so people can thrive tomorrow.
How can AI help sustainable development?
Artificial Intelligence (AI) can be a powerful tool in this mission. For example, AI's ability to analyse massive datasets can be used to optimise resource use, predict environmental changes, and develop new sustainable technologies. Imagine AI helping us manage energy grids for peak efficiency or monitor natural ecosystems for early signs of stress. By providing data-driven insights and automating processes, AI can accelerate progress toward a prosperous and sustainable future.
Here's where technology steps in as a powerful ally. Environmental monitoring, the continuous assessment of our planet's health, is crucial for achieving sustainable development. This process takes a giant leap forward with the help of remote sensing and satellite imagery. These technologies provide a bird's-eye view, offering vast amounts of data on everything from deforestation rates to changing ocean currents.
But data alone isn't enough. Environmental data analysis, powered by artificial intelligence, allows us to extract meaningful insights from this vast ocean of information. We can track trends, identify potential problems, and predict future environmental changes. This knowledge empowers us to make informed decisions for sustainable practices.
Wildlife conservation, a cornerstone of environmental health, also benefits tremendously from these technological advancements. By analysing satellite imagery, we can track animal migration patterns, identify critical habitats, and detect threats like poaching.
In the coming sections, we'll delve deeper into these tools and explore how they are being used to monitor our environment, analyse critical data, and ultimately, conserve the irreplaceable beauty and diversity of our planet for generations to come.
1. Environmental monitoring
Environmental monitoring, is the continuous assessment of our planet's health. It’s crucial for achieving sustainable development. By tracking things like air and water quality, biodiversity, land use, and climate change indicators it helps to identify problems early and adjust our development practices to minimise environmental damage.
Traditional methods of environmental monitoring often rely on manual data collection, which can be time-consuming, expensive, and limited in scope. AI-powered tools, however, revolutionise the field of environmental monitoring by offering efficient, cost-effective, and scalable solutions.
Ways that AI tools link to environmental monitoring include:
AI-powered drones
AI-powered drones and satellites have the ability to see things and access areas that humans either can’t or are challenging and expensive to reach. These tools can collect vast amounts of data, over big areas, on things like deforestation, pollution levels, and wildlife habitats. This data helps in making informed decisions about conservation efforts and environmental policies.
2. Remote sensing and satellite imagery
AI algorithms can analyse satellite imagery and remote sensing data to monitor changes in land cover, deforestation rates, urban expansion, and other environmental indicators. These tools can automatically detect and classify land use/land cover types, identify changes over time, and assess the impact of human activities on ecosystems.
This platform incorporates geospatial analysis, image analysis, and AI for processing massive datasets of satellite and aerial imagery. It allows users to extract features, detect changes, and gain insights from imagery across space and time.
This AI platform focuses on large-scale analysis of Earth Observation imagery, which means it can detect and analyse real-world objects like buildings, forests, roads, and agricultural fields, extracting valuable information for various uses.
SIC offers AI-powered tools for remote sensing data processing and analysis. Their AI functionalities include object classification, land-use monitoring, data fusion, cloud removal, and spectral analysis for environmental change detection. Its focus is on the mining, oil and gas, and geographic information systems industries.
Planet operates a fleet of satellites that capture daily imagery of the entire Earth. Their AI-powered tools enable monitoring of environmental changes, such as deforestation, land use changes, and natural disasters, at high frequency and resolution.
Gathering images and information by environmental monitoring is the first step. What happens to the data that’s been gathered and monitored? Well, next, the information needs to be assessed, and that’s where environmental data analysis comes in. This is where the magic happens. Scientists use sophisticated tools to analyse this data, identifying trends and patterns. This analysis helps us understand complex environmental issues like rising sea levels or the impact of pollution on wildlife.
3. Environmental data analysis
AI techniques such as machine learning and deep learning are used to analyse large volumes of environmental data collected from sensors, IoT (Internet of Things), and monitoring networks. These tools can identify patterns, trends, and anomalies in environmental datasets, enabling researchers and policymakers to make data-driven decisions. For instance, AI algorithms can predict air pollution levels based on meteorological data, traffic patterns, and emission sources, helping authorities take proactive measures to mitigate pollution.
General purpose environmental data analysis tools
Everyone’s heard of or used Google Earth. Well, did you know that this AI-powered platform can help the environment, too? This cloud-based platform offers massive geospatial datasets and powerful AI algorithms for analysis. You can analyse climate, land cover, and ecological trends using tools for time series analysis, classification, and visualisation. On its website it says; “Scientists, researchers, and developers use Google Earth Engine to detect changes, map trends, and quantify differences on the Earth's surface. Earth Engine is now available for commercial use, and remains free for academic and research use".
This tool is similar to Google Earth, this cloud platform provides access to large-scale environmental datasets and AI tools for analysis. It focuses on tasks like deforestation monitoring, crop yield prediction, and flood risk assessment.
Specialised environmental data analysis
This AI-powered suite caters to sustainable finance and investing. It analyses weather, climate change, and geospatial data to offer insights for environmentally conscious investments.
This AI tool helps with sustainability management by improving insights into environmental data. It allows for better reporting, benchmarking, and monitoring of environmental, social, and governance (ESG) factors.
4. Wildlife conservation
Another key area of sustainable development is monitoring wildlife conservation. AI-powered tools are used in wildlife conservation efforts to track and monitor endangered species, combat poaching, and protect biodiversity hotspots. For example, AI-based image recognition systems can analyse camera trap images to identify and classify animal species, estimate population sizes, and monitor animal behaviour. Conservationists can use these tools to prioritise conservation efforts, allocate resources effectively, and develop targeted conservation strategies.
Some examples of AI tools for sustainable development relating to this aspect of environmental monitoring are:
Wildbook is an AI-powered platform that uses image recognition to track individual animals across different habitats. It's used for population monitoring, species conservation, and combating wildlife trafficking.
SMART integrates AI algorithms to analyse data from camera traps, acoustic sensors, and satellite imagery to detect and deter poaching activities in protected areas.
Pulling everything together
Sustainable development is a complex and ever-evolving area with multiple specialisms within it. In this article we’ve shared a brief overview of just four areas that form part of the wider whole. These four specialisms and the AI tools we’ve shared show the variety of AI tech solutions available as well as the range of companies investing in technology to be used in this work, from new tech start-ups to leading household names.
While these advancements are all exciting, we do need to highlight that there is one main contradiction to all AI-powered tools helping to further any aspect of sustainability. That of its huge energy consumption. Training and running complex AI models requires significant computing power, which often translates to high energy use. This can create a paradox - using AI to solve environmental issues but contributing to them through its own energy demands.
However, even considering this contradiction, the future of environmental monitoring is brimming with possibilities thanks to the development of AI. But, challenges remain. Ensuring the accuracy and transparency of AI models is essential. Additionally, ethical considerations around data privacy and bias need to be addressed.
Despite these challenges, the synergy between environmental monitoring, remote sensing, data analysis, and AI is a powerful force for positive change. By harnessing these technologies, we can gain a deeper understanding of our planet and take informed actions to protect its delicate balance for generations to come.
Alcea Consulting Limited is a boutique AI consultancy helping businesses in any industry improve their ways of working, hit targets and solve problems using AI tools and technology.
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