top of page

AI for Sustainable Development: How AI tools and technology can help manage the resources of our planet

By Dawn Bishop - Alcea Content Writer


This is the second article in our three-part series of articles on how AI is helping manage and care for our planet through sustainable development. In this, the second article in the series, we’re exploring two key areas of sustainable development and give examples of the AI tools that are available right now for use in these areas;


  1. Climate modelling

  2. Smart resource management – this is a large field made up of multiple fields.


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 our current needs without harming the ability of future generations to meet their own. It's about finding a balance between our desire for economic growth and social progress and our need for environmental protection.

 

Can AI help us manage our world sustainably?

AI has the potential to be a game-changer for sustainable development. For example, by analysing complex data, AI can predict environmental issues, optimise resource use, and develop renewable energy and conservation solutions. However, responsible implementation is key to ensure AI helps us, not hinders our efforts towards a sustainable future. AI has the power and potential to help us all better look after our planet and ourselves.

 

What is climate modelling and smart resource management and why are they so important for achieving sustainable development?

Climate modelling and smart resource management are crucial for sustainable development because they allow us to predict and navigate our environmental challenges. Climate models help us understand how human activity impacts the Earth's systems, forecasting potential issues like rising sea levels or extreme weather events. With this knowledge, we can implement smart resource management strategies. This involves optimising resource use, like water or energy, to minimise waste and environmental impact. By combining these tools, we can make informed decisions that ensure economic growth and social progress whilst not compromising the ability of our future generations to meet their needs on a healthy planet.


Let’s look at climate modelling in more detail before moving on to smart resource management.

 


Climate modelling  uses complex computer programs to simulate Earth's climate system.  These models account for the interactions between the atmosphere, oceans, land, and ice and can be used to recreate past climates or predict future changes based on factors like greenhouse gas emissions.

 

How can AI tools and technology help with climate modelling?

AI techniques are employed in climate modelling and forecasting to analyse climate data, simulate complex climate systems, and make predictions about future climate trends. These tools help scientists understand the drivers of climate change, assess its impacts on ecosystems and communities, and develop adaptation and mitigation strategies. AI-powered climate models can generate high-resolution projections of temperature, precipitation, sea-level rise, and extreme weather events, aiding policymakers in planning for climate resilience and disaster preparedness.


Ways that AI tools support to climate modelling include:

Climate.ai utilises machine learning algorithms to improve climate models and predict future climate scenarios. Helping researchers to understand the complex interactions within the Earth's climate system and assess the impacts of climate change on various regions.

 

Operated by the European Centre for Medium-Range Weather Forecasts (ECMWF), C3S provides access to a wide range of climate data and tools for analysis and visualisation. It supports climate research, adaptation planning, and policy development.

 

These are just two examples of AI tools that leverage advanced technologies to monitor and analyse environmental data, providing valuable insights for conservation efforts, climate resilience, and sustainable development. But climate monitoring is just one part of sustainable development – what does smart resource management do, and how can AI tools enable it to do it better?

 

2. What is smart resource management?

Smart resource management is getting the most out of resources while minimising waste and environmental impact. Smart resource management is integral to the progress of environmental sustainability as it focuses on optimising the use of natural resources while minimising waste and environmental impact.

 

How can AI tools and technology help with smart resource management?

AI tools play a crucial role in enabling smart resource management practices by providing data-driven insights, predictive analytics, and automation capabilities across various sectors.

 

There are a number of different sub-areas of smart resource management; in this article, we’re going to look at the most common:


  • Energy efficiency

  • Water conservation

  • Waste management

  • The circular economy

  • Natural resource management

 

What is energy efficiency? And, how can AI help improve it?

AI-powered energy management systems analyse real-time data from smart meters, sensors, and building management systems to optimise energy usage in residential, commercial, and industrial facilities. These tools can identify energy inefficiencies, predict energy demand patterns, and recommend strategies for reducing consumption and costs. For example, AI algorithms can adjust lighting, heating, and cooling systems based on occupancy levels and weather conditions, all of which can result in significant energy savings and reduced carbon emissions.

 

Ways that AI tools support to energy efficiency include:

Sense.ai is an AI-powered home energy monitor that helps users track their electricity usage in real-time. It identifies energy-intensive appliances and provides insights to optimise energy consumption, leading to reduced electricity bills and lower carbon emissions.

 

BuildingIQ utilises machine learning algorithms to optimise commercial building heating, ventilation, and air conditioning (HVAC) systems. It adjusts temperature settings based on occupancy patterns and weather forecasts, improving energy efficiency and occupant comfort.

 

Smart resource management connects with AI by addressing water conservation.

 

What is water conservation? And, how can AI help improve it?

Water conservation is the practice of using water efficiently to reduce waste and protect this vital resource. AI-based irrigation systems can help water usage by monitoring soil moisture levels, providing accurate weather forecasts, and understand plant requirements to optimise water usage in agriculture. These tools can schedule irrigation cycles, adjust water flow rates, and detect leaks or inefficiencies in irrigation systems, thereby conserving water resources and improving crop yields. Additionally, AI algorithms can analyse water quality data from sensors and monitoring networks to identify pollution sources, mitigate contamination risks, and ensure safe drinking water supplies for communities.

 

Ways that AI tools support to water conservation include:

 

Asterra uses satellite imagery and machine learning to detect underground leaks in water distribution networks. By identifying leaks early, it helps utilities minimise water loss, conserve resources, and reduce operational costs. Asterra is an example of Smart Water Management Platforms. Many of these platforms integrate IoT(Internet of Things) sensors, data analytics, and AI algorithms to monitor water usage in real-time, detect leaks, and optimise irrigation systems. They enable efficient water management in agriculture, urban areas, and industrial facilities.

 

Another area of smart resource management is waste management. This is connected to the use of water and of energy.

 

What is waste management? And, how can AI help improve it?

 

Waste management is the process of handling waste from its creation to disposal or reuse. AI-powered waste sorting and recycling technologies automate the sorting process by using computer vision and machine learning algorithms to identify and separate recyclable materials from mixed waste streams. These tools improve recycling efficiency, reduce contamination rates, and increase the recovery of valuable resources from waste. Furthermore, AI systems can optimise waste collection routes, schedules, and vehicle fleets to minimise fuel consumption, emissions, and operational costs in waste management operations.

 

Ways that AI tools support to waste management include:

 

Bin-E is an AI-powered waste sorting robot that uses computer vision to identify and sort recyclable materials from mixed waste streams. It helps municipalities and waste management companies increase recycling rates and reduce landfill waste.

 

WasteEdge employs AI and IoT(Internet of Things) sensors to optimise waste collection routes, schedule pickups, and monitor bin fill levels. By minimising truck routes and reducing unnecessary pickups, fuel consumption and carbon emissions associated with waste collection are lower.

 

Another area which uses AI in smart resource management is called the circular economy.

 

What is the circular economy? And, how can AI help improve it?

 

The circular economy aims to keep resources in use for as long as possible by repairing, reusing, and recycling materials and products. AI facilitates the transition to a circular economy by enabling the tracking, tracing and recycling of materials and products throughout their lifecycle. Smart sensors, RFID (radio-frequency identification – similar to barcoding) tags, and blockchain technology are used to monitor and record the movement of materials, components, and products in supply chains, enabling transparency, traceability, and accountability. AI algorithms analyse data on material flows, resource usage, and product lifecycles to identify opportunities for waste reduction, reuse, remanufacturing, and recycling, thus closing the loop and minimising resource depletion and environmental pollution.

 

Ways that AI tools support the circular economy include:

 

Circular IQ is a digital platform that helps businesses transition to circular business models by assessing and optimising their supply chains. It provides tools for tracking materials, identifying circular opportunities, and collaborating with suppliers to reduce waste and maximise resource efficiency.

 

Quentic offers software solutions for environmental management, including tools for tracking material flows, managing sustainability initiatives, and measuring environmental performance. It assists companies in implementing circular economy practices and achieving their sustainability goals.

 

The final area of smart resource management we’re exploring in this article is natural resource management.

 

What is the natural resource management? And, how can AI help improve it?

 

Natural resource management is the practice of using land, water, plants, and animals sustainably to benefit both current and future generations. AI tools support sustainable natural resource management practices by providing insights into ecosystem dynamics, biodiversity conservation, and habitat restoration. Satellite imagery, remote sensing data, and GIS (Geographic Information System) technology are used to monitor and assess changes in land cover, forest health, and wildlife habitats. AI algorithms analyse ecological data to identify conservation priorities, assess ecosystem services, and develop management strategies for protected areas and natural landscapes.

 

Ways that AI tools support natural resource management include:

 

Trimble Forestry provides AI-powered solutions for forest management, including inventory mapping, harvest planning, and habitat modelling. It helps forestry companies sustainably manage their timber resources while preserving biodiversity and ecosystem services.

 

VineView Technologies develops drone-based monitoring systems for precision agriculture and natural resource management, specialising in vineyards. Its AI algorithms analyse aerial imagery to assess crop health, detect invasive species, and monitor land use changes.

 

Pulling everything together

The union of AI and sustainable development holds immense promise for the future of our planet. AI offers a powerful toolkit for tackling environmental challenges by optimising resource use, predicting climate trends, and fostering smarter management practices. From revolutionising energy efficiency to streamlining waste management and safeguarding natural resources, AI is paving the way for a more sustainable future.

 

However, the responsible implementation of AI is crucial. We must ensure these technologies are developed and utilised ethically, with due consideration for potential environmental and social impacts. By harnessing the power of AI for good, we can create a future where economic growth, social progress, and environmental protection go hand in hand, ensuring a healthy planet 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.

9 views0 comments

Comments


bottom of page