In today’s rapidly evolving technological landscape, artificial intelligence (AI) stands at the forefront of transformative change, revolutionizing industries and reshaping the way we live and work. From healthcare to finance, from education to entertainment, AI’s impact is profound and far-reaching. This series of articles delves into the myriad ways AI is being harnessed to power innovations across various industries, beginning with one of the most critical and urgent fields: sustainability.
From smart grids that enhance energy efficiency to sustainable waste management methods to improve recycling, reduce waste and maximize yield, AI is enabling groundbreaking advancements in sustainability. Join us as we explore AI’s role in creating a sustainable world, setting the stage for future articles that will uncover AI’s transformative power across other industries.
Reducing Waste at All Levels
As the world grapples with the escalating challenges of scientifically proven climate change, resource depletion, and environmental degradation, the need for sustainable solutions has never been more pressing. AI emerges as a powerful ally in this quest, offering unprecedented capabilities to monitor, analyze, and optimize our interactions with the planet at a rate that is significantly faster than human analysis. Ultimately, all avenues of AI’s mission within the sustainability industry come back to one key function; reducing waste at all levels, consumer, supplier, and corporate. In this inaugural article, we explore how AI-driven innovations are transforming the sustainability industry, paving the way for a greener, more resilient and efficient future.
Smart Energy Management:
Today’s electrical system power outages and interruptions cost Americans at least $150 billion each year.
Using smart grid systems in your home could cut down your utility bills by about 10-30%. This means a potential saving of between $200 and $600 each year.
AI can play a pivotal role in optimizing energy consumption and reducing waste. By analyzing patterns in energy usage, AI algorithms can predict peak times, adjust energy distribution accordingly, and identify inefficiencies through “smart grid” technologies.
Artificial Intelligence is the driving “intelligent agent” behind smart grids – evaluating the environment and taking actions to maximize a given goal. AI is fundamental to the integration of renewable energy, the stabilization of energy networks, and the reduction of financial risks associated with instability in the infrastructure.
For instance, the self-learning, adaptability, and calculation capabilities of AI have significant potential to address the intermittent nature of renewable energy. The generation of energy is not constant. The imbalance in peaks of production and consumption can make these sources of energy difficult to control. The use of AI in smart grids will help address this challenge by rebalancing the difference between production and consumption loads.
From the consumer side, surveys from the UK and U.S. show less-than-great customer attitudes toward utility companies. With the rise in energy suppliers and consumers, utilities companies need to leverage smart solutions to help nurture better customer engagement and satisfaction by lowering energy costs, improving energy use transparency, and reducing outages. By increasing the frequency of your individual consumer meter reads as frequently as hourly, consumers can see exactly how much energy they are using and when, giving them greater control over their energy consumption–all powered by AI software.
Precision Agriculture:
AI can optimize the use of resources in agriculture, leading to increased productivity and sustainability. Precision agriculture involves using AI technologies like machine learning and computer vision to analyze data from satellite images and sensors in the field. This data can help farmers make informed decisions about when to plant, irrigate, and harvest crops, reducing water and energy use and improving crop yields. Given the current industry challenges, doing that with a farming-as-usual approach could be tricky. Moreover, this would extend the heavy toll we already place on our natural resources.
AI is being used in agriculture for key areas for efficiency improvement, including:
- accurate, early identification and control of pests essential to minimizing crop damage and reducing the reliance on chemical pesticides
- continuous monitoring and analysis of soil health essential to ensuring optimal growing conditions and sustainable farming practices
- precise identification and elimination of weeds critical to preventing them from competing for precious resources with crops and minimizing herbicide use
- intelligent water management systems to optimize water use in the fields
Precision Agriculture:
The global Artificial Intelligence in Sustainable Transportation Market size was valued at USD 2.80 billion in 2022 and is projected to expand at a compound annual growth rate (CAGR) of 21.8% during the forecast period, reaching a value of USD 14.29 billion by 2030.
AI is significantly enhancing transportation systems for greater efficiency and sustainability. AI algorithms analyze real-time data to optimize traffic flow, reduce congestion, and minimize fuel consumption by adjusting traffic signals, rerouting vehicles, and coordinating public transit. In the automotive industry, AI is key in developing advanced driver assistance systems (ADAS) and autonomous vehicles, making them safer and more fuel-efficient with AI-powered sensors and systems. AI also supports electric vehicle (EV) adoption by predicting charging demand, optimizing charging station locations, and adjusting charging schedules to reduce grid strain and costs. Additionally, AI improves battery performance and extends EV range by analyzing driving patterns and environmental factors.
In the realm of public transportation, AI is enhancing the efficiency and sustainability of mass transit systems. AI-powered predictive maintenance algorithms monitor the health of buses, trains, and other transit vehicles in real-time, enabling proactive maintenance to prevent breakdowns and minimize service disruptions. Additionally, AI-driven route optimization algorithms optimize transit routes based on passenger demand, traffic patterns, and environmental conditions, maximizing service coverage while minimizing energy consumption and emissions.
Waste Management:
Downstream recyclers, even in more flexible advanced-recycling processes, require purity levels of 80 to 90 percent or higher, meaning mixed or co-mingled recycling presents a myriad of challenges. “AI applications in waste management can help achieve a recycling purity rate of 95-98% greatly improving the efficiency or recycling methods and reducing wasted costs.
Americans generate more than 290 million tons of municipal solid waste each year — that’s all the packaging, clothing, bottles, food scraps, newspapers, batteries and other everyday items that are thrown into garbage cans. Some of that waste is recycled, composted or burned for energy, but nearly 50% of it is sent to a landfill where it slowly decomposes and emits greenhouse gasses that account for about 25% of today’s global warming.
AI can be used to manage and reduce waste effectively, in part, by sorting waste more accurately and efficiently than humans and helping to increase recycling rates. Pal, the EJ Woody Rice Professor in the Department of Forest Biomaterials, is working with his collaborators to develop a “smart waste management system” for the collection, identification and characterization of organic materials in non-recyclable waste.
In developing the “smart waste management system,” Pal and his collaborators are integrating smart sensors, visual cameras and hyperspectral cameras with an automated waste sorting machine to examine non-recyclable waste items. “By combining hyperspectral imaging with visual cameras and smart sensors, we can collect data in real-time to improve the process of characterizing and separating waste so that it doesn’t end up in landfills,” Pal said.
AI can also predict waste generation patterns and optimize waste collection routes, reducing fuel consumption and emissions.
Sustainability Counter-Concerns with AI Implementation
Sustainability Counter-Concerns with AI Implementation
AI isn’t free. Training an intelligent system alone–upfront training, can have a steep footprint. In terms of training a large language model, each processing unit can consume over 400 watts of power while operating. Typically, you need to consume a similar amount of power for cooling and power management as well. Overall, this can lead to up to 10 gigawatt-hour (GWh) power consumption to train a single large language model like ChatGPT-3. This is on average roughly equivalent to the yearly electricity consumption of over 1,000 U.S. households. Today there are hundreds of millions of daily queries on ChatGPT. This many queries can cost around 1 GWh each day, which is the equivalent of the daily energy consumption for about 33,000 U.S. households.
Ultimately, to make a system truly “green”, the supplied energy for operation should also be sustainable. The same scenario is happening with other green tech, such as Electric Vehicles. Are EV vehicles beneficial even if they are manufactured in a facility that is only 20% powered by sustainable sources? Are EV vehicles beneficial even if they are shipped across the world on a shipping vessel fueled by fossil fuels? The answer is yes. The potential decade-long reduction/elimination of vehicle emissions vastly outweighs the upfront, partially fossil-fuel-driven energy consumption. The potentially cost-deficient energy consumption of AI now is outweighed by the dramatic positive impact AI systems will have long-term across systems in every industry.
The Growing & Lasting Benefits of AI Implementation
Artificial intelligence is revolutionizing the sustainability industry by driving significant advancements in energy management, agriculture, transportation, and waste management. AI’s ability to analyze vast amounts of data in real-time, predict patterns, and optimize processes is transforming the way we approach environmental challenges, making it a powerful ally in our quest for a greener, more resilient future. Stay tuned for future articles in this series, where we will delve into the transformative impact of AI in other industries, showcasing how this powerful technology is reshaping our world and paving the way for a brighter, more sustainable tomorrow.