(a) In the case of the Fintech sector, the primary purpose of Green AI is to detect fraud and manage potential business risks that should promote sustainability by eliminating financial malpractice or fraud, which can reduce certain economic losses and enhance the optimal use of resources.
(b) AI algorithms recognize specific trends and patterns of fraudulent activities, helping organizations to minimize business risks and reduce substantial economic losses.
Example: PayPal has recently used AI-based technology to discover fraud or scams and protect its operations from various fraudulent transactions. To protect companies and users from economic losses, the AI system of a payment app can be used to identify potentially fraudulent transactions by measuring user behavior, the current nature of transactions, and other important data.
1. Using Green AI Technology in Agriculture
(a) AI technology can help in developing the use of resources as well as pesticides, water, and fertilizers in the agricultural sector. (b) Through weather forecasting and soil sensor methods, AI algorithms support farmers in optimizing irrigation activities, focusing fertilizer use, and reducing environmental impact. Example: Microsoft’s Farm Beats project has recently launched using advanced AI and IoT capabilities to promote sustainable agriculture. By contributing data-driven knowledge to farmers, AI technology helps improve fertilization, irrigation, and pest control processes, and it also helps reduce resource use and energy consumption to align with the environmental footprint.
2. Using Green AI Techniques in Data Centers and IT Services
Introducing adjusted cooling systems, proper allocation of workloads, and resource distribution based on real-time data analytics; AI technology can improve the utilization of energy use in data centers. Example: Google has recently introduced a deep mind AI mechanism to employ cooling system mechanisms in its data centers. Deep Mind has used AI mechanisms to assess information from active sensors, reducing energy-use efficiencies to make systems quieter by up to 40%.
3. Applications of Green AI Technology in Healthcare Sector
(a) Several health benefits can be offered through Green AI technology and waste management initiatives can be optimized to minimize undesirable environmental consequences. (b) Based on the information provided related to disposal patterns, processes, and waste generation, Green AI technology can specify several advantages to optimize recycling, dispose of materials appropriately, reduce waste, and ensure correct compliance with current environmental guidelines and policies. Example: The University of Pittsburgh Medical Center (UPMC) has implemented AI-driven waste management technology to improve business productivity and sustainability. Green AI technology is implemented by medical centers with the help of data on critical waste management methods and disposal techniques to determine how to reduce waste and boost recycling rates. This offers several advantages, including cost savings, as well as reducing harmful environmental impacts.
4. Applying Green AI Technology to Transportation
(a) AI technology can recognize multiple alternative routes for electric vehicles (EVs), based on a set of variables such as battery range, available traffic, and charging stations.
(b) AI technology can also create appropriate and efficient energy-saving routes based on these available variables, thus avoiding charging stops and reducing overall energy use. Illustration: Tesla employs AI-based green technology to select appropriate routes for its electric vehicles and systematically address sustainability issues. To offer recommendations on how to travel from a point A to a point B via the shortest and quickest routes, AI technology can take into account multiple parameters, including real-time traffic conditions, the strength of the car’s battery at the moment, and the availability of nearby charging stations. This enables vehicle drivers to get the best performance from their EVs.
5. Green AI Technology for Energy Industry
(a) Green AI is capable of understanding various environmental issues and integrating new technologies at rapid rates to enhance energy efficiency and sustainability in the energy and utility sectors. (b) AI has the ability to observe and record information from driving behavioral factors and take into account multiple environmental variables to drive energy efficiency. Example: GE Renewable Energy can spot inefficiencies in turbines at an early stage with the help of AI-based technology. GE can expand the capabilities of turbines and enhance energy usage with the help of green AI algorithms by identifying potential problems in wind turbines and making working teams aware so that they can take necessary actions accordingly.
6. Adoption of Green AI Technology in Manufacturing
(a) In production industries, AI technology can be adapted in such a way that it uses less energy and is environmentally friendly. (b) Green AI can be used in a way to predict the required data from production machinery and other sensors and is an excellent example of energy saving. For example, to produce more energy and conserve energy in many different manners by identifying areas that are critical, planning production during off-peak hours, and improving equipment configurations. Example: Siemens used an artificial intelligence system while performing a production process to boost energy usage. By monitoring sensor data during production in real-time, Siemens is able to identify fraud or reductions in quality and initiate energy saving measures, resulting in reduced energy consumption and carbon output.
7. Green Technology for Education Sector
Predictive maintenance and more based on artificial intelligence can increase the efficiency of renewable energy equipment such as solar panels and wind turbines. Through the history of maintenance and sensors, AI is able to predict failures that are about to occur with pinpoint accuracy, thus allowing proactive maintenance as well as minimizing downtime. The technology has enhanced learning processes and allowed students and lecturers to improve their communication. Some other applications are as follows: (a) AI can potentially result in better methods of teaching and learning, which will guarantee an improvement in the overall quality of education. (b) The proper use of resources and knowledge using the features of AI technology makes learning accessible, enjoyable, and effective. This allows for more environmentally friendly development projects by maximizing the use of resources and incorporating green technology based on AI in education, leading to a cost-effective and efficient system of sustainable development. Example: Internet-based language learning website Duolingo has employed AI-based technology to improve the learning experience of its platform user. Students can pick up different information at their own pace as the AI-powered system has the ability to vary the learning and exercise difficulty level based on the user’s performance.
Read Also:
- Overview Of Green Artificial Intelligence (AI) In India
- Applications Of Artificial Intelligence (AI) In Technical Analysis
- Impact Of Artificial intelligence (AI) On Stock Trading
- Negative And Positive Impacts Of Using Artificial Intelligence (AI) In The Information Technology Sector
- Banking History of Artificial Intelligence (AI) In India
- Opportunities Of Artificial Intelligence (AI) In Indian Banking Sector
- Artificial Intelligence (AI) Techniques Used For Diseases Detection In Agriculture
- Impact of Artificial Intelligence (AI) In Banking‘
- Disadvantages And Challenges Of Artificial Intelligence (AI) In Banking
Leave a Reply