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text 2022-02-23 08:41
How Can AI App Development Services Fight Climate Change?

Climate change has been causing considerable damage from storms, wildfires, droughts, and much more. Artificial Intelligence and Machine Learning solutions predict and save the day, one day at a time.

Machine-based learning systems have quickly gained popularity as the government, IT firms, and investors have rapidly shown interest in them.

These AI and Machine Learning development services use algorithms identifying the patterns in data sets to make accurate predictions, recommendations, or product decisions.

In its November session, Scotland has already initiated the cop26 climate summit to combat global warming.

Some experts believe that AI can be highly energy-consuming and environmentally damaging than more ways of effectively tackling environmental issues.

Does AI have the potential to help combat climate change?

Artificial Intelligence and Machine Learning solutions are being used to send natural disaster alerts in Japan, monitor deforestation in Amazon, and design greener cities in China.

AI apps can be used to develop more energy-efficient buildings, improve electricity storage and optimize renewable energy deployment.

On micro levels, every AI application development company USA is trying to minimize the energy usage for households. It is usually done by automatically switching off lights when not in use or re-sending the electric vehicles back into the grid to meet the expected demand.

According to a recent study by accounting firm PricewaterhouseCoopers for Microsoft, Artificial Intelligence and Machine Learning solutions can effectively reduce global greenhouse emissions by 4% til 2030.

Peter Clutton-Brock, the co-founder of the Centre for AI and Climate (CAIC), a Britain-based think tank, believes that AI can process bulk unstructured data. He states that AI can understand the sea-level rise and ice sheets dynamics.

5 Ways AI Can Fight Climate Change

By 2030, AI can boost the global economy by 26%, as per World Economic Forum.

Let's look if it's for real.

1. Way to Smarter Transportation

AI is driving autonomous vehicles (AVs) from high-carbon emission to the road of sustainability. Fossil fuels generally emit massive greenhouse gases. AVs reduce these gases and enable eco-driving algorithms and thorough traffic optimization in its place.

Electric autonomous vehicles are the most certain way to reduce carbon emissions and win a losing war against global warming.

2. Power-Saver Energy Grids

AI app development services are the most remarkable ways to enable energy supply and demand in the future. The power-generating departments can make use of energy-efficient grids.

AI application development company USA can improve -
-load management,
- energy storage mechanisms,
-distribution and handling of resources

AI and Machine Learning development services can employ climate-conscious strategies for renewables to tackle global warming on a large scale.

3. Innovative Food Systems and Agricultural Activity

Imagine if the farmers could assess crop disease control, livestock nutrition, and soil fertility levels using Artificial Intelligence and Machine Learning solutions. Well, that's precisely the case.

AI supplements core decision-making, predictive analysis and improves the overall efficiency of resources in the long run.

The smart use of agricultural land and the efficiency of fertilizers, water, and sunlight turn the game of agriculture around.

AI and Machine Learning development services can easily preserve natural systems while giving exceptionally well crop season throughout the year.

One step into the future, AI can identify the genetic architecture of the plants and know exactly what it needs. It becomes easy to save the crops from pests and harsh climatic conditions.

4. Precision in Weather Forecasting-

You can get weather forecasts on your fingers. Using google, mobile apps, news, the sources are countless.

AI's climate informatics slays the weather forecasting game and climate change understanding.

Energy-efficient computing resources can run AI algorithms and climate data quickly in real-time. In this way, one can better understand the forecasts and assess climate trends.  

Advanced data modeling approaches can quickly predict extreme weather conditions with lower research costs.

5. Disaster Response Systems-

AI app development services can predict disasters well in advance and in real-time to efficiently take precautionary measures and assess vulnerabilities.

AI tools and techniques are making disaster response management more agile and responsive.

Early warning, simulations, and AI algorithms effectively predict climate trends and serve as a warning system. The government and concerned authorities can easily create optimal strategies to curb the issue.

Conclusion-

As we inch closer to the era of  Artificial Intelligence and Machine Learning solutions, we hope to see the best in the future.

The power of AI ML can help government and technologists one step closer to achieving sustainability and efficiency in a single sweep.

Environmental Intelligence is slowly gaining momentum, only to rise full-scale, by the technology pioneers in the industry.

Consagous Technologies is an AI application development company USA. We offer to contribute to the movement and make the planet a better place to live.

Original Source:

https://www.consagous.co/blog/how-can-ai-app-development-services-fight-climate-change

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text 2021-06-14 07:22
Machine Learning App Development

 

One of the industries that benefit from machine learning the most is mobile application development. The use of machine learning became so widely spread that you might not even suspect that an app relies on it.

Machine learning algorithms find patterns in massive amounts of data to make data-based predictions and decisions. The more data ML processes, the better algorithms become and the more accurate predictions and decisions they make.

Today, three main types of machine learning are defined:

 

  • Supervised machine learning – the algorithm is trained with predefined training examples. It is used for the ML to learn how to reach the right conclusions when new data is fed to it.
  • Unsupervised machine learning – the algorithm is trained on data without predefined rules. It must find patterns and relationships to make predictions in the future.
  • Reinforced machine learning – machine learning is trained to make a sequence of decisions. The agent learns how to achieve the goal in an uncertain and potentially complex environment.


Industries That Can Benefit From Machine Learning Application Development

Machine learning is the solution that is gradually finding its way into various industries. Use cases are numerous and, in this part, we are going to talk about the industries and spheres where machine learning can bring the highest value.

  • Transportation

Smart and self-driving cars have already entered our lives. Artificial intelligence enforced with machine learning algorithms are used to monitor the traffic and predict changes. The combination of these technologies allows for cars to drive without human assistance.

 

  • Healthcare

Machine learning is accelerating the healthcare industry. Such solutions collect and analyze patient data to diagnose and advise possible ways for treatment. Predictive healthcare is gaining traction.

 

  • Finance

The finance industry has a huge amount of data that needs to be analyzed to make predictions for future data collection, management, investment, and transactions. Machine learning and artificial intelligence are used in the industry for fraud detection and fraud prediction.

 

  • Cybersecurity

The technology can analyze data about incident reports, alerts, and more to identify potential threats and improve security analysis or even advise response.

 

  • Manufacturing

Companies with assembly lines can use ML algorithms together with sensors and artificial intelligence to predict the need for maintenance. Thanks to their use, companies can avoid unplanned downtown and drops in production.

 

  • eCommerce

The eCommerce industry already benefits from this technology. Personalized product recommendations increase the average order value and revenue.

 

  • Marketing

This technology can be applied in the ads industry to improve the efficiency of ad campaigns by targeting users with highly personalized ads tailored to their specific interests and needs.

Read more about Machine Learning App Development 

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