The paper contains 2805 words and is expected to last 6 minutes
Technology and nature are often seen as interdependent rather than antagonistic
Human activities have had a profound impact on nature. There is no denying that our ever-increasing demand for natural resources has led to changes in land use patterns, reduced biodiversity, increased pollution, deterioration of the natural environment and the destruction of species populations.
The rapid development of technology has brought to human society all kinds of achievements such as airplanes, skyscrapers, cheap food and industrial products, allowing people to live a long and comfortable life. Instead, technological development destroys the ecosystem and forces us to rely on unsustainable resources and systems. All the above factors directly or indirectly affect the ecosystem on which human beings and nature depend for survival.
Environmental issues are a real hot topic. The issue of how to deal with global warming since 1850 has been hotly debated.
Have global temperatures soared out of control?
Advances in technology and the ability to read, write and edit DNA have given us a much better understanding of how life works. The more we learn, the more we can use biological knowledge to cure diseases, improve agricultural yields, and more.
At the same time, production machines are becoming biological. They are capable of thinking and communicating with other machines. The biological evolution of machines has spawned a generation of faster, more adaptable, and more efficient technological products. By sensing and reacting to their surroundings, these technologies will make the world more digital and connected. Thanks to ubiquitous wireless networks, different devices can easily plug into various systems, turning cities and homes into part of an intelligent sensing environment.
The line between biology and technology is beginning to blur
Technosphere: Instead of rivers, mountains and forests, we’ve filled the planet with highways, airports and cities.
The good news is that more information about the environment is available today than ever before. With the worldwide attention to environmental issues, environmental protection regulations have increased, the research and application of advanced sensing technology has continued to deepen, and mapping technology and monitoring technology have improved accordingly. These technologies help us better understand the environment and thus better address potential threats to land, air and water security. However, there is an urgent need to arm the above research results with intelligent algorithms, combine them organically, and find a better way to solve environmental problems.
Artificial intelligence is the achievement of cognitive technology, so that cognitive technology to deal with the challenges brought by environmental problems. Ai’s work ranges from finding patterns and connections in macroscopic data sets to providing localized and personalized diagnoses and predictions, and learning to improve those diagnoses over time. Ai can always adapt to needs and solve difficulties.
At the same time, people can use AI technology to correct deviations in data models, extract the most relevant data to avoid data degradation, predict extreme events, and influence model construction. The more valuable the data, the more sensitive the AI; The more synergistic effects artificial intelligence produces, the more profound its economic benefits and impact on sustainable development will be. So paying attention to environmental issues can be doubly rewarding.
A recent survey by Intel (INTC) and the Concentrix Research Center found that 74% of decision makers working in the environmental sustainability sector believe that AI can help people solve long-standing environmental problems; Sixty-four percent of respondents believe the Internet of Things (IoT) can help solve these problems. Technology is a promising way to protect the environment in the face of harsh reality.
The potential for AI to protect the environment is immense
AI applications may solve many environmental problems
Fully automatic car connected with goods
Autonomous cars controlled by AI could drive on demand in the near future. Greenhouse gas emissions from urban transportation can be significantly reduced through route optimization, ecological driving algorithms, programmed traffic alignment and automatic ride-sharing services.
Ai-enabled traffic lights will also play a role: they can minimize traffic times by adjusting the flow of traffic. The system is already in preliminary operation at some intersections in Pittsburgh, USA. The program has reduced traffic times by 25 percent and congestion by 40 percent. The control of electrification is an important factor in determining the actual effectiveness.
Distributed grid
AI can enhance the predictability of renewable energy supply and demand on distributed grids, improve energy storage capacity, energy efficiency and energy load management, and thus help set flexible pricing and trading mechanisms to stimulate market vitality.
AI technology will help integrate renewable energy and transform it into a new and modern power grid. These new methods and products will enable distribution systems to integrate high-permeability renewable energy, reduce their carbon footprint and provide consumers with more choices.
Smart agriculture and food systems
Ai-enhanced agriculture uses robotics to automatically collect data, decisions and corrective actions to detect crop diseases and problems early, provide livestock with nutrition on time, and optimize agricultural inputs and returns at a macro level. This promises to make agriculture more resource efficient, increase yields, reduce damage to ecosystems caused by the use of water, fertilisers and pesticides, and improve agriculture’s ability to cope with climate extremes.
AI for Earth game changers: Indicative timelines
Weather and climate forecasting for the next generation
“Climate informatics” is an emerging research discipline within AI that is fundamentally changing weather forecasting and improving our understanding of climate change and its effects. Traditionally, this field requires high performance and high intensity information processing technology. Deep learning networks allow computers to run faster and incorporate knowledge from more complex real-world systems, such as atmospheric and ocean dynamics and ocean and atmospheric chemistry, into calculations. This enhances the accuracy of weather and climate modelling, making the simulations more useful to decision makers.
Smart Disaster Relief measures
Ai can analyze a disaster simulation of an area, as well as real-time local weather data and damage. Through data analysis, AI can search for potential threats, strengthen disaster prevention and control efforts, issue disaster warnings, and quickly respond to disasters by strengthening emergency coordination capabilities. Deep learning mechanisms may be incorporated into disaster simulations to determine the best strategies for dealing with natural disasters.
Priority measures to deal with the earth’s environmental problems
Smart, connected and livable cities designed by AI
AI can be combined with augmented virtual reality to simulate the surrounding environment and automatically generate management systems. Such as energy and water supply and consumption, passenger traffic flow, real-time data on the city’s weather, etc., to create a “city meter” to promote sustainable urban development.
In China, IBM’s Green Horizon project is using AI systems to predict and track air pollution to generate measures to deal with it. The system can determine, for example, whether it can effectively limit pollution in an area by limiting the number of motorists or the number of factories in operation.
The AI will simulate many weather conditions inside the city, explore different coping strategies and test their effectiveness in mitigating urban heat waves. For example, if a city plans to plant trees, the machine learning model can predict the best place to plant trees and achieve the optimal green cover to cool the city’s roads.
Transparent digital earth
We can use technology to solve problems ranging from illegal logging, water harvesting, fishing and hunting to air pollution, natural disasters and crop failures; Establish a set of real-time, open port (API), digital geospatial information platform supporting AI technology, to achieve the detection, modeling and management of ecological environment system.
In addition, the nascent AI technology has the ability to learn by itself and can quickly evolve into a practical technology that can solve real natural science problems. Therefore, the incorporation of reinforcement learning algorithms into AI systems is crucial for scientific and technological progress and the discovery of new scientific research achievements.
A true environmentalist knows that the earth is not a gift from parents, but a treasure for future generations.
I hope our future will be brighter and more environmentally friendly!
The development and progress of artificial intelligence makes it possible to use emerging technologies to solve some thorny problems in mature industries around the world. AI is becoming key to governments, organizations and individuals moving towards a clean and environmentally friendly planet. It’s time to put AI to work for earth. We’re just getting started, and when we find the right way to use cognitive technology to help us conserve our natural resources, we have a lot of potential.
To build a good “human-oriented era” requires human beings to make full use of social, economic and technological resources to build a beautiful homeland and protect the natural environment.
We share the dry goods of AI learning and development. Welcome to pay attention to the whole platform AI vertical we-media “core reading technology”.
(Add wechat: DXSXBB, join the circle and discuss the latest artificial intelligence technology.)