Ahmed Karmaoui Can you describe more about the dataset that you may have in your field?

It completely depends on fields on which you want to deploy AI systems to. For example-

Computer Vision related AI systems can be deployed as environmental alert systems in many ways in the form of environmental alert systems which may alarm whenever environmental risk creating actions being performed such as dumping of polethyn made products in a significant scale(where sensor and threshold will work to identify what is significant).

Dear Kamran Shaukat Dar,

Thank you very much for your answer. For your question about the dataset: Climatic variables such as daily and monthly data of Temperature, precipitation, wind speed, relative humidity of several sites of a defined period... Kamran Shaukat Dar

Dear Prof. Alessandro Ferrarini Many thanks for the suggestion. I appreciated your help.

Many thanks Prof. Mohd. Farhan Israk Soumik

I really appreciate your feedback. What about climate change impacts and vulnerability if you can?

Thanks

Check https://www.sciencedirect.com/science/article/pii/S2468111319300349

Also check https://www.sciencedirect.com/science/article/pii/S0925753519308835

https://cms.law/en/bgr/publication/artificial-intelligence-in-environmental-monitoring

Use of AI to carry out tests in an area that is dangerous after nuclear reactor explosion.

I just saw the paper Article Applications of machine learning methods for engineering ris...

Ahmed Karmaoui thanks for appreciation. Researchers are now a days using deep learning models on satelite images of different river's trajectory(Nile in Egypt, Ganges in India) to map out what will be the river's trajectory after years. It can be vital for agriculture and food security as these two rivers have generated two great civilizations.

• Weather, Climate and Air Quality
• Natural Hazards
• Natural Resources (food, water & resource security and biodiversity)

There is a growing interest in AI-technologies for sustainability.

Increased uses of these technologies could create new types of systemic risks.

We show a global uptake of AI-technologies in farming, forestry and marine management.

We explore gaps in principles and governance of AI from a sustainability perspective.

Many thanks, Dr. Chinaza Godswill Awuchi for sharing the paper Article Artificial Intelligence for Chemical Risk Assessment

Dear Dr. Mohd. Farhan Israk Soumik

Tanks you very much for your feedback.

Best wishes

Dear Biju Balakrishnan

I appreciate your detailed response. Many thanks for the clarification.

https://www.researchgate.net/publication/351358986_Polycyclic_Aromatic_Hydrocarbons_in_Soils_in_Industrial_Areas_Concentration_and_Risks_to_Humans_Health?_sg%5B0%5D=3JsHakbPX2eWWYv4DavqqFV4PyWGFiqu5otzfLW6iJyK3Lm-OPXNZpE9hPscamVVm_mOVhG8BOHLtaTZ44TrHufI8O4reRd8Ahs2KfQ6._rKuOMcInubZ1L5OaWTpIpzAjFHnRyt85G-FftEHZ5ptlxXCeJ6LLfy7YVJfift1Pq0ILkP3nIxl5fI_k24_Aw

http://www.pjoes.com/Polycyclic-Aromatic-Hydrocarbons-in-Soils-nin-Industrial-Areas-Concentration-and,137785,0,2.html

Satellite Validation of TROPOMI-SO2 over the Balkan Region by Airborne SO2 Measurements of Coal-Fired Power Plants

https://www.researchgate.net/publication/356171713_Satellite_Validation_of_TROPOMI-SO2_over_the_Balkan_Region_by_Airborne_SO2_Measurements_of_Coal-Fired_Power_Plants?_sg%5B0%5D=gkmM_PzaJTelkAnGazlQGv7T4J1HA6aokRktD4kR2M-RSUp_HGLFPss3TizTX71uwg8mCs-s3ZoNb_j80HZGyqLXT-wSB6TATfds4gAs.AnlvBncFeBD6hWg-oFizveLhfqXxbVSS3cnHPngfysW0GHwupSnmcktwxwa7Bm9xDoQ5fjoNM4k5KYNM1ckZGA

Dear Dr. Predrag Ilić

Thank you very much for sharing these research efforts.

Dear Dr Ahmed Karmaoui . See the following useful link: https://www.rics.org/globalassets/rics-website/media/news/artificial-intelligence-what-it-means-for-the-built-environment.pdf

Kindly see also the following very good link: https://cms.law/en/hun/publication/artificial-intelligence-in-environmental-monitoring

See also the following very useful link: https://www.findaphd.com/phds/project/assessing-the-applicability-of-artificial-intelligence-in-the-environmental-impact-assessment-process-a-case-study-of-oil-and-gas-projects/?p113581

Dear Dr. Aref Wazwaz

Thank you very much for sharing the documents. Excellent examples of AI applications in the field.

You are most welcome dear

Dr Ahmed Karmaoui

Wish you the best always.

An interesting AI Application:

Article A Framework for Evaluating Land Use and Land Cover Classific...

Dear Prof. Mirzakhmet Syzdykov

Thank you very much for your contribution.

Interesting question and seeking for experts' responses.

https://www.cleantechloops.com/artificial-intelligence-environment-protection/

(PDF) Artificial Intelligence Techniques for Information ...

https://www.academia.edu/37673508/Artificial...

https://ai4er-cdt.esc.cam.ac.uk

Dear Prof. Keshab Babu Koirala

Thank you very much for the support

Many thanks, Prof. Kariman Ramzy El Helow for the links

Clustering and classification algorithms.

Ahmed Karmaoui: I believe if your dataset is in the form of CSV, you can easily apply machine learning models. However, if it is in the form of images, Deep learning (transfer learning) models are there. The Ensembling techniques may increase the overall accuracy as well. Let me know if you need any further assistance.

Also check https://www.sciencedirect.com/science/article/pii/S0925753519308835

https://cms.law/en/bgr/publication/artificial-intelligence-in-environmental-monitoring

Dear Dr. Kamran Shaukat Dar

Thank you very much for your valuable answer.

Dear Shivani Garg

Many thanks for sharing the links.

Water Security is one of the most (if not the most) nagging issues in water-scarce countries. Examples for sustainable development in the arid region are given in the following discussions:

(2) Adaptation and Resilience to Climate Change: "Temporal Paradox" versus "Chronology Protection Conjecture". (researchgate.net)

(2) On Water Scarcity Indicators (researchgate.net)

Thank you very much my dear Prof. Jamel Chahed for sharing these examples.

Kindly check the attached pdf:

“Implementation of Sensors and Artificial Intelligence for Environmental Hazards Assessment in Urban, Agriculture and Forestry Systems”

Many thanks, Dr. Manal Hadi Kanaan for sharing the document.

Check this article and its supplementary PowerPoint resource uploaded for python source coding:

Conference Paper FOSS4G – IT 2021 - Revealing TROPOMI environmental COVID-19 ...

Thank you very dear Salvatore Polverino for sharing your paper.

Robots can be used in precise quantification of life cycle input data of construction sites.

Thank you very much Dr. Shuraik Kader for your contribution

I agree with the response of @Manal Hadi Kanaan which is direct use of AI on environment.

Thank you very much Dr. Isa Baba Koki for your contribution

موضوع مثير للاهتمام

شكرا جزيلا Wabelha Mahde Mohmmed

Dear Dr Ahmed Karmaoui . See the following useful RG link: Article Editorial: Implementation of Sensors and Artificial Intellig...

Many thanks my dear Prof. Aref Wazwaz for the suggestion.

Kindly see also the following useful RG link: Article A review of artificial intelligence based risk assessment me...

Interesting doc. Thanks Prof. Aref Wazwaz

You are most welcome dear

Prof. Ahmed Karmaoui

Wish you the best always.

Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, and speech recognition and machine vision. One of the important applications of artificial intelligence is reducing the computational costs of optimization. Various algorithms based on their assumptions to solve problems have been presented and investigated, each of which having assumptions to solve the problems. However, an environment in artificial intelligence is the surrounding of the agent. The agent takes input from the environment through sensors and delivers the output to the environment through actuators.

For risks assessment we have tried to use" Adaptive neuro fuzzy inference system" as an artificial intelligence tools for ranking and prioritization failures mode .

U can check this work :

https://www.emerald.com/insight/content/doi/10.1108/JEDT-07-2021-0395/full/html?skipTracking=true

Artificial intelligence treating the problem of uncertainty in quantitative risk analysis (QRA)

Artificial intelligence has many subcategories which can be utilized like Machine learning (Supervised , Unsupervised , Reinforcement), Natural learning processing , Deep learning , Data mining, Artificial neural network, Expert systems.

New perspectives coming from Fluid Mechanics would boost data-driven approaches in the parameterization of CGMs and ESMs models. Applying machine learning to study fluid mechanics, January 2022Acta Mechanica Sinica.

Abstract: his paper provides a short overview of how to use machine learning to build data-driven models in fluid mechanics. The process of machine learning is broken down into five stages: (1) formulating a problem to model, (2) collecting and curating training data to inform the model, (3) choosing an architecture with which to represent the model, (4) designing a loss function to assess the performance of the model, and (5) selecting and implementing an optimization algorithm to train the model. At each stage, we discuss how prior physical knowledge may be embedding into the process, with specific examples from the field of fluid mechanics. Available on: Article Applying machine learning to study fluid mechanics

https://www.researchgate.net/post/Scientific_Watch_on_Forecasting_Climate_Change