APPLICATION OF AI IN MANAGEMENT OF ENVIRONMENTAL CHALLENGES RPO-1.pptx

Ai management

1. POST DOC. EXPERIENCE “Differential expression of selective genes among age related Senile Dementia of Alzheimer’s type (SDAT) and Alzheimer’s patients” IMS, BHU, Varanasi, U.P (July-Dec.2012) OVERSEAS EXPERIENCE “Mitochondrial ETC mediated oxidative stress intended Dopaminergic neuronal degeneration in Parkinson’s disease”, Prof. Gino Cartopassi , Research Group (UC-Davis, California, USA, March 2009-May 2010), Under Ph.D., sandwich program. “Free Radicals, antioxidant and Neurodegenerative disorders” workshop held at Oxygen Club of California (OCC), Santa Barbara, California, USA (Mar 12- 27 2008) PREVIOUS TEACHING EXPERIENCE Associate Professor in the Department of Zoology, Dean, Faculty of Science & Director, Research Centre, NGB (DU) Dec. 2012-July 2024 Asst. Professor-I, CARISM, SASTRA University (www.sastra.edu.in) Thanjavur, Tamilnadu . India (Sep. 2008- June 2012) Cumulative IF H Index I 10 Citation 42.5 18 21 560

2. TABLE OF CONTENTS INTRODUCTION TO ARTIFICIAL INTELIGENCE (AI) CURRENT GLOBAL ENVIRONMENTAL THREATS IMPLICATIONS OF AI IN ENVIRONMENT MANAGEMENT AI APPLICATIONS IN ENVIRONMENTAL CHALLENGES CASE STUDIES OF AI IN ENVIRONMENTAL MANAGEMENT GLOBAL WARMING AND AI AS PREVENTIVE TOOL HEAVY METAL TOXICITY AND AI AS PREVENTIVE MEASURE BIOREMEDIATION AND ROLE OF AI IN BIOREMEDIATION POLLUTED VS UNPOLLUTED ENVIRONMENT CAREER OPPORTUNITIES OF STUDENTS IN AI AND ENVIRONMENTAL STUDIES CHALLENGES AND ETHICAL CONSIDERATIONS FUTURE OF AI IN ENVIRONMENTAL MANAGEMENT CONCLUSION ACKNOWLEDGEMENTS REFRENCES

3. INTRODUCTION TO ARTIFICIAL INTELLIGENCE

4. ARTIFICIAL INTELLIGENCE IS THE STIMULATION OF HUMAN INTELLIGENCE PROCESSESD BY MACHINE,ESPECIALLY BY COMPUTER APPLICATION. IT IS A FIELD OF RESEARCH IN COMPUTER SCIENCE THAT DEVELOPS AND STUDIES METHODS AND SOFTWARE THAT ENABLES THE MACHINE TO PERCEIVE THEIR ENVIRONMENT AND USE LEARNING AND INTELLIGENCE TO TAKE ACTIONS THAT MAXIMIZE THEIR CHANCES OF ACHIEVING DEFINED GOALS. SOME HIGH-PROFILE APPLICATIONS OF AI INCLUDE ADVANCED WEB SEARCH ENGINES (GOOGLE SEARCH); RECOMMENDATION SYSTEMS (USED BY YOUTUBE, AMAZON, AND NETFLIX); INTERACTING VIA HUMAN SPEECH (GOOGLE ASSISTANT,SIRI, AND ALEXA); AUTONOUMOUS VEHICLES (TESLA/ WAYMO); GENERATIVE AND CREATIVE TOOLS (CHATGPT, AND AI ART); AND SUPERHUMAN PLAY AND ANALYSIS in STRATAEGY GAMES (CHESS AND GO).

5. CHRONOLOGICAL INTERVENTIONS OF AI SOURCE : http//: www.imb.com

6. SOURCE : http//: www.imb.com

7. CURRENT ENVIRONMENTAL CHALLENGS CAUSE: DEVELOPMENT/INDUSTRILISATION – GLOBAL NEED ON THE COST OF DEFORESTATION : DEFORESTATION IS ONE OF THE MOST PRESSING ENVIRONMENTAL ISSUES THAT THE WORLD IS FACING CURRENTLY. IT IS THE CONVERSION OF NATURAL FOREST LAND TO CONCRETE FORESTED LAND BY HUMANS. IN YEAR 2023 ITSELF REPORTED; 24% INCREASE IN GLOBAL TREE COVER LOSS (DUE TO NATURAL AND MAN MADE CALAMITIES). (WORLD RESOURCES INSTITUTE REPORT 2024) CONSEQUENCES: CLIMATE CHANGE : THE RISE IN GLOBAL TEMPERATURE DUE TO HUMAN ACTIVITIES PRIMARILY THE BURNING OF FOSSIL FUELS IS CAUSING EXTREME WEATHER EVENTS,RISING SEA LEVEL CAUSES PARADIGM SHIFT IN ECOSYSTEM. LOSS OF BIODIVERSITY : HABITAT DESTRUCTION, POLLUTION,CLIMATE CHANGE AND OVER EXPLOITATION OF RESOURCES HAVE LED TO A RAPID LOSS OF SPECIES. AIR POLLUTION : A MAJOR ENVIRONMENTAL ISSUE THAT HARMS THE ENVIRONMENT AND HUMAN HELATH. RESPONSIBLE FOR AROUND SEVEN MILLION DEATHS EACH YEAR.

8. CONSEQUENCES contd …. WATER SCARCITY : FRESHWATER RESOURCES ARE BECOMING INCREASINGLY SCARCE DUE TO OVERUSE, POLLUTION AND CHANGING WEATHER PATTERNS. SOIL DEGRADATION : UNSUSTAINABLE AGRICULTURAL PRACTICES, DEFORESTATION AND INDUSTRIAL ACTIVITIES ARE CAUSING SOIL EROSION, DESERTIFICATION AND LOSS OF ARABLE LANDS. PLASTIC WASTE : THE MASSIVE ACCUMULATION OF PLASTICS IN OCEAN AND LANDFILLS IS A MAJOR ENVIRONMENTAL CRISIS. PLASTIC TAKE HUNDREDS OF YEARS TO DECOMPOSE AND ARE HARMFUL TO WILDLIFE, PARTICULARLY MARINE LIFE WHICH CAN INGEST OR BECOME ENTANGLED IN PLASTIC DEBRIS.

9. SOURCE : https://sigmaearth.com/the-biggest-environmental-problems

10. ROLE OF AI IN ENVIRONMENT MANAGEMENT DATA DRIVEN-DECISION MAKING: AI PROCESSES MASSIVE DATA SETS TO IDENTIFY PATTERNS AND TRENDS. AUTOMATION AND EFFICIENCY : AI ENHANCES RESOURCE MANAGEMENT AND OPTIMIZATION. PREDICTIVE ANALYSIS : AI MODELS PREDICT FUTURE ENVIRONMENTAL SCENARIOS, ENABLING EARLY INTERVENTIONS. REAL TIME MONITORING : AI ALLOWS CONSTANT MONITORING OF ECOSYSTEM, AIR QUALITY AND CLIMATE PATTERN.

11. APPLICATIONS OF AI IN ENVIRONMENTAL CHALLENGES CLIMATE CHANGE MITIGATION AND ADAPTATION WEATHER PREDICTION MODELS : AI MODELS ANALYZE CLIMATE DATA TO PREDICT WEATHER PATTERNS,HELPING CITIES AND INDUSTRIES PREPARE FOR CLIMATE EVENTS. CARBON FOOTPRINT REDUCTION : AI POWERED TOOLS FOR MONITORING EMISSIONS FROM INDUSTRIES, TRANSPORTATION AND AGRICULTURE. POLLUTION MANAGEMENT AIR AND WATER QUALITY MONITORING : AI SENSORS AND DRONES DETECT POLLUTANT IN REAL TIME,OFFERING ACTIONABLE INSIGHTS FOR TIMELY INTERVENTION. WASTE MANAGEMENT : AI SYSTEM OPTIMIZE WASTE SORTING, RECYCLING,AND DISPOSAL PROCESSES.

12. ENERGY EFFICIENCY SMART GRID AND SMART CITIES : AI OPTIMIZES ENERGY CONSUMPTION IN CITIES BY ADJUSTING LIGHTING,TRAFFIC FLOW,AND HEATING IN REAL TIME,REDUCING ENERGY WASTE. RENEWABLE ENERGY INTEGRATION : AI MODELS PREDICT ENERGY PRODUCTION FROM RENEWABLE SOURCES ( SOLAR,WIND) IMPROVING GRID RELIABILITY AND DISTRIBUTION. BIODIVERSITY PROTECTION WILDLIFE TRACKING : AI POWERED DRONES AND SENSORS MONITOR ENDANGERED SPECIES AND ECOSYSTEM, PROVIDING REAL-TIME DATA TO CONSERVATIONISTS. FOREST MANAGEMENT : AI ANALYZES SATELITE IMAGES AND DRONE FOOTAGE TO MONITOR DEFORESTATION AND ILLEGAL LOGGING ACTIVITIES.

13. MODUS OPERANDI OF AI: TACKLING CLIMATE CHANGE THE USE OF ARTIFICIAL INTELLIGENCE CAN CONTRIBUTE TO THE FIGHT AGAINST CLIMATE CHANGE.EXISTING AI SYSTEMS INCLUDE TOOLS THAT PREDICT WAETHER,TRACK ICEBERGS AND IDENTIFY POLLUTION. THE POWER OF ARTIFICIAL INTELLIGENCE TO PROCESS HUGE AMOUNT OF DATA AND HELPS HUMAN MAKE DECISION IS TRANSFORMING INDUSTRIES. AS ONE OF THE WORLD’S TOUGHEST CHALLENGES, COMBATING CLIMATE CHANGE IS ANOTHER AREA WHERE AI HAS TRANSFORMATIONAL POTENTIAL. ALMOST 4 BILLION PEOPLE ALREADY LIVE IN AREAS HIGHLY VULNERABLE TO CLIMATE CHANGE, ACCORDING TO THE WORLD HEALTH ORGANIZATION.AND THIS is EXPECTED TO LEAD TO AROUND 250,000 EXTRA DEATHS A YEAR BETWEEN 2030 and 2050, FROM UNDER NUTRITION, MALARIA, DIARRHOEA AND HEAT STRESS ALONE.

14. 1. ICEBERGS ARE MELTING – AI KNOWS WHERE AND HOW FAST : AI HAS BEEN TRAINED TO MEASURE CHANGES IN ICEBERGS 10,000 TIMES FASTER THAN a HUMAN COULD DO IT.THIS WILL HELP SCIENTISTS UNDERSTAND HOW MUCH MELTWATER ICEBERGS RELEASE INTO THE OCEAN – A PROCESS ACCELERATING AS CLIMATE CHANGE WARMS THE ATMOSPHERE. SCIENTISTS AT THE UNIVERSITY OF LEEDS IN THE UNITED KINGDOM SAY THEIR AI CAN MAP LARGE ANTARCTIC ICEBERGS IN SATELLITE IMAGES IN JUST ONE-HUNDREDTH OF A SECOND, REPORTS THE EUROPEAN SPACE AGENCY. FOR HUMANS, THIS TASK IS LENGTHY AND TIME-CONSUMING, AND IT’S HARD TO IDENTIFY ICEBERGS AMID THE WHITE OF CLOUDS AND SEA ICE.

15. 2. MAPPING DEFORESTATION WITH AI AI, SATELLITE IMAGES AND ECOLOGY EXPERTISE ARE ALSO BEING USED TO MAP the IMPACT OF DEFORESTATION ON THE CLIMATE CRISIS.SPACE INTELLIGENCE, A COMPANY BASED IN EDINBURGH, SCOTLAND, SAYS IT IS WORKING IN MORE THAN 30 COUNTRIES AND HAS MAPPED MORE THAN 1 MILLION HECTARES OF LAND FROM SPACE USING SATELLITE DATA.THE COMPANY’S TECHNOLOGY REMOTELY MEASURES METRICS, SUCH AS DEFORESTATION RATES AND HOW MUCH CARBON IS STORED IN A FOREST. 3. AI IS HELPING COMMUNITIES FACING CLIMATE RISKS IN AFRICA IN AFRICA, AI IS being USED IN A UNITED NATIONS PROJECT TO HELP COMMUNITIES VULNERABLE TO CLIMATE CHANGE IN BURUNDI, CHAD AND SUDAN.THE IKI PROJECT USES AI TECHNOLOGY TO HELP PREDICT WEATHER PATTERNS, SO COMMUNITIES AND AUTHORITIES CAN BETTER PLAN HOW TO ADAPT TO CLIMATE CHANGE AND MITIGATE its IMPACT.THIS INCLUDES IMPROVING ACCESS to CLEAN ENERGY, IMPLEMENTING PROPER WASTE MANAGEMENT SYSTEMS AND ENCOURAGING REFORESTATION.

16. 4 . USING AI TO RECYCLE MORE WASTE ANOTHER AI SYSTEM IS HELPING TO TACKLE CLIMATE CHANGE BY MAKING WASTE MANAGEMENT MORE EFFICIENT.WASTE IS A BIG PRODUCER OF METHANE AND IS RESPONSIBLE FOR 16% OF GLOBAL GREENHOUSE GAS (GHG) EMISSIONS, ACCORDING TO THE UNITED STATES ENVIRONMENTAL PROTECTION AGENCY .GREYPARROT, a SOFTWARE STARTUP BASED IN LONDON, UNITED KINGDOM, HAS DEVELOPED AN AI SYSTEM THAT ANALYZES WASTE PROCESSING AND RECYCLING FACILITIES TO HELP THEM RECOVER AND RECYCLE MORE WASTE MATERIAL.THE COMPANY TRACKED 32 BILLION WASTE items across 67 WASTE CATEGORIES in 2022, AND SAYS IT IDENTIFIES 86 TONNES of MATERIAL ON AVERAGE THAT COULD BE RECOVERED BUT IS BEING SENT TO LANDFILL.

17. 5. AI IS CLEANING UP THE OCEAN IN THE NETHERLANDS, AN ENVIRONMENTAL ORGANIZATION CALLED THE OCEAN CLEANUP IS USING AI and OTHER TECHNOLOGIES TO HELP CLEAR PLASTIC POLLUTION FROM THE OCEAN.AI THAT DETECTS OBJECTS IS HELPING THE ORGANIZATION CREATE DETAILED MAPS OF OCEAN LITTER IN REMOTE LOCATIONS. THE OCEAN WASTE CAN THEN BE GATHERED AND REMOVED, WHICH IS MORE EFFICIENT THAN PREVIOUS CLEANUP METHODS USING TRAWLERS AND AEROPLANES.PLASTIC POLLUTION CONTRIBUTES TO CLIMATE CHANGE BY EMITTING GHGs AND HARMING MATURE.

18. 6. AI HELPS PREDICT CLIMATE DISASTERS IN SAO PAULO, BRAZIL, A COMPANY CALLED SIPREMO IS USING AI TO PREDICT WHERE AND WHEN CLIMATE DISASTERS WILL OCCUR, AND WHAT TYPE OF CLIMATE DISASTERS THEY WILL BE.THE AIM IS TO HELP BUSINESSES AND GOVERNMENTS BETTER PREPARE FOR CLIMATE CHANGE AND THE GROWING CHALLENGES FOR COMMUNITIES THAT COME WITH IT.THE COMPANY WORKS IN INDUSTRIES INCLUDING INSURANCE, ENERGY, LOGISTICS AND SPORT, WHERE IT’S ANALYSIS OF DISASTER CONDITIONS AND FACTORS SUCH AS AIR QUALITY CAN INFORM DECISIONS ON WHETHER TO DELAY OR SUSPEND EVENTS.

19. 7. HOW AI CAN HELP INDUSTRY DECARBONIZE AI IS BEING USED TO HELP COMPANIES IN THE METALS AND MINING, OIL, AND GAS INDUSTRIES TO DECARBONIZE THEIR OPERATIONS.EUGENIE-AI BASED COMPANY IN CALIFORNIA, UNITED STATES, HAS DEVELOPED AN EMMISION-TRACKING PLATFORM THAT COMBINES SATELLITE IMAGERY WITH DATA FROM MACHINES AND PROCESSES.AI THEN ANALYZES THIS DATA TO HELP COMPANIES TRACK, TRACE AND REDUCE THEIR EMISSIONS BY 20-30%. INDUSTRIAL SECTORS GENERATE AROUND 30% OF GREENHOUSE GAS EMISSIONS GLOBALLY.

20. 8. REFORESTING HILLS IN BRAZIL USING DRONES AI POWERED COMPUTERS ARE PAIRING UP WITH DRONES IN BRAZIL TO REFOREST THE HILLS AROUND THE COASTAL CITY OF RIO DE JANEIRO, REUTERS REPORTS. THE COMPUTERS DEFINE THE TARGETS AND NUMBER OF SEEDS TO BE DROPPED.THE INITIATIVE, WHICH LAUNCHED IN JANUARY 2024, IS A PARTNERSHIP BETWEEN RIO’S CITY HALL AND START-UP MORFO, AND AIMS TO GROW SEEDS in HARD-TO-REACH AREAS.A SINGLE DRONE CAN DISPERSE 180 SEED CAPSULES PER MINUTE, WHICH IS 100 TIMES FASTER THAN USING HUMAN HANDS FOR TRADITIONAL REFORESTATION, ACCORDING TO THE LOCAL GOVERNMENT.

21. 9 . A WISHLIST OF AI CLIMATE TOOLS GOOGLE DEEP MIND, GOOGLE’S AI RESEARCH LABORATORY, SAYS IT IS APPLYING AI TO HELP FIGHT CLIMATE CHANGE IN A NUMBER OF AREAS.THIS INCLUDES BUILDING A COMPLETE WISH LIST OF DATASETS THAT WOULD ADVANCE GLOBAL AI SOLUTIONS FOR CLIMATE CHANGE. GOOGLE DEEPMIND IS WORKING ng ON THIS WITH CLIMATE CHANGE AI, A NON-PROFIT ORGANIZATION SET UP BY VOLUNTEERS FROM ACADEMIA AND INDUSTRY WHO SEE A KEY ROLE FOR MACHINE LEARNING IN COMBATING CLIMATE CHANGE.OTHER GOOGLE AI TOOLS ARE FOCUSED ON IMPROVING WEATHER FORECASTING AND INCREASING THE VALUE OF WIND ENERGY BY BETTER PREDICTING THE OUTPUT FROM A WIND FARM.

22. CASE STUDIES OF AI IN ENVIRONMENTAL MANAGEMENT GOOGLE’S AI FOR FOREST MONITORING USE OF MACHINE LEARNING TO ANALYZE SATELLITE IMAGES AND DETECT DEFORESTATION IN NEAR REAL-TIME, SUPPORTING CONSERVATION EFFORTS. IMB’S GREEN HORIZON INITIATIVE AI USED FOR AIR QUALITY PREDICTION,ENERGY CONSUMPTION OPTIMIZATION,AND CLIMATE RISKS MANAGEMENT. DEEPMIND’S AI FOR ENERGY EFFICIENCY GOOGLE’S DEEPMIND USES AI TO OPTIMIZE ENERGY CONSUMPTION IN DATA CENTRES, REDUCING ENERGY USE BY UPTO 40%.

23. BENEFITS OF AI IN ENVIRONMENTAL MANAGEMENT IMPROVED ACCURACY AND PRECISION AI CAN PROCESS VAST AMOUNT OF ENVIRONMENTAL DATA FASTER AND MORE ACCURATELY THAN HUMANS. PROACTIVE MANAGEMENT AI HELPS IN EARLY DETECTION AND INTERVENTION, REDUCING THE IMPACT OF ENVIRONMENTAL DISASTERS. COST EFFICIENCY AI SOLUTIONS OPTIMIZE RESOURCE USE,REDUCING OPERATIONAL COSTS. ENHANCED SUSTAINABILITY AI AIDS IN ACHIEVING LONG-TERM SUSTAINABILITY GOALS BY PROMOTING EFFICIENT ENERGY USE, WASTE REDUCTION, AND RESOURCE CONSERVATION.

24. AI: Reaching the Unreached 1 . HEALTHCARE ONE OF THE CRITICAL AI APPLICATIONS IS IT’S INTEGRATION WITH THE HEALTHCARE AND MEDICAL FIELD. AI TRANSFORMS HEALTHCARE BY IMPROVING DIAGNOSTICS, PERSONALIZING TREATMENT PLANS, AND OPTIMIZING PATIENT CARE. AI ALGORITHMS CAN ANALYZE MEDICAL IMAGES, PREDICT DISEASE OUTBREAKS, AND ASSIST IN DRUG DISCOVERY, ENHANCING THE OVERALL QUALITY OF HEALTHCARE SERVICES. IBM WATSON HEALTH USES AI to ANALYZE VAST AMOUNTS OF MEDICAL DATA, ASSISTING DOCTORS IN DIAGNOSING DISEASES AND RECOMMENDING PERSONALIZED TREATMENT PLANS.

25. 2. AI IN ELECTRIC VEHICLE BATTERIES BATTERY MANAGEMENT SYSTEMS (BMS) OPTIMIZATION AI CAN ENHANCE THE FUNCTIONING of BMS, WHICH MONITOR AND MANAGE THE CHARGING, DISCHARGING, AND HEALTH OF EV BATTERIES. AI ALGORITHMS CAN PREDICT BATTERY BEHAVIOR, OPTIMIZE CHARGE CYCLES, AND ENSURE THAT BATTERIES ARE OPERATING WITHIN THEIR OPTIMAL PARAMETERS. THIS CAN EXTEND THE LIFESPAN OF THE BATTERY AND PREVENT OVERHEATING OR OVERCHARGING. BATTERY MANUFACTURING AI IS USED IN THE MANUFACTURING PROCESS TO IMPROVE QUALITY CONTROL AND EFFICIENCY. MACHINE LEARNING MODELS CAN PREDICT DEFECTS, OPTIMIZE PRODUCTION LINES, AND ENSURE CONSISTENCY IN BATTERY CELL PRODUCTION. THIS HELPS REDUCE COSTS AND ENHANCES THE SCALABILITY OF EV BATTERY PRODUCTION.

26. 3. APPLICATIONS OF AI IN BRAIN CHIPS NEURAL ENHANCEMENT THESE CHIPS COULD POTENTIALLY BOOST COGNITIVE FUNCTIONS SUCH AS MEMORY, FOCUS, AND DECISION-MAKING, ACTING AS AN AUGMENTATION TO THE HUMAN BRAIN’S NATURAL PROCESSING POWER. BRAIN-COMPUTER INTERFACES (BCI) AI-POWERED BCIs COULD ENABLE INDIVIDUALS TO CONTROL EXTERNAL DEVICES, SUCH AS PROSTHETICS OR COMPUTERS, SIMPLY BY THINKING. THIS IS ESPECIALLY BENEFICIAL FOR PEOPLE WITH DISABILITIES OR THOSE SUFFERING FROM CONDITIONS LIKE PARALYSIS.

27. GLOBAL WARMING AND ROLE OF ARTIFICIAL INTELLIGENCE IN PREVENTING GLOBAL WARMING GLOBAL WARMING REFERS TO THE LONG-TERM INCREASE IN EARTH’S AVERAGE SURFACE TEMPERATURE DUE TO HUMAN ACTIVITIES, PRIMARILY THE EMISSION OF GREENHOUSE GASES (GHGs) SUCH AS CARBON DIOXIDE (CO₂), METHANE (CH₄), AND NITROUS OXIDE (N₂O). THIS WARMING TREND IS PART OF A BROADER PHENOMENON KNOWN AS CLIMATE CHANGE, WHICH INVOLVES SHIFTS IN TEMPERATURE, WEATHER PATTERNS, AND ECOSYSTEMS AROUND THE GLOBE. CAUSES OF GLOBAL WARMING BURNING OF FOSSIL FUELS : THE COMBUSTION OF COAL, OIL, AND NATURAL GAS FOR ENERGY PRODUCTION, TRANSPORTATION, AND INDUSTRIAL ACTIVITIES IS THE PRIMARY SOURCE OF CO₂ EMMISIONS.DEFORESTATION: CUTTING DOWN FORESTS REDUCES THE PLANET’S CAPACITY TO ABSORB CO₂, CONTRIBUTING TO HIGHER LEVELS OF THIS GREENHOUSE GAS IN THE ATMOSPHERE.

28. AGRICULTURE AND LIVESTOCK: AGRICULTURAL PRACTICES, SUCH AS RICE CULTIVATION AND LIVESTOCK FARMING, PRODUCE SIGNIFICANT AMOUNTS OF METHANE.INDUSTRIAL PROCESSES: CERTAIN MANUFACTURING PROCESSES RELEASE NOT ONLY CO₂ BUT ALSO OTHER POTENT GREENHOUSE GASES SUCH AS HYDROFLUORO CARBON (HFCs).WASTE MANAGEMENT: LANDFILLS GENERATE METHANE EMISSIONS FROM THE DECOMPOSITION OF ORGANIC WASTE. CONSEQUENCE OF GLOBAL WARMING RISING SEA LEVELS: MELTING GLACIERS AND ICE SHEETS, COMBINED WITH THERMAL EXPANSION OF SEAWATER, CONTRIBUTE TO THE RISE IN SEA LEVELS, THREATENING COASTAL COMMUNITIES.EXTREME WEATHER EVENTS: GLOBAL WARMING LEADS TO MORE FREQUENT AND SEVERE WEATHER EVENTS LIKE HURRICANES, HEATWAVES, DROUGHTS, AND HEAVY RAINFALL.ECOSYSTEM DISRUPTION: SPECIES STRUGGLE TO ADAPT TO RAPIDLY CHANGING CLIMATES, RESULTING IN LOSS BIO-DIVERSITY HABITAT DESTRUCTION,AND ALTERED MIGRATION PATTERNS.

29. Role of Artificial Intelligence (AI) in Preventing Global Warming OPTIMIZING ENERGY EFFICIENCY SMART GRIDS AND DEMAND RESPONSE: AI-DRIVEN SMART GRIDS OPTIMIZE ELECTRICITY DISTRIBUTION, REDUCING ENERGY CONSUMPTION AND MINIMISING WASTE. AI ALGORITHMS can PREDICT ENERGY DEMAND AND ADJUST SUPPLY DYNAMICALLY, ENSURING THAT ENERGY IS USED MORE EFFICIENTLY.ENERGY MANAGEMENT IN BUILDINGS: AI CAN CONTROL HEATING, VENTILATION, AND AIR CONDITIONING (HVAC) SYSTEMS IN REAL-TIME, ENSURING OPTIMAL ENERGY USE BASED ON OCCUPANCY, WEATHER CONDITIONS, AND USAGE PATTERNS.INDUSTRIAL OPTIMIZATION: AI CAN OPTIMIZE INDUSTRIAL PROCESSES, IDENTIFYING INEFFICIENCIES, REDUCING ENERGY CONSUMPTION AND MINIMISING WASTE EMISSIONS. FOR EXAMPLE, AI SYSTEMS CAN BE USED in STEEL MANUFACTURING TO CUT ENERGY USE.2. RENEWABLE ENERGY INTEGRATION PREDICTING RENEWABLE ENERGY OUTPUT: AI can PREDICT the ENERGY OUTPUT IN RENEWABLE SOURCES LIKE SOLAR and WIND BY ANALYSING WEATHER DATA AND HISTORICAL TRENDS. THIS ALLOWS FOR BETTER INTEGRATION OF THESE VARIABLE ENERGY SOURCES INTO THE POWER GRIDSTORAGE OPTIMIZATION : AI CAN HELP OPTIMIZE THE CHARGING AND DISCHARGING CYCLES OF ENERGY STORAGE SYSTEMS, SUCH AS BATTERIES, TO ENSURE A CONSTANT SUPPLY OF RENEWABLE ENERGY EVEN DURING PERIODS OF LOW PRODUCTION.3. CARBON CAPTURE AND STORAGE (CCS) AI CAN IMPROVE THE EFFICIENCY AND COST-EFFECTIVENESS OF CARBON CAPTURE TECHNOLOGIES WHICH AIM to CAPTURE CO₂ EMISSIONS FROM POWER PLANTS AND OTHER INDUSTRIAL SOURCE LEARNING MODELS CAN PREDICT THE MOST EFFICIENT LOCATIONS FOR CAPTURING CO₂ AND OPTIMIZING STORAGE TECHNIQUES. DIRECT AIR CAPTURE (DAC) : AI ALGORITHMS CAN BE USED TO IMPROVE THE PERFORMANCE OF DAC SYSTEMS THAT CAPTURE CO₂ DIRECTLY FROM THE TMOSPHERE AND STORE UNDERGROUND.

30. H EAVY METAL TOXICITY AND AI AS PREVENTIVE MEASURE SOURCE : INTERNET

31. AI CAN PLAY A SIGNIFICANT ROLE IN PREVENTING HEAVY METAL TOXICITY IN THE ENVIRONMENT THROUGH SEVERAL KEY APPROACHES : MONITORING AND DETECTION : AI SYSTEMS CAN BE USED TO ANALYZE SATELLITE IMAGES, AND MONITORING DEVICES TO IDENTIFY METALS IN AIR, SOIL, AND WATER. MACHINE LEARNING ALGORITHMS CAN HELP IDENTIFY PATTERNS AND PREDICT AREAS AT RISK OF CONTAMINATION. PREDICTIVE MODELING: AI CAN PREDICT POTENTIAL CONTAMINATION EVENTS BY ANALYZING FACTORS SUCH AS INDUSTRIAL ACTIVITY, CLIMATE CONDITIONS, AND WASTE DISPOSAL PRACTICES. BY FORECASTING THESE RISKS, REGULATORY AGENCIES AND INDUSTRIES CAN TAKE PREVENTIVE ACTIONS BEFORE CONTAMINATION OCCURS.

32. BIOREMEDIATION AND ROLE OF AI IN BIOREMEDIATION Bio-removal of Emerging Pollutants by Advanced Bioremediation

33. BIOREMEDIATION REFERS TO THE USE OF BIOLOGICAL MICROORGANISMS, PLANTS, OR FUNGI, TO DEGRADE OR DETOXIFY ENVIRONMENTAL CONTAMINANTS, SUCH AS OIL SPILLS, HEAVY METALS, PESTICIDES, OR INDUSTRIAL WASTE. IT IS A SUSTAINABLE, ECO-FRIENDLY APPROACH TO ENVIRONMENTAL CLEANUP, AS IT UTILIZES NATURAL PROCESSES TO RESTORE POLLUTED ENVIRONMENTS. IN SITU BIOREMEDIATION EX SITU BIOREMEDIATION

34. AI ENHANCES VARIOUS ASPECTS OF BIOREMEDIATION, IMPROVING ITS SCALABILITY AND EFFECTIVENESS:MICROBIAL SELECTION AND OPTIMIZATION: AI CAN BE USED TO ANALYZE ENVIRONMENTAL DATA AND IDENTIFY THE MOST SUITABLE MICROORGANISMS FOR SPECIFIC CONTAMINANTS. MACHINE LEARNING MODELS CAN PREDICT THE EFFECTIVENESS OF DIFFERENT MICROBES IN DEGRADING POLLUTANTS, ALLOWING FOR MORE TARGETED BIOREMEDIATION STRATEGIES. AUTOMATION OF BIOREMEDIATION SYSTEMS: AI CAN BE INTEGRATED INTO AUTOMATED BIOREMEDIATION SYSTEMS, SUCH AS BIOREACTORS OR BIOFILTERS. THESE SYSTEMS CAN ADAPT TO CHANGING CONDITIONS AND MANAGE MICROBIAL POPULATIONS IN REAL TIME, ENHANCING THE SPEED AND EFFICIENCY OF CONTAMINANT REMOVAL.IDENTIFICATION OF NOVEL BIOREMEDIATION AGENTS: AI TOOLS, SUCH AS DEEP LEARNING AND LEARNING BIOLOGY, CAN ASSIST IN IDENTIFYING NEW STRAINS OF FUNGI, OR ENZYMES WITH THE POTENTIAL FOR BIOREMEDIATION. BY ANALYZING GENOMIC AND ENVIRONMENTAL DATA, AI CAN GUIDE RESEARCHERS TOWARD NOVEL BIOLOGICAL SOLUTIONS TO POLLUTION.

35. POLLUTED VS UNPOLLUTED ENVIRONMENT POLLUTED WATER BODY UNPOLLUTED WATER BODY OF ANTARTICA REGION

36. DENSE SMOG REGION CLEAN REGION OF ANTARTICA

37. CARRIER OPPORTUNITIES FOR STUDENTS IN AI AND ENVIRONMENTAL STUDIES ENVIRONMENTAL DATA SCIENTIST AI POWERED CLIMATE ANALYST WILDLIFE CONSERVATION TECHNOLOGIST AI BASED WASTE MANAGEMENT EXPERT ACADEMIC RESEARCHER SUSTAINABILITY CONSULTANT

38. CHALLENGES AND ETHICAL CONSIDERATIONS DATA PRIVACY COLLECTION OF ENVIRONMENTAL DATA MUST BE BALANCED WITH PRIVACY CONCERNS. BIAS IN AI ALGORITHM ENVIRONMENTAL DATASETS MAY CONTAIN BIASES,LEADING TO INACCURATE OR UNFAIR OUTCOMES. ENERGY CONSUMPTION OF AI AI TECHNOLOGIES THEMSELVES CONSUME SIGNIFICANT ENERGY;THEIR ENVIRONMENTAL IMPACT SHOULD BE CONSIDERED. ACCESS AND EQUITY ENSURING THAT AI DRIVEN SOLUTIONS ARE ACCESSIBLE TO ALL COUNTRIES, ESPECIALLY IN DEVELOPING REGIONS.

39. FUTURE OF AI IN ENVIRONMENTAL MANAGEMENT AI FOR CIRCULAR ECONOMY AI CAN BE A KEY ENABLER OF A CIRCULAR ECONOMY BY OPTIMIZING RECYCLING PROCESSES AND PROMOTING SUSTAINABLE PRODUCT LIFE CYCLES. GLOBAL AI COLLABORATION BUILDING INTERNATIONAL PARTNERSHIPS TO LEVERAGE AI FOR ADDRESSING GLOBAL ENVIRONMENTAL CHALLENGES. INTEGRATION WITH IOT AI AND INTERNET OF THINGS (IOT) CAN WORK TOGETHER TO CREATE SMART ECOSYSTEMS FOR SUSTAINABLE RESOURCE MANAGEMENT.

40. CONCLUSION AI PLAYS A CRUCIAL ROLE IN ADDRESSING URGENT ENVIRONMENTAL CHALLENGES BY ENHANCING DECISION-MAKING, IMPROVING MONITORING, AND OPTIMIZING RESOURCE USE. IT IS BELIEVED THAT WITH CONTINUED INNOVATION AND ETHICAL CONSIDERATIONS, AI CAN BE A GAME-CHANGER IN THE PURSUIT OF A SUSTAINABLE FUTURE. CALL TO ACTION TO EMPHASIZE THE NEED FOR COLLABORATIVE EFFORTS BETWEEN GOVERNMENTS, INDUSTRIES, AND AI EXPERTS TO SCALE UP AI-DRIVEN ENVIRONMENTAL SOLUTIONS.

41. ACKNOWLEDGEMENTS: PROF. SUDHIR MEHROTRA, HOD, DEPT.OF BIOCHEMISTRY (LU) FOR ALL LOGISTIC SUPPORT TO MEET THE PLATEFORM MR. ANUDIT PANDEY (GRDUATE STUDENT) FOR DRAFTING THE PRESENTATION DR. PRADEEP UPADHYAY (NGBDU, PRAYAGRAJ) FOR TECHNICAL INPUTS ON AI AND ENVIRONMENTAL SCIENCE DR.RAJESH K. KESHARWANI (NGBDU, PRAYAGRAJ) FOR PROVIDING INPUTS OVER AI AND MACHINE LEARNING.

42. REFRENCES Munakata T. Fundamentals of the New Artificial Intelligence: Neural, Evolutionary, Fuzzy and More. Second Edition. Cleveland, OH: Springer; 2008. A. Fabregat et al.Using Machine Learning to estimate the impact of different modes of transport and traffic restriction strategies on urban air quality.Urban Clim .(2022). Recent applications of AI to environmental disciplines: A review, January 2024,The Science of The Total Environment. Authors : Aniko Konya,Peyman Nematzadeh .

43. Thank You