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Artificial Intelligence and The Sustainable Development Goals (SDGs) Adoption of AI in Agriculture Industry.pptx

BC Chew
BC Chew

Artificial Intelligence and The Sustainable Development Goals (SDGs) Adoption of AI in Agriculture Industry

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Artificial Intelligence and The Sustainable
Development Goals (SDGs): Adoption of AI in
Agriculture Industry
8 DECEMBER 2023
BIODATA EDUCATION:
1. University Technology Malaysia (UTM)
o Bachelor of Civil Engineering
o Master of Technology Management
2. University of Edinburgh Scotland
o PHD - Science and Technology
Get to know more about when you google “bcchew”
RESEARCH INTEREST:
o Green Technology Development & Deployment
o Sustainable Management
Associate Professor Ts. Dr. Chew Boon Cheong
Sustainable Development Goals (SDGs)
The Sustainable Development Goals (SDGs),
were adopted by the United Nations in 2015
as a universal call to action to end poverty,
protect the planet, and ensure that by 2030
all people enjoy peace and prosperity
The 17 SDGs are integrated — they recognize
that action in one area will affect outcomes
in others, and that development must
balance social, economic and environmental
sustainability
1
2
Artificial Intelligence and The Sustainable Development Goals (SDGs) Adoption of AI in Agriculture Industry.pptx
CATEGORIZING THE SDGS IN TERMS OF AI IMPACT
ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE
DEVELOPMENT GOALS (AI4SDGS)
Artificial intelligence (AI) is a
disruptive technology that can
revolutionize society and an
enabling technology that can
foster societal progress
AI development should
be used to promote the
achievement of the
global SDGs
AI research organizations,
universities, and companies all
have a responsibility to use AI
to enhance the long-term
growth of society, economy,
and environment
The global effort to AI to
assist sustainable
development, human rights,
and whole of humanity,
leaving no one behind

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Artificial Intelligence and The Sustainable Development Goals (SDGs) Adoption of AI in Agriculture Industry.pptx

  • 1. Artificial Intelligence and The Sustainable Development Goals (SDGs): Adoption of AI in Agriculture Industry 8 DECEMBER 2023
  • 2. BIODATA EDUCATION: 1. University Technology Malaysia (UTM) o Bachelor of Civil Engineering o Master of Technology Management 2. University of Edinburgh Scotland o PHD - Science and Technology Get to know more about when you google “bcchew” RESEARCH INTEREST: o Green Technology Development & Deployment o Sustainable Management Associate Professor Ts. Dr. Chew Boon Cheong
  • 3. Sustainable Development Goals (SDGs) The Sustainable Development Goals (SDGs), were adopted by the United Nations in 2015 as a universal call to action to end poverty, protect the planet, and ensure that by 2030 all people enjoy peace and prosperity The 17 SDGs are integrated — they recognize that action in one area will affect outcomes in others, and that development must balance social, economic and environmental sustainability 1 2
  • 5. CATEGORIZING THE SDGS IN TERMS OF AI IMPACT
  • 6. ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE DEVELOPMENT GOALS (AI4SDGS) Artificial intelligence (AI) is a disruptive technology that can revolutionize society and an enabling technology that can foster societal progress AI development should be used to promote the achievement of the global SDGs AI research organizations, universities, and companies all have a responsibility to use AI to enhance the long-term growth of society, economy, and environment The global effort to AI to assist sustainable development, human rights, and whole of humanity, leaving no one behind
  • 7. 1 2 3 Artificial intelligence (AI) is the development of computer systems that can do tasks that typically require human intelligence Learning, reasoning, solving problems, perceiving, comprehending language, and even making decisions are all included in these tasks AI is an interdisciplinary science with multiple approaches, but advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry ARTIFICIAL INTELLIGENCE
  • 8. ARTIFICIAL INTELLIGENCE IN AGRICULTURE AI is widely employed in several fields, and its applications are progressing, becoming more precise and performant, including manufacturing, healthcare, banking and finance, aviation and hospitality AI in the agricultural sector includes innovative technologies such as field sensors, drones, farm management software tools, automated machinery and water and fertilizer management solutions
  • 9. END HUNGER, ACHIEVE FOOD SECURITY AND IMPROVED NUTRITION AND PROMOTE SUSTAINABLE AGRICULTURE UNIVERSAL ACCESS TO SAFE AND NUTRITIOUS FOOD END ALL FORMS OF MALNUTRITION DOUBLE THE PRODUCTIVITY AND INCOMES OF SMALL-SCALE FOOD PRODUCERS SUSTAINABLE FOOD PRODUCTION AND RESILIENT AGRICULTURAL PRACTICES MAINTAIN THE GENETIC DIVERSITY IN FOOD PRODUCTION INVEST IN RURAL INFRASTRUCTURE, AGRICULTURAL RESEARCH, TECHNOLOGY AND GENE BANKS PREVENT AGRICULTURAL TRADE RESTRICTIONS, MARKET DISTORTIONS AND EXPORT SUBSIDIES ENSURE STABLE FOOD COMMODITY MARKETS AND TIMELY ACCESS TO INFORMATION THE TARGETS
  • 10. FOOD AGRICULTURE Agriculture is on the frontlines of nearly all urgent global challenges, from hunger to climate change to rising inequality. Investment in agriculture has an important poverty- reduction effect especially amongst the poorest people. For the past five years, hunger has been on the rise. Every night, about 690 million people go to bed hungry. Food production and agriculture are important because they support more people than any other sector on the planet. Sustainable food systems and agricultural practices can adapt, build resilience, and mitigate emissions.
  • 11. AI IN AGRICULTURE CAN PLAY A STRATEGIC ROLE At a global level, the agricultural sector has a value of 3,6 trillion dollars, providing the 4% of the global gross domestic product (GDP) with a stable measure during the last twenty years (FAO, 2022). In some developing countries, it accounts for more than 25% of GDP (FAO, 2022). Such a critical industry stands as a food and energy base of the new economy, mainly because it ensures food security (Magasumovna et al., 2017).
  • 12. VARIOUS IMPLICIT PROBLEMS HAVE BEEN HISTORICALLY CHALLENGING THE AGRICULTURAL SECTOR THE NUMBER OF WORKERS WHICH IS SIGNIFICANTLY COLLAPSED WITH A PROGRESSIVE DIFFICULT-TO-EMPLOY WORKFORCE between 2000 and 2022, the global workforce employed in agriculture collapsed from 40% to 27%, representing a reduction of 177 million people (FAO, 2022). FOR EXAMPLE 01
  • 13. VARIOUS IMPLICIT PROBLEMS HAVE BEEN HISTORICALLY CHALLENGING THE AGRICULTURAL SECTOR DECREASING PRODUCTIVITY CAUSED BY CLIMATE CHANGE AND DESERTIFICATION with a decline of 134 million hectares of cultivated land between 2000 and 2020 (FAO, 2022). FOR EXAMPLE 02
  • 14. FOR THIS REASON… achieving food security in a sustainable way is one of the objectives included in the United Nations (UN) 2030 Sustainable Goals with the Zero-Hunger program (European Commission, 2017). as a result, a growing need to modify agricultural methods and available technologies so that “maximum crops can be attained and human effort can be reduced” (Saad et al., 2021). a country can be considered food secure “if food is available, accessible, nutritious and stable across the other three dimensions” (Musa and Basir, 2021). the latest FAO World Food and Agriculture – Statistical Yearbook (2022), in 2021, 770 million people were undernourished, with an increment of 150 million from 2020 (Wijerathna-Yapa and Pathirana, 2022).
  • 15. APPLICATIONS IN AGRICULTURE The topic of AI applications in agriculture is an opportunity to address some of the cited problems creating new business scenarios in the agricultural sector (Amoussohoui et al., 2022). In the last years, the agricultural sector has started to integrate information and communication technologies in traditional farming with the aim of improving crop yield efficiency, reducing costs and optimizing process inputs with the usage of data. Innovation technology, digitalization and AI could, therefore, represent some of the ways and strategies to mitigate the above-mentioned issues, achieve sustainability goals and manage the climate change challenge (DiVaio et al., 2020; Yela Aranega et al., 2022).
  • 16. AGRICULTURAL SECTOR CULTIVATION OF PLANTS ANIMAL PRODUCTION FISH FARMING
  • 17. PROBLEMS TO SOLVE - OBJECTIVE TO ACHIEVE Increase efficiency and optimization maximizing farm returns Manage the environmental impact and external changes Predict and manage the farm complexity Feed the increasing global population-food security
  • 18. TECHNOLOGY USED Decision Support System (DSS) Artificial Intelligence and Machine Learning Big Data Analytics Internet of Things (IOT) Drone Robots
  • 19. TECHNOLOGY USED Cloud Computing Geographical Indication System (GIS) Biotechnology Blockchain Autonomous Devices
  • 20. APPLICATIONS IN AGRICULTURE Agronomic Planning and Economic Applications Precision Farming and Agronomic Applications
  • 21. APPLICATIONS IN AGRICULTURE Water Optimization and Environmental Management Applications Food Supply Chain Applications and Traceability
  • 22. Platform business model in the food supply chain Agritech 4.0 with integrated smart food supply chain Supply chain management 5.0 New information- based system based on traceability POSSIBILITY TO LEAD A NEW BUSINESS MODEL
  • 25. CONNECTS TO SUSTAINABILITY ISSUES Reduce The Use Of Pesticides, Heavy Metals and Nitrates Which Pollute Agricultural Soil and Water Reduce The Consume and Loss Of Water Climate-oriented and Ecologically Friendly Applications • Food Security In A Sustainable Way • Making Sustainable The Ecological Impact Of Food Production
  • 26. ADVANTAGES AI IN AGRICULTURE Efficiency Benefits and Productivity Increase Food Safety and Easy Compliance Organizational Advantages and Decision Support Environmental Benefits
  • 27. DISADVANTAGES AI IN AGRICULTURE Difficult to Create A Unique System For Different Areas and Crops Complexity to Realize Environmental Impact in The Food Chain From Genetically Engineered Crops Which Will Destroy The Actual Natural Habitat Carbon Dioxide Emission As A Consequence Of Intensive Use of Energy The System Cannot Work Without Power Supply
  • 28. BARRIERS AI IN AGRICULTURE Lack of Equipment, Internet Access, Storage Capacity and High-quality Data Mismatch Between Applications and Farmer Practical Needs Farmers Lack of Technical Knowledge About ICT and Other Emerging Technologies High Investment Costs and Low Perceived Effectiveness Lack of Integration and Complexity of The Food Supply Chain User Psychological Barriers to Adoption Data Control and Data Security Large Energy Consumption and Unsustainability
  • 29. PRACTICAL IMPLICATIONS Support Farmers In The Decision-making Process Support Everyday Farm Operations Increasing Efficiency & Effectiveness Provide Farmers Useful Forecasts To Manage The Farm Unpredictability Planning Their Activity Provide Farmers New Solutions With Integrated Technologies
  • 30. POLICY IMPLICATIONS Governments should use the agricultural data to improve policy-making and decision- making learning from data Governments should create advisory units to support the farmers awareness about complex technological tasks Governments should subscribe new investments to enhance the technological transition Governments should support the social innovation to engage younger generations to be more involved in the honey and bee industry
  • 32. CONCLUSION AI solutions agricultural sector by offering sound opportunities to farmers and entrepreneurs in the field to support their decision-making process and increase the farm’s profitability. Still, fostering sustainability practices.
  • 34. ARTIFICIAL INTELLIGENCE USES IN SUSTAINABLE DEVELOPMENT GOALS (SDGs) Poverty Mapping in Big Data Analytics Source: World Bank Poverty and Inequality Platform (2022) Unemployment Forecasts Source: (AI: A Key Enabler for Sustainable Development Goals, 2018)
  • 35. ARTIFICIAL INTELLIGENCE USES IN SUSTAINABLE DEVELOPMENT GOALS (SDGs) Analytics of Satellite Images and Agro- Meteorological Monitoring Autonomous Mowing, Picking And Harvesting, Weed Control, Sorting and Packaging, Etc Source: (AI: A Key Enabler for Sustainable Development Goals, 2018)
  • 36. ARTIFICIAL INTELLIGENCE USES IN SUSTAINABLE DEVELOPMENT GOALS (SDGs) Predictive Healthcare - Make More Effective and Efficient Operational and Clinical Decisions Cognitive Healthcare - Provides Decisions Based on its Capacity to Gather and Identify Data Source: (AI: A Key Enabler for Sustainable Development Goals, 2018)
  • 37. ARTIFICIAL INTELLIGENCE USES IN SUSTAINABLE DEVELOPMENT GOALS (SDGs) Global Classroom (Mixed Reality, Computer Vision and Monitoring) Machine Teaching (An Emerging Sub- Field of AI) Source: (AI: A Key Enabler for Sustainable Development Goals, 2018)
  • 38. ARTIFICIAL INTELLIGENCE USES IN SUSTAINABLE DEVELOPMENT GOALS (SDGs) Monitoring and Track Gender Bias Women's Economic Empowerment (Innovative Skills Development and Training Technologies) Source: (AI: A Key Enabler for Sustainable Development Goals, 2018)
  • 39. ARTIFICIAL INTELLIGENCE USES IN SUSTAINABLE DEVELOPMENT GOALS (SDGs) Smart Water Monitoring and Management System Smart Renewable Energy Grid Source: (AI: A Key Enabler for Sustainable Development Goals, 2018)
  • 40. ARTIFICIAL INTELLIGENCE USES IN SUSTAINABLE DEVELOPMENT GOALS (SDGs) Improve Job Security (Utilizing AI to Automate Mundane Tasks) AI-Powered Training Solutions Source: (AI: A Key Enabler for Sustainable Development Goals, 2018)
  • 41. ARTIFICIAL INTELLIGENCE USES IN SUSTAINABLE DEVELOPMENT GOALS (SDGs) Industry 4.0 (Smart Factory) Robotic Assistive System Source: (AI: A Key Enabler for Sustainable Development Goals, 2018)
  • 42. ARTIFICIAL INTELLIGENCE USES IN SUSTAINABLE DEVELOPMENT GOALS (SDGs) Smart City (Municipality That Uses ICT) Energy Consumption Monitor Source: (AI: A Key Enabler for Sustainable Development Goals, 2018)
  • 43. ARTIFICIAL INTELLIGENCE USES IN SUSTAINABLE DEVELOPMENT GOALS (SDGs) Smart Disaster Response Capture Information for Evaluation from Camera Systems or Marine Vehicles Source: (AI: A Key Enabler for Sustainable Development Goals, 2018)
  • 44. ARTIFICIAL INTELLIGENCE USES IN SUSTAINABLE DEVELOPMENT GOALS (SDGs) A Transparent Digital Earth (tackling natural disasters, air pollution, illegal deforestation, fishing, poaching, etc) Smart Agriculture and Food Systems Source: (AI: A Key Enabler for Sustainable Development Goals, 2018)
  • 45. ARTIFICIAL INTELLIGENCE USES IN SUSTAINABLE DEVELOPMENT GOALS (SDGs) Reduce the amount of time and resources required for data gathering, analysis, and option creation, and allocate those resources instead to more challenging tasks like strategic decision-making, dialogue, negotiation, and trust-building Algorithms driven by AI can sift through enormous volumes of data to find possible partners that share their values, objectives, and vision
  • 46. REFERENCES AI-Ethics frameworks with the UN SDGs - Google Search. (n.d.). Www.google.com. Retrieved November 28, 2023, from https://www.google.com/search?q=AI- Ethics+frameworks+with+the+UN+SDGs&sca_esv=585931027&rlz=1C1CHBD_enMY916MY916&tbm =isch&sxsrf=AM9HkKkcFwYUAnhapb4vF0jUmqlLIqNTjA:1701179068316&source=lnms&sa=X&ved= 2ahUKEwisxsPw6eaCAxV4aGwGHZtPC3EQ_AUoAnoECAEQBA&biw=1229&bih=591&dpr=1.56#imgr c=JytYDzzkk0PRgM AI: A Key Enabler for Sustainable Development Goals. (2018, April 27). Www.slideshare.net. https://www.slideshare.net/AlaaKhamis/ai-a-key-enabler-for-sustainable-development-goals- 95241642
  • 47. REFERENCES AI4SDGs-Research-Program-2020. (2020). Ai-For-Sdgs.academy. https://www.ai-for- sdgs.academy/AI4SDGs-Research-Program-2020 Artificial Intelligence for Sustainable Development Goals (AI4SDGs) Research Program. (2020). Ai-For- Sdgs.academy. https://www.ai-for-sdgs.academy/ai4sdgs-research-program Burns, E. (2021). What Is Machine Learning and Why Is It Important? SearchEnterpriseAI. https://www.techtarget.com/searchenterpriseai/definition/machine-learning-ML IBM. (2023). What is Machine Learning? IBM. https://www.ibm.com/topics/machine-learning Nasir, O., Javed, R. T., Gupta, S., Vinuesa, R., & Qadir, J. (2023). Artificial intelligence and sustainable development goals nexus via four vantage points. Technology in Society, 72, 102171. https://doi.org/10.1016/j.techsoc.2022.102171