"AI for Clean Air and Public Health: Innovations in Environmental Monitoring"
Environmental Health and
Air Quality Monitoring:
Objective:
Explore the transformative potential of artificial intelligence in Environmental Health and Air Quality Monitoring, focusing on AI applications to track the impact of environmental factors on public health, real-time air quality monitoring with pollution prediction using machine learning, and leveraging AI for epidemiological studies to comprehend environmental health risks.
Theme:
This session aims to unravel the groundbreaking applications of artificial intelligence in revolutionizing environmental health and air quality monitoring. Attendees will delve into AI-driven solutions for precisely tracking and understanding the impact of environmental factors on public health, implementing real-time air quality monitoring and pollution prediction models through machine learning, and utilizing AI in epidemiological studies to gain deeper insights into environmental health risks. The session underscores the critical role of AI in providing actionable data to safeguard public health, mitigate environmental risks, and foster informed decision-making for a healthier, cleaner future.
Environmental Health and Air Quality
Monitoring is
contribution to
The
Sustainable
Development Goals:
Goal 3: Good Health And Well Being
Discuss how AI assists and tracks environmental impacts on public health, predicting
air quality and aiding epidemiological studies.
Assessing heat-related illnesses, water quality, noise pollution, and ways promoting
green spaces for better health.
Goal 7: Affordable and Clean Energy
Discover the transformative potential of AI-driven innovations in renewable energy
technologies, bolstering accessibility and sustainability of energy solutions
globally, while simultaneously addressing Environmental Health and Air Quality
Monitoring concerns.
Investigate how thorough research and analysis in AI are crucial for equitable
access to dependable and sustainable energy sources, driving forward global energy
security and resilience.
Goal 12: Responsible Consumption and Production
Dive into how AI plays a crucial role in monitoring environmental factors affecting
public health, from real-time air quality tracking to conducting epidemiological
studies. This encompasses addressing concerns like Air Quality and Respiratory
Health, Climate Change, and Infectious Diseases, among others.
Explore approaches for deploying AI-based climate change monitoring methods, aiming
to mitigate the adverse effects of environmental factors on public health and foster
sustainable practices.
Goal 13: Climate Action
Explore AI's role in tracking environmental factors on public health, from real-time
air quality monitoring to epidemiological studies, addressing diverse issues such as
climate change and infectious diseases.
Investigate AI-driven climate change mitigation strategies, integrating resilience
into urban planning to address environmental justice and health disparities.
Who Can Join
Research Scholars
Technology Experts
Students & Alumini’s
Editorial Board Members of Journals
Government Officials
Industry Professionals
Tracks
Topics of Interest for Submission include, but are not limited to:
1 AI applications for tracking the impact of environmental factors on public health.
2 Real-time air quality monitoring and pollution prediction using machine learning.
3 Epidemiological studies using AI to understand environmental health risks.
4 Air Quality and Respiratory Health
5 Climate Change and Infectious Diseases
6 Vector-Borne Disease Surveillance
7 Heat-Related Illnesses and Climate Variability
8 Water Quality and Gastrointestinal Health
9 Noise Pollution and Mental Health
10 Green Spaces and Cardiovascular Health
11 Chemical Exposure and Cancer Epidemiology
12 Extreme Weather Events and Public Health Preparedness
13 Environmental Justice and Health Disparities
Outcomes:
- Participants will gain insights into how AI applications contribute to a comprehensive understanding of the intricate relationship between environmental factors and public health, paving the way for targeted interventions.
Enhanced Public Health Understanding:
- The session aims to showcase the efficacy of machine learning in providing real-time air quality data and accurate pollution predictions, enabling proactive measures to mitigate the impact on public health.
Timely Air Quality Monitoring and Pollution Prediction:
- Attendees will explore how AI-driven epidemiological studies offer advanced analytics, uncovering complex relationships between environmental factors and health risks, leading to more effective risk mitigation strategies.
Advanced Epidemiological Insights:
- The integration of AI in environmental monitoring is expected to empower policymakers, healthcare professionals, and communities with data-driven insights, fostering informed decision-making to promote cleaner air and better public health outcomes
Informed Decision-Making for Cleaner Environments:
Scope & Benefits of Attending Beyond Intelligence 2024 conference
Discover the transformative potential of Beyond Intelligence 2024 with a focus on sustainable innovation and technology-driven solutions to address pressing environmental challenges. Learn,
Benefits of Attending Beyond Intelligence 2024
- Resource Efficiency and Infrastructure Resilience: Learn about strategies to optimise resource use and enhance the resilience of critical infrastructure.
- Sustainable Energy and Environmental Conservation: Dive into discussions on renewable energy sources, biodiversity preservation, and effective environmental conservation practices.
- Innovation for Sustainable Development: Engage in sessions promoting innovation, environmental awareness, and the adoption of eco-friendly practices.
- Responsible Business Practices: Gain insights into fostering sustainability through ethical financial strategies, transparent corporate operations, and responsible business practices.
- Inclusive Decision-Making for Sustainability: Understand the role of human behaviour, societal values, and cultural perspectives in driving inclusive decision-making processes for sustainable development.
Author Guidelines
Guidelines for Abstract Submission:
- Language: Abstracts must be written in English.
- Length: Limited to one paragraph with 200-250 words.
- Format: Submit in MS Word (.doc or .docx) document format.
- Content: Abstracts should provide an informative summary of the original work. Include a brief biography with your abstract, following the example provided in the template.
- Formatting: Center-align the Title, Author's Names, and Affiliations. Underline the presenting author's name.
- Submission: Please submit your abstract through the designated submission portal.
- Acknowledgment: Upon abstract submission, you will receive an acknowledgment email within three working days.
Evaluation Process
Guidelines for Full Paper Submission
If your abstract has been accepted and the registration fee for Beyond Intelligence 2024 has been paid, you are invited to submit the full paper. Please adhere to the following guidelines for the submission:
- Total number of pages: 6-8 in double-column format
- Language: English (checked for grammar and language errors)
- Tables, figures, and images should be properly named and of high quality.
- Keywords should be written in lowercase letters (except for names/scientific names) and separated by commas.
- Affiliation names, including the country, must be provided.
- Each paper should be structured into the following sections:
- Background, Motivation, and Objective
- Statement of Contribution/Methods
- Results, Discussions, and Conclusions
Once your full paper is prepared according to the above instructions, please proceed to submit it through the provided link. Submit your Full paper Here.
Session Lists
