Identifying Waste Management Strategy and Activation Model for Tanguar Haor Region
Climate Adaptation & Resilience
- 50+ organizations
- 2024-2027
- 12 Publications
Lead: Dr. Sarah Johnson
Summary
Since February 2022, this ongoing project, associated with Bangladesh’s Ministry of Civil Aviation and Tourism, develops waste management strategies and adaptive practices in Tanguar Haor. Daahuk has facilitated over 200 large-capacity waste bins for boatmen, riverside markets, and communities, identifying leaders from trade groups for supervision. Low-cost logistics support removes waste from this pristine ecosystem, incorporating a subsidy-based volunteering model for financial inclusion to encourage participation. With the Bangladesh Tourism Board as patron, Daahuk ensures inclusive regional facilitation. Aligned with Daahuk’s philosophy of Integrated Social Capital, it strengthens networks for long-term resilience, complementing eco-tourism and conservation efforts. This initiative protects biodiversity, promotes community ownership, and integrates with broader climate-focused projects, driving sustainable growth in vulnerable wetlands through collaborative action and innovation.
Key Objectives
- Climate Intelligence: Develop AI systems that forecast and mitigate climate risks in vulnerable regions.
- Social Impact Analytics: Use data to identify inequities and design targeted social interventions.
- Sustainable Development: Support environmental restoration and sustainable resource use through predictive modeling.
- Collaborative Innovation: Build partnerships across sectors to ensure ethical and inclusive AI implementation.
Key Objectives
50+ Organization
25+Countries of operation
100k+Beneficiaries reached
Key Challenges We Aim to Overcome
The project faces several challenges, including limited access to reliable and diverse data, ethical and privacy concerns in AI usage, and difficulties in ensuring transparency and fairness. Collaboration across global organizations can lead to coordination complexities, while technological and infrastructure gaps in some regions may hinder implementation
Data Accessibility and Quality
Obtaining reliable, diverse, and up-to-date datasets from different regions can be difficult
Ethical and Privacy Concerns
Ensuring transparency and fairness in AI decisions is crucial to prevent bias and misuse
Limited Technological Infrastructure
Many developing regions lack the resources, connectivity needed to effectively use AI solutions.
Project Highlights
Explore our journey through impact-driven innovations showcased in our Project Gallery
