Workshop Registration End Date :20 Apr 2026

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Virtual Workshop

AI for Waste Reduction and Resource Optimization

Skills you will gain:

About Workshop:

The workshop AI for Waste Reduction and Resource Optimization is designed to explore how artificial intelligence can support sustainable decision-making across industries by improving efficiency, minimizing waste, and maximizing resource utilization. As organizations face increasing environmental and operational challenges, AI-driven tools and data analytics are becoming essential for identifying inefficiencies, forecasting resource demand, optimizing processes, and enabling circular economy practices.

Aim:

To help participants understand how AI can reduce waste, optimize resource use, and support sustainable, data-driven decision-making.

Workshop Objectives:

  • To introduce the role of AI in waste reduction and resource optimization.
  • To explore data-driven methods for improving operational efficiency.
  • To understand AI applications in sustainability and smart decision-making.
  • To examine strategies for minimizing waste and maximizing resource use.
  • To provide practical insights into AI-enabled sustainable solutions.

What you will learn?

📅 Day 1 — QUANTIFY — AI-Driven Waste Identification & Characterization

  • The Visual Intelligence of Circular Systems: Leveraging state-of-the-art Object Detection (like YOLO architectures) for automated recycling and waste sorting.
  • Dataset Challenges in Sustainability: Overcoming the scarcity of labeled environmental datasets using synthetic data generation and transfer learning.
  • Multimodal Data Integration: Combining RGB imagery with hyperspectral or infrared data to identify material compositions that the human eye cannot see.

🛠️ Hands-on:

  • Notebook Lab: Training a lightweight Convolutional Neural Network (CNN) in Google Colab to classify different types of recyclable waste (plastics, glass, paper) from a standard image dataset.

📅 Day 2 — PREDICT — Demand Forecasting & Resource Conservation

  • Predictive Modeling for Zero-Waste: Utilizing advanced regression and time-series models to predict resource consumption spikes and avoid surplus perishables or raw materials.
  • Feature Engineering for Resource Optimization: Integrating external variables such as weather, market trends, and historical IoT sensor data to create robust forecasting pipelines.
  • Predictive Maintenance as a Waste Reducer: Using machine learning to predict machine failures before they happen, reducing scrap rates and energy waste.

🛠️ Hands-on:

  • Notebook Lab: Building an XGBoost or Random Forest regression model to forecast daily resource or energy demand and optimize inventory levels to minimize waste.

📅 Day 3 — OPTIMIZE — Operations Research & Reinforcement Learning for Circular Systems

  • Smart Logistics & Route Optimization: Using genetic algorithms and heuristics to minimize the carbon footprint and fuel waste in waste collection and distribution networks.
  • Reinforcement Learning (RL) in Resource Allocation: Introduction to how RL agents can learn to dynamically allocate resources (like water or grid energy) in real-time.
  • AI and Life Cycle Assessment (LCA): Discussing how AI can be mapped to standard LCA frameworks to prove the quantifiable carbon and waste reduction for peer-reviewed academic publication.

🛠️ Hands-on:

  • Notebook Lab: Solving a classic vehicle routing problem (VRP) for smart waste collection using Python optimization libraries to find the most fuel-efficient and resource-optimized routes.

Mentor Profile

Assistant Professor
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Fee Plan

StudentINR 2499/- OR USD 75
Ph.D. Scholar / ResearcherINR 3499/- OR USD 85
Academician / FacultyINR 4499/- OR USD 95
Industry ProfessionalINR 6499/- OR USD 115

Important Dates

Registration Ends
20 Apr 2026 Indian Standard Timing 4: 30 PM IST
Workshop Dates
20 Apr 2026 to
22 Apr 2026  Indian Standard Timing 05: 30PM IST

Get an e-Certificate of Participation!

2024Certfiacte

Intended For :

  • Students interested in AI and sustainability
  • Researchers and Ph.D. scholars in related fields
  • Academicians and faculty members
  • Industry professionals in waste management, manufacturing, and supply chain
  • AI/ML practitioners and data analysts
  • Entrepreneurs working on sustainable solutions

Career Supporting Skills

Workshop Outcomes

  • Understand the role of AI in waste reduction and resource optimization.
  • Identify opportunities to apply AI for improving efficiency and sustainability.
  • Gain insights into data-driven strategies for minimizing waste and maximizing resource use.
  • Explore practical applications of AI in sustainable operations and decision-making.
  • Develop a clearer perspective on implementing intelligent solutions for resource management.