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Technical solutions for waste classification and management: A mini-review
Shreya M1, Nimal Yughan V1, Jyotika Katyal1
1School of Electronics Engineering, Vellore Institute of Technology, Chennai, India.
Summary
Automated waste segregation using convolutional neural networks and Internet of Things (IoT) systems offers a solution to India
Area of Science:
- Environmental Science
- Computer Science
- Engineering
Background:
- Rapid population growth and urbanization in India have led to escalating waste generation challenges.
- Current waste management systems struggle with effective segregation and disposal due to a lack of public awareness and infrastructure.
- There is a critical need for advanced technologies to improve municipal solid waste management.
Purpose of the Study:
- To review recent literature on automated waste segregation and management technologies.
- To evaluate the efficacy of convolutional neural network (CNN) architectures for waste classification.
- To explore Internet of Things (IoT)-based models for efficient waste monitoring and collection.
Main Methods:
- Review of scientific literature focusing on CNNs for waste image classification.
- Analysis of image processing techniques versus sensor-based methods for waste segregation.
- Evaluation of IoT models for waste management, considering sensors, microcontrollers, and communication protocols (e.g., LoRa, GSM, Zigbee, Wi-Fi).
Main Results:
- Convolutional Neural Networks (CNNs) demonstrate significant potential for accurate waste classification through image processing.
- Image processing methods are often preferred over traditional sensors for detailed waste categorization.
- IoT-based systems offer optimized waste collection routes, reduced costs, and efficient data transmission for waste monitoring.
Conclusions:
- Automated waste segregation using CNNs and IoT is crucial for effective municipal solid waste management in rapidly urbanizing regions.
- Technological advancements in image processing and IoT can significantly improve waste handling efficiency and resource utilization.
- Further research and implementation of these integrated systems are recommended to address the growing waste crisis.
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