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Smart textile waste collection system - Dynamic route optimization with IoT
Antti Martikkala1, Bening Mayanti2, Petri Helo3
1Unit of Automation Technology and Mechanical Engineering, Tampere University, Korkeakoulunkatu 7, FI-33720, Tampere, Finland; Department of Mechanical and Industrial Engineering, Norwegian University of Science and Technology, Richard Birkelands Vei 2b, NO-7034, Trondheim, Norway.
Digitalization improves textile recycling. Smart bins with sensors enable dynamic route optimization for waste collection, reducing costs by 7.4% and CO2 emissions by 10.2%.
Area of Science:
- Environmental Science
- Industrial Ecology
- Sustainable Systems
Background:
- Textile production's environmental impact necessitates improved recycling systems.
- Current textile waste collection lacks data-driven optimization, leading to inefficiencies.
- Digitalization and sensor technology offer potential solutions for waste management.
Purpose of the Study:
- To develop and test a low-cost, open-source data collection system for textile waste.
- To integrate smart bins with dynamic route optimization for efficient collection.
- To evaluate the cost and environmental benefits of a sensor-enhanced collection system.
Main Methods:
- Development of Arduino-based low-cost sensors for textile bin monitoring.
- Deployment of sensors for over twelve months in Finnish outdoor conditions.
- Case study comparing conventional and dynamic collection schemes for discarded textiles.
Main Results:
- The sensor-enhanced dynamic collection system reduced costs by 7.4% compared to the conventional method.
- A time efficiency improvement of -7.3% was observed.
- A potential reduction of 10.2% in CO2 emissions was demonstrated.
Conclusions:
- Smart bins linked to dynamic route optimization significantly improve textile waste collection efficiency.
- Low-cost, flexible data collection tools are viable for real-world environmental monitoring.
- Digitalization of textile recycling offers substantial economic and environmental benefits.
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