An Efficient Edge Computing-Enabled Network for Used Cooking Oil Collection

Area of Science:

• Environmental Science
• Computer Science
• Engineering

Background:

• Over 98% of domestic cooking oil in Portugal is improperly disposed of, leading to environmental contamination.
• Recycling used cooking oil (UCO) into energy is hindered by inefficient collection methods.

Purpose of the Study:

• To develop and evaluate an IoT-based smart collection system for domestic UCO.
• To improve UCO recycling rates and reduce environmental pollution through efficient collection.

Main Methods:

• Implementation of the Smart Waste Accumulation Network (SWAN), an IoT solution using edge computing for UCO collection bins.
• Deployment of a countrywide network of smart bins in Portugal, processing data locally to ensure reliability during network failures.
• Comparative analysis of edge computing versus cloud computing for UCO collection efficiency over four years.

Main Results:

• An exponential increase in collected UCO was observed, with the SWAN system exceeding previous national collection totals.
• Improved estimation of optimal collection and maintenance intervals, enhancing operational efficiency.
• Demonstrated system scalability and resilience to communication network disruptions.

Conclusions:

• The SWAN system, leveraging edge computing, offers a scalable and efficient solution for domestic UCO collection.
• The approach significantly boosts UCO recycling rates and contributes to environmental protection.
• Edge computing provides a robust alternative to cloud-based systems for waste management networks.