Abstract

Future university campuses will be characterized by a series of novel services enabled by the vision of Internet of Things, such as smart parking and smart libraries. In this paper, we propose a complete solution for a smart waste management system with the purpose of increasing the recycling rate in the campus and provide better management of the entire waste cycle. The system is based on a prototype of a smart waste bin, able to accurately classify pieces of trash typically produced in the campus premises with a hybrid sensor/image classification algorithm, as well as automatically segregate the different waste materials. We discuss the entire design of the system prototype, from the analysis of requirements to the implementation details and we evaluate its performance in different scenarios. Finally, we discuss advanced application functionalities built around the smart waste bin, such as optimized maintenance scheduling.

Highlights

  • The Internet of Things vision is becoming a reality, transforming the way we live and interact with the environment

  • We provide a brief description of such a management server: to fully test the functionalities offered, we provide a Smart Waste Bin simulator (SWB-sim), which allows simulating a multitude of SWB instances, providing enough data

  • We have presented the design and implementation of a waste management system for Smart Campuses

Read more

Summary

Introduction

The Internet of Things vision is becoming a reality, transforming the way we live and interact with the environment. Embedding different types of sensors and actuators into such waste bins, connecting them to the Internet and driving them through intelligent algorithms (i.e., following the vision of the Internet of Things (IoT)) may give an incredible boost to the recycling performance. Motivated by these reasons, this paper extends our previous paper [19] and describes the realization of a complete solution for the efficient management of USW.

Related Work
Prototype Design
Sensors and Actuators
Waste Sensing Module
Waste Classification Algorithm
Dataset
Waste Classification
Classification from Scalar Data
Classification from Images
Hybrid Classification
Waste Classifier Location
Recognition Time
Energy Consumption
Management Application
Management Server
TSP for waste collection
Findings
Conclusions
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call