# IoT-based Route Recommendation for an Intelligent Waste Management System

arXiv: https://arxiv.org/abs/2201.00180 · HTML: https://mlsanity.com/paper/2201.00180/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 51 references that are in the map.
- First posted on arXiv 1 Jan 2022.

## Builds on (most cited first, 6 of 6)

- [Edge Intelligence: The Confluence of Edge Computing and Artificial Intelligence](https://mlsanity.com/paper/1909.00560/) (2019)
- [AI-based Modeling and Data-driven Evaluation for Smart Manufacturing Processes](https://mlsanity.com/paper/2008.12987/) (2020)
- [Urban Sensing based on Mobile Phone Data: Approaches, Applications and Challenges](https://mlsanity.com/paper/2008.12992/) (2020)
- [Leveraging Artificial Intelligence to Analyze the COVID-19 Distribution Pattern based on Socio-economic Determinants](https://mlsanity.com/paper/2102.06656/) (2021)
- [Leveraging Artificial Intelligence to Analyze Citizens' Opinions on Urban Green Space](https://mlsanity.com/paper/2102.06659/) (2021)
- [Tales of a City: Sentiment Analysis of Urban Green Space in Dublin](https://mlsanity.com/paper/2107.06041/) (2021)

## Built on by (most cited first, 2 of 2)

- [Smart Waste Management System for Makkah City using Artificial Intelligence and Internet of Things](https://mlsanity.com/paper/2505.19040/) (2025)
- [An Intelligent Robotic and Bio-Digestor Framework for Smart Waste Management](https://mlsanity.com/paper/2604.14882/) (2026)

## Abstract (arXiv)

The Internet of Things (IoT) is a paradigm characterized by a network of embedded sensors and services. These sensors are incorporated to collect various information, track physical conditions, e.g., waste bins' status, and exchange data with different centralized platforms. The need for such sensors is increasing; however, proliferation of technologies comes with various challenges. For example, how can IoT and its associated data be used to enhance waste management? In smart cities, an efficient waste management system is crucial. Artificial Intelligence (AI) and IoT-enabled approaches can empower cities to manage the waste collection. This work proposes an intelligent approach to route recommendation in an IoT-enabled waste management system given spatial constraints. It performs a thorough analysis based on AI-based methods and compares their corresponding results. Our solution is based on a multiple-level decision-making process in which bins' status and coordinates are taken into account to address the routing problem. Such AI-based models can help engineers design a sustainable infrastructure system.