# Smart Waste Management System for Makkah City using Artificial Intelligence and Internet of Things

arXiv: https://arxiv.org/abs/2505.19040 · HTML: https://mlsanity.com/paper/2505.19040/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 14 of its 74 references that are in the map.
- First posted on arXiv 25 May 2025.

## Builds on (most cited first, 14 of 14)

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- [EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](https://mlsanity.com/paper/1905.11946/) (2019)
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- [DeepViT: Towards Deeper Vision Transformer](https://mlsanity.com/paper/2103.11886/) (2021)
- [Towards Robust Vision Transformer](https://mlsanity.com/paper/2105.07926/) (2021)
- [Monkeypox Skin Lesion Detection Using Deep Learning Models: A Feasibility Study](https://mlsanity.com/paper/2207.03342/) (2022)
- [A Web-based Mpox Skin Lesion Detection System Using State-of-the-art Deep Learning Models Considering Racial Diversity](https://mlsanity.com/paper/2306.14169/) (2023)
- [Smart Healthcare in the Age of AI: Recent Advances, Challenges, and Future Prospects](https://mlsanity.com/paper/2107.03924/) (2021)
- [IoT-based Route Recommendation for an Intelligent Waste Management System](https://mlsanity.com/paper/2201.00180/) (2022)

## Abstract (arXiv)

Waste management is a critical global issue with significant environmental and public health implications. It has become more destructive during large-scale events such as the annual pilgrimage to Makkah, Saudi Arabia, one of the world's largest religious gatherings. This event's popularity has attracted millions worldwide, leading to significant and un-predictable accumulation of waste. Such a tremendous number of visitors leads to in-creased waste management issues at the Grand Mosque and other holy sites, highlighting the need for an effective solution other than traditional methods based on rigid collection schedules. To address this challenge, this research proposed an innovative solution that is context-specific and tailored to the unique requirements of pilgrimage season: a Smart Waste Management System, called TUHR, that utilizes the Internet of Things and Artificial Intelligence. This system encompasses ultrasonic sensors that monitor waste levels in each container at the performance sites. Once the container reaches full capacity, the sensor communicates with the microcontroller, which alerts the relevant authorities. Moreover, our system can detect harmful substances such as gas from the gas detector sensor. Such a proactive and dynamic approach promises to mitigate the environmental and health risks associated with waste accumulation and enhance the cleanliness of these sites. It also delivers economic benefits by reducing unnecessary gasoline consumption and optimizing waste management resources. Importantly, this research aligns with the principles of smart cities and exemplifies the innovative, sustainable, and health-conscious approach that Saudi Arabia is implementing as part of its Vision 2030 initiative.