Technology Category
Planning, Routing, and Scheduling: Optimization of Spatio-temporal SystemsIntelligent Robots: Multi-Robot SystemsApplication Domains: Internet of Things, Sensor Networks & Smart Cities
Smart Waste Management System for Makkah City using Artificial Intelligence and Internet of Things
🤖 AI Summary
During the Hajj pilgrimage, waste generation surges dramatically and exhibits highly dynamic spatial-temporal distribution, rendering conventional fixed-interval collection strategies ineffective and posing severe environmental and public health risks. To address this challenge, we propose TUHR—a scalable intelligent waste management system tailored for ultra-large-scale temporary religious events. TUHR introduces an adaptive waste management paradigm integrating ultrasonic fill-level sensors, MQ-series gas sensors (e.g., for H₂S detection), ESP32-based edge nodes, and lightweight AI models to enable real-time fill-level and hazardous gas monitoring, anomaly detection, and coordinated optimization of collection routes. The system supports dynamic scheduling and precise resource allocation, improving waste response time by 42% and reducing unnecessary patrol fuel consumption by 31.5%, thereby significantly enhancing sanitation resilience at holy sites. TUHR provides a generalizable, scalable methodology for intelligent solid waste management in high-density transient environments, directly supporting Saudi Arabia’s Vision 2030 goals for sustainable smart cities.
Technology Category
Application Category
📝 Abstract
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.
Problem
Research questions and friction points this paper is trying to address.
Addressing unpredictable waste accumulation during Makkah pilgrimage using AI and IoT.
Detecting harmful substances in waste containers to mitigate health risks.
Optimizing waste management resources for economic and environmental benefits.
Innovation
Methods, ideas, or system contributions that make the work stand out.
IoT sensors monitor waste levels dynamically
AI detects harmful substances like gas
Smart system optimizes waste collection resources
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