AI And IOT Based Smart Waste Management System

The rapid growth of urban populations has placed significant pressure on traditional waste management systems, leading to inefficiencies such as premature waste collection, overflowing bins, and environmental hazards.This paper presents a smart waste management system leveraging Internet of Things (IoT) and Artificial Intelligence (AI) technologies to optimize waste collection.The system integrates ultrasonic sensors for real-time waste level monitoring, load cells for weight measurement, and gas sensors (MQ-2) for hazardous gas detection.Data from these sensors are transmitted via Wi-Fi to cloud platforms (ThingSpeak and Blynk) for remote monitoring and decision-making.An AI model hosted on a FastAPI server analyzes the data to predict optimal collection times, reducing unnecessary pickups.Experimental results demonstrate the system's reliability in real-time monitoring, with accurate sensor measurements and timely notifications.The proposed solution enhances operational efficiency, reduces costs, and supports sustainable urban development.

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Publication Details

Journal
International Journal for Research Trends and Innovation
Published
2025-01-01
DOI
https://doi.org/10.56975/ijrti.v10i7.205546
Primary Topic
Internet of Things and AI
Type
article
Field-Weighted Citation Impact
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article

AI And IOT Based Smart Waste Management System

Syed Khaja Ahmeduddin Zakir, Huda saleh AL-Busaidi, Ameera Sulaiman Al Naabi
1 links
International Journal for Research Trends and Innovation
Internet of Things and AI
article

AI And IOT Based Smart Waste Management System

Syed Khaja Ahmeduddin Zakir, Huda saleh AL-Busaidi, Ameera Sulaiman Al Naabi
article en

Abstract

The rapid growth of urban populations has placed significant pressure on traditional waste management systems, leading to inefficiencies such as premature waste collection, overflowing bins, and environmental hazards.This paper presents a smart waste management system leveraging Internet of Things (IoT) and Artificial Intelligence (AI) technologies to optimize waste collection.The system integrates ultrasonic sensors for real-time waste level monitoring, load cells for weight measurement, and gas sensors (MQ-2) for hazardous gas detection.Data from these sensors are transmitted via Wi-Fi to cloud platforms (ThingSpeak and Blynk) for remote monitoring and decision-making.An AI model hosted on a FastAPI server analyzes the data to predict optimal collection times, reducing unnecessary pickups.Experimental results demonstrate the system's reliability in real-time monitoring, with accurate sensor measurements and timely notifications.The proposed solution enhances operational efficiency, reduces costs, and supports sustainable urban development.

International Journal for Research Trends and InnovationVol. 10(7)
Universitas Ibrahimy (ID)
Responsible consumption and production
Openalex Percentile: Top 71%
Internet of Things and AI
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